Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It does reveal a multi-step behavior: app detection, app creation with local_dir, git repo_url handling, and sandbox fallback. However, it omits important behavioral details such as side effects, required permissions, or what happens after deployment.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The text is short and information-dense, but it is not well structured or front-loaded. The first sentence is a cryptic runtime reference that obscures the tool's purpose, while the second sentence crams multiple deployment steps into a compact form that is hard to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a deployment tool with sequential behavior and no output schema or annotations, so the description needs to be more complete. It leaves gaps around what the `template` parameter controls, how the agent should discover valid templates, and what a successful deployment looks like. The pipeline mention helps but is not sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate, but it barely does. The only parameter, `template`, is never explained: no source, no format beyond the regex, no relationship to agent_templates_list or agent_templates_get. The title's mention of 'MONA Agent template' gives minimal context but not enough to select or format the parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description identifies a deploy action and a resource ('Deploy thư mục', 'MONA Agent template' in the title), and outlines a pipeline via cloud_app_detect and cloud_app_create. However, it never clearly states that this tool deploys a MONA Agent template using the `template` parameter, and the exact relationship with cloud_agent_deploy is ambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit guidance on when to use this tool versus siblings like cloud_agent_deploy or vibecloud_agent_deploy. The line 'Gọi cùng runtime với cloud_agent_deploy' is more of a runtime hint than usage guidance, and 'sandbox trước nếu chưa có host' is a procedural condition but not a clear selection criterion.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It clearly states the operation is 'Read', implying a non-mutating action, and enumerates the template components it accesses. However, it does not describe failure behavior, output format, or whether missing files are handled, leaving some gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

One short sentence, front-loaded with the action and the enumerated template components. Every word earns its place; there is no redundant explanation or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter read operation with no output schema, the description is mostly complete: it identifies the target and the scope of what is read. It lacks only minor behavioral details like what happens if the template does not exist, but overall it gives an agent enough context to call correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description only says 'của một template' (of a template), which merely echoes the property name without adding format details, examples, or how to construct the value. It does not compensate for the schema's lack of descriptive guidance.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a clear verb 'Đọc' (Read) and specifies the exact resource: the README, AGENTS.md, tools, deploy, checklist, and skills of a template. This clearly distinguishes it from sibling tools like agent_templates_list (which lists templates) and agent_deploy (which deploys).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool is used to inspect template contents, but it does not explicitly state when to use it versus alternatives or mention any exclusions. The context signals and sibling names help, but the description itself offers no direct routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden of behavioral disclosure. It implies a read operation via 'Đọc' but does not disclose return format, side effects, network behavior, or whether any of the deployment steps are actually performed by this tool. The deployment sentence is ambiguous and could be mistaken as part of this tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and mostly front-loaded with the main purpose. However, the second sentence about deployment is tersely written and mixes workflow instructions into the tool description, making the overall structure less coherent than it could be.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter list tool, the description gives the main sources and a deployment follow-up, but it omits what the tool actually returns (e.g., a list of template names, metadata) and does not clarify how it differs from agent_templates_get. Without an output schema or annotations, this leaves meaningful gaps for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters and the schema fully covers them, so there is little for the description to add. The mention of template sources is contextual rather than parameter documentation, which is acceptable given the empty input schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the action ('Đọc template') and the resources (local folder, URL catalog, integrated wave 1 catalog). It does not explicitly distinguish this from the sibling agent_templates_get, and the second sentence about deployment slightly muddies the purpose, but the core purpose is understandable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives a workflow hint: after reading templates, deploy via cloud_app_detect then cloud_app_create, using a sandbox first if no host exists. However, it never explicitly states when to use this tool versus alternatives such as agent_templates_get, and the deployment sentence is more of an imperative than a selection guideline.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full disclosure burden. It does usefully reveal that the tool currently returns a clear stub status and that sandbox mode is free with no wallet needed. However, it does not explain actual side effects, authentication requirements, or what happens outside sandbox mode.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and contains no filler; the stub status and sandbox behavior are stated in a single short sentence. The main downside is that 'Slot runtime agent wave' is dense and unclear, which reduces usability despite the economy of words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a deploy-like tool with no annotations, no output schema, and an undocumented required parameter, the description is incomplete. An agent cannot fully infer what template means, what a successful non-stub response would look like, or which sibling tool should be chosen instead.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The required parameter 'template' has no schema description and the description never mentions it, leaving its meaning unclear. The sandbox=true wording is essentially duplicated from the schema, so it adds little new semantic value beyond what is already structured.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a verb ('Slot') and a resource ('runtime agent wave') and states that it returns a clear stub status, so it is not a pure tautology. However, 'Slot runtime agent wave kế tiếp' is cryptic and does not clearly say whether this actually deploys an agent, schedules a wave, or returns a placeholder. It also does not distinguish itself from siblings like agent_deploy or vibecloud_agent_deploy.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance about when to use this tool versus the many sibling deploy tools. The sandbox=true note is parameter-level information, not tool-selection guidance. No alternatives or exclusions are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the behavioral transparency burden and does add useful non-obvious details: first host creation takes ~2–3 minutes while later deploys take 10–20 seconds; sandbox=true is free and creates no real infrastructure; cost approval is needed only once; and the workflow polls until done/succeeded. It does not cover error behavior, authentication prerequisites, or edge cases like the relationship between local_dir and repo_url, but it discloses the most consequential behaviors.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense, repetitive, and mixes Vietnamese and English, duplicating the same workflow in prose and in the final English summary. It reads as a process narrative rather than a tool definition, and the first sentence focuses on timing ('App từ git đã live...') instead of a clean purpose statement. It would benefit from a short definition followed by essential workflow notes.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex 14-parameter tool with no annotations and no output schema, the description is not complete enough for reliable invocation. It does provide helpful end-to-end context around sandbox estimation, cost approval, polling, and returning a URL, but it leaves major gaps around required inputs, build configuration, wait/timeout behavior, and the exact response shape. An agent would still have to guess about many parameters.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 7%, with only sandbox described in the schema. The prose adds meaning for sandbox=true/false and mentions local_dir, repo_url, and domain, but the remaining ~11 parameters (name, port, wait, branch, build_type, dockerfile, app_host_id, timeout_sec, interval_sec, env) are left entirely undocumented in both the schema and the description. This is a significant gap for a 14-parameter tool.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description conveys that this tool creates and deploys a cloud app from a local directory or git repository and returns a URL, especially via the English summary 'upload and deploy, return URL, then attach an optional domain.' It distinguishes itself from agent_deploy by explicitly saying 'không gọi agent_deploy cho deploy dự án.' However, the core purpose is embedded in a long, multi-step workflow rather than stated as a crisp one-line definition.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides an explicit workflow: run cloud_app_detect locally, check host/prices/balance, create with sandbox=true to estimate cost, get human approval, create with sandbox=false, poll until succeeded, and optionally add a domain. It also gives a clear exclusion: do not call agent_deploy for project deployment. It does not contrast with cloud_app_deploy, but it gives enough context for when to use this pipeline.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses that the tool deletes the app, domain, and A record, and that the app host may still be charged afterward — an important behavioral consequence. However, it does not state whether the action is irreversible, what permissions are needed, or what happens on failure, so it is only partially transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short but poorly structured: it leads with unrelated timing information about git apps ('app host đầu tiên ~2–3 phút, deploy sau đó 10–20 giây') before stating the actual deletion purpose. The core message is buried at the end, and the bilingual mixing creates noise. This is not an example of efficient front-loading.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has only two parameters and no output schema, and the description gives the essential effect (delete app/domain/A record) and an important consequence (possible host charges). Still, it does not mention what the response will contain, how to confirm success, or any error-handling behavior. For a destructive tool, this leaves meaningful gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema covers 50% of parameters: 'sandbox' is well documented in the schema, so the description does not need to repeat it. For 'app_id', the description only weakly implies it should be an approved app's ID. It does not explain where to find app_id or distinguish it from other app-related identifiers, so it adds modest value at best.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description includes a clear action-and-resource statement: 'Delete an approved app.' It also specifies what the deletion covers ('xoá app/domain/A record'), which adds precision. However, it does not differentiate from the sibling 'vibecloud_app_delete' or clarify what 'approved' means, so it is not a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'Sau khi user duyệt xoá' gives a clear precondition: use the tool only after the user has approved the deletion. It also warns about a post-delete consequence ('app host vẫn có thể tính phí'), which informs the decision to delete. It does not explicitly name alternatives or exclusions, but the usage context is clear enough.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden and discloses meaningful behavior: timing estimates (first host ~2–3 min, subsequent deploys 10–20 sec), the ZIP→upload→job→deploy pipeline, redeploy semantics for omitted local_dir, and the fact that the tool polls. Gaps remain — failure behavior and whether the live app is overwritten are unstated — but this is far more transparent than typical.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact but structurally weak: it opens with a release-note-style 'Git apps are live' line and saves its clearest purpose statement for the end. Every point is duplicated in Vietnamese and English, roughly doubling the length without doubling the information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutating 6-parameter tool with no annotations and no output schema, significant gaps remain: there is no statement of what the tool returns (job ID? status?), what the required app_id refers to, or how this relates to app creation tools. The process and timing are well covered, but an agent still cannot predict the invocation result.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 17%, so the description must compensate; it does well for local_dir, explaining its dual role of fresh ZIP upload versus redeploying the existing archive. But the required app_id is never explained as identifying the target app, and wait/timeout_sec/interval_sec are only gestured at through the single word 'poll'.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The final sentence states a specific action — 'Redeploy uploaded source or a git app and poll' — with a clear verb and resource. However, the opening line 'App từ git đã live' reads like a changelog announcement rather than tool documentation, and the description never distinguishes this from the near-identical sibling vibecloud_app_deploy.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives useful when-to-include/when-to-omit direction for local_dir ('bỏ local_dir để redeploy bản đã upload'), and the pipeline 'upload → chờ job → deploy' implies the conditions under which upload happens. But it names no alternative tools — cloud_app_create for new apps and vibecloud_app_deploy are never referenced — and provides no when-not-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioral disclosure burden. It explicitly states two key traits: the operation is completely offline and it does not execute project code, and it also lists what will be detected. It does not describe behavior on invalid or missing directories, but the core safety profile is clearly communicated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loaded with the output list and safety constraint, making it easy to scan. The bilingual phrasing creates slight redundancy, but both parts are brief and the English sentence serves as a compact summary.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter detection tool with no output schema, the description covers both what the tool detects and the important safety guarantee, so an agent can predict the call's behavior and likely return content. The main gap is the absence of explicit error behavior for missing or unsupported directories, but that is minor given the enumerated output fields.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage and only one parameter, local_dir, so the natural-language description must compensate. It indirectly clarifies that local_dir refers to a local project/app directory whose stack and metadata will be detected. However, it does not state path format, whether the directory must exist, or what happens if detection fails, so the compensation is only partial.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific action (detect/nhận diện) on a local app and enumerates concrete outputs: Node/Next/Vite/Python/PHP/static, port, start, Dockerfile, build_type, and .env.example variable names. This makes it clearly distinct from sibling app lifecycle tools like cloud_app_create, cloud_app_list, and cloud_app_get, which operate on deployed resources rather than local directories.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly implies this is for analyzing a local directory, and the 'offline / no code execution' note gives useful safety context. However, it does not explicitly state when to use this tool versus alternatives, such as using it before cloud_app_deploy or using cloud_app_get for an already-deployed app. The routing guidance is left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden. It discloses that the API returns CNAME instructions and that HTTPS verification should wait for DNS, which is meaningful. It does not mention mutation side effects, idempotency, failure conditions, or costs beyond what sandbox implies.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The first sentence about deploy timing (~2–3 minutes, 10–20 seconds) is irrelevant for adding a domain and adds noise. The bilingual repetition lengthens the text, and the core instruction is buried in the middle rather than front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema or annotations, so the description must define both behavior and return. It does mention CNAME instructions, which is helpful, but it leaves app_id semantics, exact response shape, approval failure handling, and the overall add-domain workflow incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 33% (only sandbox is described), so the description must compensate. It implies host is the custom domain and adds the important "approved domain" constraint, but it never explains app_id or how host relates to the CNAME flow. Two required parameters remain effectively undocumented.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

"Attach custom domain" and "Thêm domain đã được duyệt" clearly state the verb and resource. The operation is distinct from app create, list, host list, deploy, and logs siblings. It does not differentiate from the nearly identical vibecloud_app_domain_add sibling, so it stops short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives useful context: the domain must already be approved and you must wait for DNS before checking HTTPS. However, it never explicitly states when to use this tool versus alternatives, nor does it mention prerequisites like needing an existing deployed app or where to get app_id.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description properly carries behavioral disclosure: it warns that the entire env is replaced, instructs sending the full map of entries to keep, says not to log secrets, and notes that deploy must be called afterward. This is meaningful beyond the plain 'Set app environment' statement.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is cluttered with bilingual repetition, including 'Git apps are live' twice, and it opens with deploy timing that is not central to this tool's purpose. The actual purpose statement is buried at the end, making it harder for an agent to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 3-parameter tool with no output schema, the description is incomplete. It provides useful operational notes but fails to clearly document parameter meanings, what happens before approval, or what the caller should expect after invoking deploy. The mixed structure further reduces completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is low at 33%, and the description does not compensate enough. It adds some context about the env map ('send full map to keep'), but it never explains app_id or sandbox, and it mostly restates what the schema already implies for env.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description ends with 'Set app environment' and refers to replacing the entire env, making the core action clear. It does not explicitly say 'environment variables' but the meaning is recoverable from context and schema. It is not a tautology and is distinguishable enough from siblings like cloud_app_deploy.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly instructs calling cloud_app_deploy afterwards to apply the environment changes, which gives an ordered workflow. It does not state when not to use this tool or mention alternative tools, but the follow-up step provides useful usage guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral burden itself and does state this is a read/inspect operation, which implies no destructive side effects. It adds useful context about deployment timing (first host 2-3 minutes, subsequent deploys 10-20 seconds), but it does not disclose output structure, error behavior, or prerequisites beyond that.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a mixed-language, somewhat redundant jumble: the same statement appears in Vietnamese and English, and the deployment timing note is placed before the core purpose. The key phrase 'Inspect app' is buried at the end, and the sentence about host timing would be better as secondary context.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has no annotations and no output schema, so the description must supply context on its own. It lists some returned fields and gives deployment timing, but it omits the meaning of the app_id parameter, how output is structured, and when to choose this tool over the many sibling app tools, leaving notable gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 50%; the sandbox parameter has a description in the schema, but app_id has none and the tool description does not explain it either. The description names return fields but never connects them to the parameters, so it fails to compensate for the undocumented app_id.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the tool as an inspection/read operation for a single app, enumerating the data it returns: status, URL, deployments, and app host. It is distinguishable from sibling list tools like cloud_app_list and cloud_app_host_list by focusing on a single app's details, though it does not explicitly name those alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies this tool is used after an app has been deployed from Git, with timing context for the first host and subsequent deploys, and its purpose is to read app status/URL/deployments. However, it gives no explicit when-to-use or when-not-to-use guidance versus alternatives such as cloud_app_list, cloud_app_detect, or cloud_app_logs.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It does add meaningful context: it declares the operation is a read ('Đọc'), states that git apps are live, and gives concrete timing expectations for host readiness. However, it does not disclose what the response contains, whether sandbox=true changes the returned data, or how empty results are signaled beyond the implied 'no host yet' case.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a run-on mixing three distinct concerns: timing expectations, workflow routing, and the actual purpose statement. The core purpose ('List app hosts') appears last instead of being front-loaded, and the same content is redundantly repeated in Vietnamese and English. While short in total length, the structure forces the agent to parse through operational noise to find the primary function.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a low-complexity tool — one optional boolean parameter, no output schema, no nested objects — so the description doesn't need much. It covers the key operational context: when hosts are available, how long to wait, and what to do if none exist. The main gap is that without an output schema, the description never hints at the shape or content of the returned host list, leaving the agent guessing about the response format.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% — the sandbox parameter already has a clear description ('Thử 0đ, không tạo hạ tầng thật / Sandbox, no charge'). The description reinforces this by referencing 'sandbox cloud_app_create' as the estimation path, connecting the sandbox flag to a concrete workflow. This adds marginal context beyond the schema but doesn't meaningfully expand parameter semantics, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the operation in both languages: 'List app hosts' and 'Đọc app host' (read app hosts), combining a specific verb with a resource. It is distinguishable from sibling tools like cloud_app_list (lists apps) and cloud_app_get (gets a single app) because it targets hosts specifically. The purpose statement exists but is buried at the end after timing and workflow context, which slightly weakens it.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit routing guidance: 'chưa có host thì sandbox cloud_app_create trước để ước tính' (if there's no host yet, use sandbox cloud_app_create first to estimate), telling the agent exactly what to do when this tool would return nothing useful. It also sets timing expectations (first host ~2–3 minutes, subsequent deploys 10–20 seconds) that help the agent decide whether to wait or retry. It doesn't explicitly contrast with cloud_app_list or the vibecloud_app_host_list sibling, but the primary decision boundary is covered.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the disclosure burden. It implies a read-only listing operation by saying 'Liệt kê' and adds deployment-timing context, but it does not state whether the list is limited to the current user, whether sandbox mode changes results, or what the response contains. The timing note is interesting but only marginally relevant to this tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is cluttered with bilingual repetition ('App từ git đã live' / 'Git apps are live'), an unrelated timing statement about first app hosts, and the core instruction 'List apps' is buried at the end. The useful guidance about listing before creating is present but not front-loaded, and several words do not earn their place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple list tool with one optional parameter, the description is minimally usable: an agent can infer it should call this before app creation. However, there is no output schema, so the description should clarify what the response includes, and it fails to distinguish this tool from cloud_app_host_list or vibecloud_app_list, making tool selection riskier.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% for the single optional sandbox parameter, so the schema already documents it fully. The description does not mention sandbox at all, but the baseline of 3 applies because the schema carries the semantic weight and the description adds nothing that conflicts or enhances it.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear verb and resource: 'List apps.' It also adds context that listing should happen before creating to avoid duplicates, which distinguishes it from app-creation tools. However, it is muddled by unrelated deployment-timing notes and does not explicitly differentiate from cloud_app_host_list or cloud_app_get.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Liệt kê app trước khi tạo để tránh trùng' gives a clear, practical condition for when to use this tool: list existing apps before creating a new one to prevent duplicates. It does not mention exclusions or alternative list tools, so it stops short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the behavioral disclosure burden. It discloses that at most 500 log lines are read, logs may contain secrets, raw logs should not be exposed publicly, and includes deployment timing behavior. These details go beyond the schema, though auth requirements and rate limits are not mentioned.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and information-dense, but it is fragmented and mixes Vietnamese and English with some redundancy. The actual purpose, 'Read deployment logs,' is placed at the end rather than front-loaded, making the structure less effective than it could be.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple read-only logging tool, the description provides useful context: log line limit, secret handling warning, and timing expectations. However, it ignores the required app_id parameter, leaves deployment ambiguous, and does not describe the return format. Since there is no output schema, these gaps are noticeable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 33%, and the description does not compensate. The app_id and deployment parameters are left without meaningful explanation, and the description does not clarify how 'deployment' relates to the log request. Only sandbox has a schema description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb and resource: 'Read deployment logs.' It also adds context that the tool applies to git-based apps once they are live. It does not differentiate itself from the sibling vibecloud_app_logs, so it falls short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides relevant timing context ('first app host ~2–3 min, deploy later 10–20 seconds') and warns about secrets, which indirectly helps an agent decide when expectations are realistic. However, it does not explicitly state when to use this tool versus vibecloud_app_logs or when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

There are no annotations, so the description carries the behavioral transparency burden. 'Đọc' clearly indicates a non-mutating read operation, and the VND/general-wallet scope adds useful precision. It does not describe response format or potential edge cases, but for a zero-parameter read tool this is minimally sufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single Vietnamese sentence conveys action, resource, currency scope, and the intended timing. Every phrase earns its place, and the core action is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple, parameter-free read-only balance tool with no output schema, this description is complete enough for an agent to decide when and how to invoke it. The purpose, resource, currency, and usage context are all explicit.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, so there is no parameter documentation burden. The description does not need to explain input semantics, and the schema already reflects no required inputs.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a clear verb ('Đọc'/'read') with a specific resource ('số dư ví VND chung'/'general VND wallet balance'), and adds a concrete purpose: checking before creating paid resources. It is distinct in intent from financial siblings like cloud_topup and cloud_ledger, though it does not explicitly name or contrast a sibling.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description states a clear usage context: read the balance before creating paid resources. This gives the agent a concrete trigger for invoking the tool, though it does not explicitly mention when not to use it or suggest alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so the description carries the full burden. It discloses the data returned (limits and usage by period) and implies a non-mutating operation, but it does not state authorization needs, what 'period' means, or the output format. This is minimal but not misleading.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, focused sentence with no filler. It front-loads the action and the subject matter, which is appropriate for a parameterless read tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and no annotations, the description must explain what the agent will get back; it does say 'limits and usage by period.' However, 'period' is left ambiguous and there is no mention of whether this reflects the current billing cycle or how the data is structured, so the description is only moderately complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters and schema description coverage is 100%, so the baseline of 4 applies. The description appropriately implies no configuration is needed beyond calling the tool.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Liệt kê' = list) and names the resource (limits and usage by period), making the tool's read intent clear. It does not explicitly distinguish itself from siblings like cloud_budget_set or cloud_usage, but the 'get' vs 'set' pairing strongly signals a read operation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The read-only usage is implied by the verb 'Liệt kê' and the tool name, suggesting it should be used when the agent needs to check budget limits or consumed amounts. However, it provides no explicit guidance about when to prefer this over cloud_balance, cloud_usage, or cloud_budget_set.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure, yet it only states the action. It does not reveal whether the call creates or overwrites an existing budget, whether limit_vnd is a hard cap or a soft alert, or what side effects occur for running resources. For a write operation, this is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single Vietnamese sentence with zero filler; the verb and scope dimensions are front-loaded. Every word earns its place, though the brevity comes at the cost of completeness, which is penalized in other dimensions.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 4 required parameters, no annotations, and no output schema, yet the description is only one short sentence. An agent lacks the information to construct valid calls (ID formats, limit semantics, period behavior) or to anticipate the consequences of setting a budget.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description should compensate, but it only echoes the scope enum values. It gives no guidance on scope_id (whose ID, where to find it), how limit_vnd is interpreted (per period, total, tax-inclusive), or what period means in billing terms.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Đặt giới hạn chi tiêu' (set spending limit), and enumerates the three scopes (product, project, token). This clearly identifies what the tool does and reads as the write counterpart to cloud_budget_get. However, it doesn't explicitly differentiate from cloud_token_limit, whose scope could overlap when scope=token, so full sibling differentiation is missing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given on when to use this tool versus alternatives. The description neither mentions that reading budgets belongs to cloud_budget_get nor explains how this differs from cloud_token_limit or cloud_subscription_update. The agent must infer usage purely from sibling tool names.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the behavioral burden. It usefully discloses that the code must be user-provided and approved, and it warns against guessing. However, it does not describe the tool's effects such as code consumption, credit application, or failure behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded, stating the action and the critical safety guardrail in two short clauses. The bilingual wording is not pure duplication: the Vietnamese adds the explicit 'do not guess' rule while the English names the approved promotional credit code.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-string-parameter redemption tool with no output schema, the description is nearly complete: it identifies the required input, the consent condition, and a safety rule. It omits return/result behavior and explicit platform differentiation from vibecloud_credit_redeem, but these are minor for selecting and invoking correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema only describes 'code' as a 2-64 character string with no semantic explanation. The description adds that it is a promotional credit code supplied by the user, which materially clarifies the parameter. Format details are still absent, but for a single simple string this is adequate compensation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a redeem action on a credit code ('Redeem an approved promotional credit code') and adds that the code must be user-approved. It does not explicitly differentiate cloud_credit_redeem from vibecloud_credit_redeem beyond the tool name, so it falls short of a perfect 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives an explicit precondition: only redeem codes the user has provided and agreed to. It also gives an explicit prohibition: do not guess codes. It does not name an alternative tool, but the main decision rule for safe usage is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the behavioral disclosure burden. It usefully reveals that wallet verification happens first, the operation returns a job_id for polling, and sandbox mode avoids charges. However, it does not disclose billing/charge behavior beyond the sandbox case, failure modes, or what happens after the job completes.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two short sentences with no filler. The core workflow is front-loaded ('check wallet, then create') and the sandbox exception is stated compactly afterward. Every phrase contributes useful information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a complex creation tool with seven parameters, no annotations, and no output schema, so the description needs to provide more context. It mentions job_id for polling but does not explain package_slug, resource sizing semantics, or how results/errors will be returned. An agent would likely need to inspect sibling tools or infer too much to invoke this correctly in non-sandbox cases.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 14%, so the description must compensate for the undocumented parameters. It only repeats the engine types and the sandbox meaning already present in the schema, while cpu, ram_gb, disk_gb, package_slug, and app_name receive no added semantic guidance. For a seven-parameter tool, this is insufficient.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('tạo'), the resource types (MongoDB/PostgreSQL/MySQL), and the asynchronous behavior (returns job_id to poll). The title 'Tạo database MONA Cloud' also differentiates it from the sibling vibecloud_create_database. It is clear and actionable, though the description itself does not explicitly contrast it with sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context that the tool checks the shared wallet before creating and that sandbox=true is for free trials without a wallet. This gives some when-to-use guidance, but it does not mention alternatives or conditions such as when to prefer vibecloud_create_database or cloud_vps_create.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral burden. The verb 'List' / 'Đọc' does communicate a read-only operation and 'monthly invoices' scopes the subject matter, but the description does not disclose pagination, ordering, filtering behavior, or the shape of the returned invoice list.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two short clauses, action-first, with no filler. The Vietnamese and English versions are near-duplicates, but bilingual clarity is acceptable for a multilingual MCP agent and the overall size is appropriately minimal.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple zero-parameter listing operation, the description is sufficient to convey the intended call and the general result: a list of monthly invoices. It omits return-field details, but that is acceptable given the simplicity and the absence of an output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has zero properties and full coverage, so there are no parameter semantics to explain. The description adds no parameter details, but none are needed for a zero-parameter tool; the 0-parameter baseline of 4 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the action ('List' / 'Đọc') and the resource ('monthly invoices' / 'hoá đơn hàng tháng') with account scope. It is clear about what the tool does, though it does not explicitly distinguish itself from vibecloud_invoice_list or cloud_invoice_pdf.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the obvious use case: listing monthly invoices for the account. It provides no explicit guidance about when not to use it or which sibling tool to select instead, such as cloud_invoice_pdf for PDFs or vibecloud_invoice_list for the VibeCloud platform.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full behavioral burden. It discloses the key behavioral trait: the PDF is written to a private temporary file, a path is returned, and the file may be cleaned up by the OS, so the caller must copy it elsewhere. This is meaningful transparency beyond a bare action.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is one concise bilingual sentence with a clear order: action, output, and critical warning. Every element contributes value and the most important caveat about temporary-file cleanup is included without bloat.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter tool with no output schema and no annotations, this description covers the essential context: what is downloaded, where it is stored, what is returned, and what the caller must do before cleanup. It would be more complete if it noted how to obtain the invoice_id, but the core invocation contract is clear.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It does add some context by framing the operation as downloading an invoice PDF, implying invoice_id identifies the target invoice. However, it does not explain where invoice_id comes from or provide any format/lifecycle details, so compensation is minimal.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states a specific verb and resource: download an invoice PDF to a temp file and return its path. It is easy to distinguish from listing tools like cloud_invoice_list, though it does not explicitly differentiate itself from the sibling vibecloud_invoice_pdf.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool—when an invoice PDF needs to be downloaded—and includes the operational advice to copy the file before OS cleanup. However, it does not mention alternatives, exclusions, or how this differs from vibecloud_invoice_pdf.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full behavioral burden. It discloses the sandbox auto-detection trait, but omits the blocking/polling behavior implied by wait, timeout_sec, and interval_sec, and says nothing about return shape or failure modes. For a status-waiting tool this is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with no wasted words; the main action leads and the sandbox caveat follows. It is efficient, though it earns brevity at the cost of omitting polling behavior.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 5 parameters, no annotations, and no output schema, the description is too thin. An agent cannot tell what wait=true does, how timeout_sec/interval_sec drive the polling loop, or what a job status result looks like, so it cannot invoke the tool with full confidence.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 20% (only sandbox is documented in schema), well below 50%, so the description must compensate. It adds meaning for sandbox (auto-detected, no header needed) and implies job_id via 'theo ID', but wait, timeout_sec, and interval_sec remain entirely unexplained in both schema and description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb+resource: 'Đọc job thật hoặc sandbox theo ID' (read real or sandbox job by ID), and the title 'Theo dõi job MONA Cloud' confirms it is a MONA Cloud job-status tracker. It is distinguishable from the sibling vibecloud_job_status via the MONA Cloud naming, though the description itself does not explicitly name that sibling.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives such as vibecloud_job_status. The note 'API tự nhận diện sandbox nên không cần header' is an invocation hint, not a when-to-use or exclusion statement, so an agent gets no tool-selection direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral disclosure burden. It communicates a read-only operation and specifies the types of ledger entries involved (deposits, deductions, refunds). However, it does not mention pagination behavior, result ordering, or what happens when ledger data is unavailable.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no filler. Every word contributes to stating the operation and the resource, making it easy to scan and understand quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has no annotations and no output schema, so the description must cover more ground. It identifies the ledger entry types but omits output expectations, pagination behavior, and differentiation from closely related sibling tools, leaving the agent with an incomplete picture for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description needed to compensate by explaining pagination-related parameters. It does not mention 'limit' or 'cursor' at all. The schema provides basic constraints, but the description adds no semantic value for these parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Đọc' / read) and names the exact resource: ledger lines covering deposits, deductions, and refunds. It is clear about what the tool accesses, though it does not explicitly differentiate it from sibling tools like cloud_balance or monapay_list_transactions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool instead of related siblings such as cloud_balance, cloud_usage, or monapay_list_transactions. There is no mention of exclusions, prerequisites, or the context in which ledger reading is the appropriate choice.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full disclosure burden. It does add one genuinely useful behavioral fact — the vc_live token conversion only happens while the upstream is in legacy mode — which reveals state-dependent behavior. But it never states whether the operation mutates state, is idempotent, requires a prior link to exist, or what the caller receives in return.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single front-loaded sentence with no filler: the core confirmation action appears first and the conditional behavior follows. The density of unexplained domain jargon slightly hurts readability, but structurally it is tight and every clause earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no annotations, no output schema, and no parameters, the description must fully explain invocation expectations — and it does not. An agent cannot determine what MONA Pass or vc_live token are, what 'upstream old mode' refers to, whether this is a read or write operation, or what a successful call yields. The presence of near-named siblings with no differentiation widens the gap further.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool declares zero parameters, so schema coverage is trivially 100% and there is nothing for the description to add about parameter meaning. The baseline of 4 for 0-parameter tools applies; no parameter guidance is needed or missing.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description does use a specific verb ('Xác nhận' / confirm) and names a concrete resource (MONA Cloud compute receiving MONA Pass), plus a conditional conversion behavior, so it is not a tautology. However, the core terms — 'MONA Pass,' 'vc_live token,' 'upstream,' and 'chế độ cũ' — are unexplained jargon that an agent cannot reliably resolve. It also gives no hint of how this differs from the similarly named siblings monapay_link and vibecloud_link.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The only conditional in the text ('chỉ đổi thành vc_live token khi upstream còn ở chế độ cũ') describes an internal behavioral branch, not when the agent should call this tool. There is no mention of alternatives, prerequisites, exclusions, or any routing guidance between cloud_link, monapay_link, and vibecloud_link, so the agent is left to guess.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description clarifies that the tool returns a URL rather than actually opening the console, which is useful given the 'open' in the tool name. However, with no annotations, the description carries the full burden and does not disclose any prerequisites, side effects, or URL characteristics such as expiration or authentication requirements.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is one concise sentence, front-loaded with the primary action 'Trả URL' (return URL). It efficiently conveys purpose and use cases with no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a parameterless tool with no output schema and no annotations, the description adequately explains what the tool returns and why. It could explicitly state the return format (e.g., a string URL) or any required authentication, but these are largely inferable from the description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters and the input schema is empty, so the baseline for parameter semantics is 4. The description reinforces the tool's purpose but adds no parameter-specific meaning because there are no parameters to document.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb 'Trả URL' (return URL) and a specific resource 'console chung' (common console), and lists three clear use cases: topping up wallet, changing budget, or managing account. This distinguishes it from action-oriented siblings like cloud_topup or cloud_budget_set, though it does not explicitly name any alternative.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context by stating the intended use cases ('để nạp ví, đổi budget hoặc quản lý tài khoản'). This tells the agent when the tool is appropriate, but it does not explicitly state when not to use it or name alternative tools, so it falls short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioral burden. It does disclose the core behavior — listing package slugs with CPU/RAM/disk specs — which implies a read-only query. However, it doesn't clarify whether the list shows all available packages or only the user's, nor whether authentication is required.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

One short Vietnamese sentence with a front-loaded verb and no filler. Every word contributes either the resource or the returned fields, and the length is appropriate for a parameterless list operation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple zero-parameter list tool with no output schema, the description covers the essential need by naming the returned fields. It is slightly incomplete only because it doesn't situate itself among the cloud/vibecloud sibling family or clarify the scope of the listing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters and an empty input schema, so the baseline of 4 applies — there is nothing the description needs to document about parameters. Its focus on output fields is the appropriate use of the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb (liệt kê/list), a resource (MONA Cloud packages), and the exact output fields (package_slug, CPU/RAM/disk), so an agent knows what the tool does and returns. The title reinforces the platform. It doesn't explicitly distinguish itself from vibecloud_packages or cloud_plan_list, but the 'cloud_' prefix and title provide partial differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given about when to call this tool versus the many overlapping siblings (vibecloud_packages, cloud_plan_list, cloud_prices, cloud_services_list). There are no exclusions, conditions, or alternative references, so an agent must guess which listing tool satisfies its intent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the disclosure burden. It usefully indicates the tool returns a plan/pricing table and a sizing recommendation, and frames the operation as reading before cost approval. However, it does not explicitly state read-only safety, output shape, or side-effect behavior beyond the implicit 'list' semantics.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded with the main output (plans with monthly/yearly prices), then the sizing recommendation and usage context. The bilingual structure adds a little redundancy, and the 'admin_only không tự chọn' phrase is slightly cryptic, but overall there is no wasted filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a low-complexity listing tool with three optional, self-descriptive parameters and no output schema, the description gives enough to call correctly: it lists plans and prices, accepts resource requirements for a sizing suggestion, and is meant to be read before cost approval. It could be more explicit about no-argument behavior and output structure, but these are minor gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It does clarify that cpu, ram_gb, and disk_gb represent the required/resources values used for the cheapest-fit recommendation. It does not explain behavior when all parameters are omitted or add per-parameter detail, leaving only the self-explanatory property names.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly says the tool lists plans with monthly/yearly prices and gives a recommendation for the cheapest plan meeting CPU/RAM/disk requirements. It uses specific verbs like 'List' and 'gợi ý' against a concrete resource, though it does not explicitly differentiate itself from similar siblings such as cloud_packages or cloud_prices.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives a clear usage context: read this before approving costs, and notes an admin-only constraint with 'admin_only không tự chọn'. It does not name alternative tools for different scenarios, but it does convey when and under what restriction the tool should be used.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations present, the description carries the full behavioral burden. It discloses that this is a read operation ('Đọc') with no side effects, but it adds nothing else: no mention of response format, freshness, or limitations. This is minimally viable for a zero-parameter read tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is one short, front-loaded sentence that states exactly what the tool does without wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a no-parameter, no-output-schema read tool, the description is nearly complete: the agent knows the operation, resource, and scope from the title. It could be improved by explicitly noting the return is a price list and differentiating from vibecloud_prices, but these are minor for this simple tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters and the schema confirms an empty object, so there are no parameters to document. Per the rubric, 0 params earns a baseline of 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Đọc đơn giá giờ hiện hành' (read the current hourly price list). Combined with the title 'Bảng giá MONA Cloud', it clearly identifies this as the MONA Cloud pricing lookup and distinguishes it from the sibling vibecloud_prices tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'current hourly price' implies when the tool should be used, but there is no explicit when-to-use or when-not-to-use guidance, and no mention of alternatives such as vibecloud_prices or cloud_packages. The intended selection context is inferred from the title rather than stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full behavioral disclosure burden. It usefully warns that the command can incur costs, advises checking the wallet, and explains that sandbox=true is free and wallet-free. However, it does not disclose whether rebuilding destroys existing data or causes downtime, which is significant for a rebuild operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and well-structured: purpose first, then the cost warning, then the sandbox clarification. Every sentence earns its place, and there is no redundant filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a potentially costly and destructive operation with no output schema and no annotations, the description omits important context: what rebuild actually does to the service, how to obtain a valid service_id, and whether there is a way to track completion. The cost and sandbox notes are helpful, but safe invocation still requires significant inference.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 50%, and the description only repeats the sandbox parameter's schema text. The service_id parameter, which is required, receives no semantic explanation beyond its name. The description fails to compensate for the undocumented parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('rebuild') and resource ('VPS/database MONA Cloud'), making the core operation clear. It is distinguishable from start/stop tools by the rebuild verb, though it does not explicitly differentiate from the closely related sibling vibecloud_rebuild.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides operational caveats about cost and sandbox mode, but gives no guidance on when to prefer this tool over alternatives like cloud_service_start, cloud_service_stop, or vibecloud_rebuild. There is no clear 'use this when...' statement.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description does the work: it discloses the scope of what is aggregated (VPS/databases plus virtual accounts/webhooks) and the title suggests a read-only status view. However, it never explicitly says the operation is non-mutating, what 'Gom' returns, or whether stopped/failed resources are included.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and free of fluff, with the resource scope listed front-loaded. It loses a point because the colloquial 'Gom' and the ambiguous 'cùng' chain could be clearer while staying concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description should explain what the agent can expect back and how this aggregated view differs from dedicated list tools. It names resource categories but omits return shape, status semantics, and any exclusions, leaving a zero-parameter tool under-specified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has zero parameters and 100% schema coverage, so there is nothing for the description to add. The baseline of 4 applies because no parameter semantics are needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states an action ('Gom' = gather/aggregate) over explicit resources: MONA Cloud VPS/databases and MONA Pay virtual accounts/webhooks. This makes the overall purpose reasonably clear and separates it from single-resource siblings, though 'Gom' is colloquial and the exact output is left implicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given for when to use this tool instead of the many relevant siblings such as cloud_services_list, monapay_list_virtual_accounts, or monapay_list_webhooks. The description implies an aggregate overview but never states the intended selection condition.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the transparency burden and does add some behavior: `sandbox=true` merges trial 0đ services and 'không cần header' signals an auth-header requirement. It does not mention read-only status, pagination, or any side effects, though listing is implicitly non-destructive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence states the action, resource, parameter mode, and header requirement without filler. Every clause earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a low-complexity listing tool with one optional parameter and no output schema, the description covers purpose, the sandbox modality, and the header requirement. It stops short of describing the response shape or pagination, but those are minor gaps for this simple call.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the only parameter (`sandbox`) already has a schema description stating 'thử 0đ, không cần ví'. The tool description repeats the sandbox behavior and adds the header note, but this is only marginal value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Liệt kê') and resource ('VPS/database'), so an agent can tell this is a listing operation. It is clear but does not explicitly differentiate itself from the similarly named sibling `cloud_services` or `cloud_subscription_list`.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives useful invocation context: `sandbox=true` includes 0đ trial services and no header is required. It does not, however, state when to prefer this tool over siblings like `cloud_services` or `cloud_subscription_list`, leaving alternative selection to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden and does a good job by warning that starting can incur costs, advising to check the wallet first, and clarifying sandbox=true costs 0đ with no wallet required. This addresses the most critical behavioral side effect, though it omits details like idempotency, failure behavior, or effects on an already-running service.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short, purposeful sentences. The core action and resource are front-loaded, followed by the cost warning and the sandbox clarification. No filler or redundant restatement beyond the minimal title overlap.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the essentials: what it starts, the cost risk, and the free-test path. However, with no output schema and no annotations, it omits what the tool returns (e.g., job ID, status), whether the service must already exist, and what the response/UI will say. This is adequate but not fully complete for an agent making autonomous calls.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 50% since service_id lacks a description, while sandbox has one. The description reinforces the sandbox semantics and hints that service_id refers to a MONA VPS/database, but does not explain the service_id format, where to obtain it, or how it is validated. This is partial compensation at best.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states action 'start' and target 'VPS/database MONA Cloud', which resolves the exact resource type and scope. It is visually and semantically distinct from sibling tools like cloud_service_stop, cloud_service_rebuild, and vibecloud_start.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides useful context about cost and sandbox mode, implying sandbox should be used for free testing. However, it does not explicitly state when to prefer this tool over alternatives like cloud_vps_create, cloud_services, or vibecloud_start, nor does it give conditions for normal vs sandbox use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It does add value by stating the action is always permitted and that stopping reduces costs, which hints at billing behavior. But it omits the risk profile: whether stopping is reversible via cloud_service_start, whether a stopped database loses data availability, or whether running workloads are affected.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single compact sentence with two clauses, both of which earn their place: the first carries the action and resource, the second adds policy/permission context. No filler or redundancy; the core information is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple 2-parameter tool with no output schema, the description covers the essentials: action, resource type, and policy. But it leaves gaps: no indication of what the call returns, no confirmation that a stopped service can be restarted, and no guidance on where service_id comes from. Adequate but not complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 50%: the sandbox parameter is well documented in the schema ('thử 0đ, không cần ví'), and service_id is reasonably self-evident from its name. However, the tool description adds no parameter information and does not explain how to obtain a valid service_id (e.g., from cloud_services_list), leaving the required parameter only minimally described.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Dừng' = stop) and a specific resource ('VPS/database MONA Cloud'), making the action unambiguous. The 'MONA Cloud' qualifier distinguishes it from the vibecloud_stop sibling, and the stop action separates it from start/rebuild siblings, though this differentiation is implicit rather than explicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The clause 'luôn cho phép dừng để người dùng hạn chế chi phí' provides a clear permission signal (always allowed) and a use-case context (cost reduction), which is genuinely useful guidance. However, it does not mention any exclusions, preconditions, or alternatives such as vibecloud_stop, so the guidance is implied rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full behavioral burden. It clearly signals a read operation via 'Đọc' and 'List', and it discloses the output scope (current plans, renewal period, auto-renew). However, it does not mention whether the list is scoped to the authenticated user, whether only active subscriptions are returned, or what the response format looks like.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Very short and front-loaded, with the Vietnamese phrase carrying more detail than the generic English 'List subscriptions.' There is minor redundancy between the tool name and the English summary, but nothing else is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple 0-parameter list tool with no output schema, the description covers the resource and the key returned aspects. Still, it leaves gaps around user scoping, whether only active subscriptions are listed, and the exact format of renewal-period and auto-renew fields.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters and the schema coverage is 100%, so there are no parameter semantics for the description to clarify. The 0-parameter baseline of 4 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a clear verb and resource ('List subscriptions') and the Vietnamese description adds the specific data exposed: current plans, renewal period, and auto-renew status. It does not explicitly distinguish itself from vibecloud_subscription_list or the plan/list siblings, but the purpose is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives such as cloud_plan_list, cloud_packages, or vibecloud_subscription_list. The only implicit cue is the verb 'List' versus update-oriented siblings, but no conditions or exclusions are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden, and it does disclose key behavioral traits: updates are mutating, upgrades are prorated, downgrades apply next cycle, and cancellation requires specific parameter values. It also implies an approval step. It is not exhaustive about side effects or return behavior, but it covers the most important operational semantics.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and avoids padding, but it mixes Vietnamese and English awkwardly, and the trailing '/ Update or cancel renewal' partly duplicates the Vietnamese content. The information is dense but the structure is somewhat run-on and not cleanly front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 5-parameter mutation tool with no annotations and no output schema, the description gives solid behavioral context but leaves gaps: service_id is not explained, the approval mechanism is vague, and there is no indication of what response the agent should expect. The core workflow is clear, but an agent would still need to infer some call details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It does clarify the meaning of auto_renew=false and cancel_action values, and it maps plan_code/period to changing plan/cycle. However, the required service_id parameter is not mentioned, and some fields like period are only implied. Partial compensation, not full.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear verb and resource: changing package/cycle/renewal or cancelling a subscription. The phrase 'Update or cancel renewal' reinforces the action, and the cancel path is spelled out. It does not explicitly name sibling tools, but the intent is not ambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives useful process context: read subscription and prices, estimate, then get approval. It also explains when upgrade vs downgrade takes effect and how to cancel via auto_renew=false with cancel_action. It does not explicitly mention when not to use this tool or point to alternatives, so it falls just short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the target and scope; it does not disclose whether an existing spend guard is overwritten, whether the operation is reversible, what permissions are needed, or what the response or error behavior looks like.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, compact sentence with no filler and the main action front-loaded. It is appropriately concise, though slightly too terse to carry the behavioral and parameter information an agent needs.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutating tool with no annotations and no output schema, the description is too sparse. It omits behavior on overwrite, the meaning of period, the interpretation of spend_limit_vnd, and any return or confirmation details. An agent would need to guess several important aspects before safely invoking the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It explains the role of token_id by mentioning 'token hiện tại hoặc token_id chỉ định', but it does not explain spend_limit_vnd or period, including the accepted day/month values. The most important parameters are left undocumented in the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb 'Đặt' (set) and identifies the resource as a spend guard scoped to either the current token or a specified token_id. This makes the tool's purpose clear and distinguishes it from broader budget tools like cloud_budget_set, though it does not explicitly name a sibling as an alternative.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool: to set a per-token spend guard for the current token or a specified token_id. However, it gives no explicit guidance about when not to use it, does not mention alternatives, and does not clarify prerequisites or the relationship to other budget/spend tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must carry the behavioral burden. It usefully discloses that this is not a final payment but a step that returns a VietQR for a human to pay, implying the wallet credit is not immediate. It does not disclose cancellation, expiry, idempotency behavior, or post-payment verification, but the human-payment trait is a meaningful disclosure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single compact sentence with no filler. The primary action is front-loaded, and the human-payment caveat is placed as a clarifying second clause, giving high information density.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description must explain what the agent receives and how to use the returned VietQR, but it only says 'returns VietQR'. It also omits the role of idempotency_key and any post-payment status flow, leaving the agent without enough to handle the full top-up workflow.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema descriptions cover only amount (integer VND) and leave idempotency_key undocumented. The tool description adds no parameter-level meaning, so an agent cannot infer why idempotency_key is needed or how the amount relates to the returned QR beyond what the schema already states.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('Tạo yêu cầu nạp ví') and its result ('trả VietQR'), making the tool's purpose clear. It also adds the key distinction that the QR is for a human to complete payment, which differentiates it from generic QR/checkout siblings, though it does not name any alternative explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool should be used when a wallet top-up requires a human payment step, which is useful context. However, it gives no explicit guidance on when to prefer this over monapay_create_qr, monapay_create_checkout, or other payment-related siblings, and no exclusions or prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full behavioral burden. It states the operation is a read ('Đọc'), but does not disclose output format, currency, tax inclusion, timezone handling, or pagination. It is minimally transparent but leaves significant behavior unspecified.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, compact sentence that conveys the core purpose and parameter semantics without redundancy. Every element earns its place and the main scope is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple two-parameter read tool with no output schema, the description covers the essential purpose and parameter meaning. However, it does not describe response contents beyond 'usage and total money', and offers no usage guidance or notes on output currency/format, leaving room for ambiguity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It maps 'theo tháng' to the period parameter and 'lọc sản phẩm' to the product parameter, which adds real semantic meaning. However, it does not explain period format, requiredness, or product value expectations beyond what the schema pattern already suggests.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('Đọc' = read) on a specific resource (MonA Cloud usage and total cost by month), with an optional product filter. This is clear and matches the title, though it does not explicitly differentiate it from cost-adjacent siblings like cloud_ledger or cloud_invoice_list.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus alternatives such as cloud_ledger, cloud_balance, or invoice tools. The description implies it is for monthly usage/cost lookups but provides no exclusions or comparison context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the transparency burden. It discloses important behavioral traits: estimating pricing first, asking for approval before creation, checking the wallet balance, returning estimate and job_id, and supporting a zero-cost sandbox mode. It does not cover failure behavior or how approval is requested, but the core side effects are visible.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded with the most important constraint: estimate and ask for approval before creating. It packs a lot of useful guidance into a short space, though the English summary '/ Estimate, approve, create VPS.' repeats the earlier workflow and the sandbox sentence largely duplicates the schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex tool with 9 parameters, no output schema, and no annotations, the description covers a lot: pricing source selection, monthly vs hourly behavior, wallet validation, job_id return, and sandbox. Still, it leaves required app_name undefined, does not clarify how billing_mode defaults, and does not explicitly separate this tool from vibecloud_create_vps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 11%, so the description must compensate. It does add meaning by explaining that monthly mode comes from plan_code and ignores CPU/RAM/disk, while hourly mode relates to cloud_prices/cloud_packages, and it clarifies period and sandbox behavior. However, app_name, billing_mode, and package_slug are not explained directly, leaving a real gap for a 9-parameter tool.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool creates a VPS and adds the concrete workflow 'Estimate, approve, create VPS', which is more specific than a generic create action. It does not explicitly differentiate from vibecloud_create_vps or other VPS creation siblings, but 'MONA Cloud' in the title and the cloud_* pricing references give indirect context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly instructs the agent to read cloud_plan_list for monthly or cloud_prices/cloud_packages for hourly, and explains when to use plan_code vs CPU/RAM/disk parameters. It also gives sandbox usage guidance and notes the wallet-check requirement, but it does not state an explicit exclusion like 'use vibecloud_create_vps for VibeCloud'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral burden. It conveys a read-only 'return' operation on the current profile, which is useful, but it does not mention authentication expectations, potential errors, or session-related caveats. It is adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two short clauses in Vietnamese and English with the core action and resource front-loaded. It contains no filler or redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter tool this is mostly complete, but with no output schema the returned 'profile' shape is unspecified, and the sibling landscape contains monapay_whoami and monapay_me with no disambiguation. A one-line note about which service this identity belongs to would close the gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are zero parameters, so there is nothing for the description to explain beyond confirming the call takes no arguments. The empty schema already fully covers this, so the baseline score of 4 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Return') and a clear resource ('current MONA Pass profile'), and the title reinforces the MONA Cloud scope. However, it does not explicitly distinguish this from sibling monapay_whoami, so it stops short of full sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The use case is implied: call it when the current MONA Pass identity/profile is needed. There is no explicit guidance about when to prefer this over similar identity tools such as monapay_whoami or monapay_me, which would be valuable given the large sibling list.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral burden. It does state that this is a read operation for account and quota, which implies no mutation. However, it does not disclose details like response structure, authentication needs, or any rate-limit behavior, though those may be less critical for a simple read tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loads the key instruction to use the tool first. It includes a useful API URL without excessive detail, though the Vietnamese and English sentences are partially redundant.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter read tool, the description provides enough context: when to use it, what it reads, and where the API endpoint lives. It does not describe the exact return payload, but 'account and quota' gives adequate operational meaning without an output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters and the schema is fully covered, so the description need not explain parameters. The baseline of 4 applies and the description appropriately omits irrelevant parameter details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool reads the account and quota, and explicitly says to use it first during email integration. The verb 'read' plus the resource 'account and quota' is specific, though it does not explicitly differentiate from sibling mail tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear usage context: 'Khi bắt đầu tích hợp email' (when starting email integration) and 'Use first'. It communicates when to invoke the tool but does not mention when not to use it or point to alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden and delivers: the key 'chỉ trả một lần' (returned only once) — the most safety-critical trait for a credential tool — plus storage guidance (write to .env as MONAMAIL_API_KEY) and a security instruction not to print the key in chat. This goes well beyond a bare 'create key' statement, though it omits details like whether old keys remain valid.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact — two short sentences — and front-loaded with the usage trigger. The bilingual portions carry distinct content (Vietnamese adds the .env and no-print-in-chat details; English summarizes the action), with only minor duplication and no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple 3-param, no-nested-object tool, it covers purpose, trigger, and the critical one-time-secret behavior. The main gap is response shape: with no output schema, the agent is only told the key is returned once, not what fields to expect, and error behavior is unmentioned.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 33% (just idempotency_key), so the description must compensate. It does map the `mode` parameter via 'tạo key live hoặc test,' but the required `name` parameter is undocumented in both the schema and the description — a genuine gap that the enum-only mode field only partially offsets.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action with a specific verb and resource: 'tạo key live hoặc test' / 'Use to create an app key.' The create action distinguishes it from sibling tools like mail_api_keys_list and mail_api_key_revoke, though those alternatives are never named explicitly, which keeps it a step below a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Khi tích hợp SDK vào app' ('When integrating SDK into app') provides an explicit trigger condition, and the live/test distinction clarifies the two modes this tool covers. It gives clear context for when to invoke it but does not state exclusions or point to alternatives for listing/revoking keys.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not state whether revocation is immediate or irreversible, what happens to integrations currently using the key, or how success is reported. For a destructive operation, this is a notable gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loaded with the purpose. The Vietnamese and English sentences are redundant with each other, but the duplication is compact and unlikely to confuse. It earns a high score, though a single-language version would be slightly tighter.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple one-parameter tool, the description gives the core trigger and target. However, with no output schema and no annotations, it misses behavioral details such as irreversibility, effect on active services, and confirmation/error behavior, leaving an agent with partial information.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It does mention key_id as the identifier used for revocation, but it does not explain where the key_id comes from (e.g., from mail_api_keys_list) or any format expectations beyond the schema's min/max length.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action (revoke) on a specific resource (API key), and adds the condition under which it applies (unused or compromised). This clearly differentiates it from sibling tools like mail_api_key_create and mail_api_keys_list.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives explicit when-to-use guidance: revoke when the key is unused or compromised. It does not explicitly name alternatives or exclusion criteria, but the context is strong enough for an agent to select this tool over related key management tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses two useful behavioral facts: only prefix and status are returned, and the secret is never returned. It does not mention pagination, errors, or auth, but for a zero-parameter inspection tool this is a minor gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and information-dense, with no filler. The Vietnamese sentence and English summary carry slightly overlapping meaning, which costs a small amount of structural efficiency, but both are useful and the overall size is appropriate.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter list with no output schema, the description explains what the tool does, what fields it reads, and what it deliberately does not return. There is no material missing context that would prevent an agent from invoking it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema is empty with zero parameters, so there is nothing for the description to document. The description still adds value by indicating what the returned data will contain (prefix/status, no secret), satisfying the baseline for a parameterless tool.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'inspect existing API key metadata.' It also adds a concrete scope by saying the tool reads prefix and status but not the secret, which clearly separates it from sibling create/revoke tools like mail_api_key_create and mail_api_key_revoke.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The first sentence gives a clear usage context: when checking an app's key, read its prefix and status. It does not explicitly name alternatives or state when not to use it, but 'existing API key metadata' plus the sibling names make the list-vs-create/revoke distinction obvious.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It usefully discloses that the tool returns DNS records and notes that the Cloudflare token is not stored, but it does not describe side effects, whether the domain registration is persistent, how long DNS propagation takes, or whether verification is required afterward.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded with the core purpose, but it repeats the same information in Vietnamese and English ('Trả record DNS' / 'get DNS records'). Bilingual duplication adds length without adding new semantic content, so it is not as tightly written as it could be.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and no annotations, the description should explain what the DNS records look like, what the agent should do with them, and whether a verification step is needed. It provides the key output type (DNS records) and the Cloudflare alternative, but omits follow-up verification context and any mention of retry/idempotency behavior, leaving moderate gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 50%: idempotency_key is documented in the schema, but domain has no schema description. The description adds some meaning by clarifying that domain refers to a sender domain for the app, but it does not specify format rules, whether it must be a root domain or subdomain, or how the idempotency_key interacts with the registration process.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool registers a sender domain and returns DNS records, using a specific verb and resource ('register a sender domain', 'get DNS records'). It also distinguishes itself from the Cloudflare sibling tool by naming mail_domain_cloudflare, so an agent can tell the purpose apart.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives an explicit when-to-use context ('when sending by the app's domain') and names an alternative: call mail_domain_cloudflare if the user uses Cloudflare. However, it does not explicitly mention when to prefer mail_domain_verify or exclude other non-Cloudflare cases, so the guidance is strong but not fully exhaustive.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full behavioral burden. It does well by disclosing that the token is single-use, not stored, and not logged, and that the tool modifies DNS and performs verification. It stops short of describing failure modes or DNS propagation behavior, but these are secondary to the main security-relevant disclosure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact, front-loaded with the triggering condition and main effect, and contains no filler. The bilingual phrasing is justified for mixed-language users, and the security note is integrated without bloating the entry.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the core action and token-security behavior, but omits important context such as prerequisites (e.g., whether the domain must already exist, whether a Cloudflare zone is required), expected return/status information, and error behavior. Since there is no output schema and no annotations, these gaps matter for reliable agent invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds meaning beyond the schema by identifying api_token as a user-provided Cloudflare token that is used once and never logged, and by implying that domain_id is the target domain. However, schema coverage is only 33%, and the description does not clarify where domain_id comes from or how it relates to the mail-domain lifecycle, so compensation is only partial.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action: when a user provides a Cloudflare token, add DNS records and verify the domain. It clearly distinguishes this from sibling tools like mail_domain_add and mail_domain_verify by making Cloudflare automation the central resource and process.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'Khi người dùng cung cấp token Cloudflare' explicitly names the triggering condition: use this when the user supplies a Cloudflare token. It does not name sibling alternatives or state when not to use them, but the context is clear enough for an agent to recognize the intended usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must carry behavioral disclosure. 'Xem/view' signals a read-only listing and it indicates the returned data (domain and verification status), but it does not clarify whether unverified domains are also returned, nor does it mention pagination or auth expectations. Adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and to the point, with no wasted words. The Vietnamese and English sentences largely restate the same idea, which is minor redundancy, but the overall structure is efficient and readable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-input list tool, the description covers the essential context: when to use it and what it returns (domains and verification status). Since there is no output schema, the description adequately names the return content. Missing deeper details like response format are not critical here.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has zero parameters and full schema description coverage, so the baseline of 4 applies. The description adds relevant context about what the tool scans, even though there is nothing parameter-specific to document.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb-resource pair: 'find verified sender domains' and viewing domain plus verification status. It is clearly a lookup operation, and the list intent is unambiguous even though it does not explicitly contrast with the sibling mail_domain_add/verify/cloudflare tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives a concrete usage context: when choosing a sending address, use this to check domains and their verification status. It does not explicitly name alternatives or exclusions, but for a simple zero-parameter list tool, this is clear enough guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses that the tool checks DKIM and domain status, but it does not state whether verification is read-only or triggers an action, nor mention side effects or propagation timing. Basic behavior is clear, but the safety profile is incomplete.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short bilingual sentences with no filler; the most important usage condition ('after adding DNS records') is front-loaded and the rest is directly relevant.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a low-complexity tool with one required parameter and no output schema, the description covers the key workflow context and enough semantics to invoke it. A minor gap is the lack of guidance about possible pending states or propagation delays after DNS changes.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 50% and domain_id has no description in the schema. The description identifies the domain as the object being verified, which maps to domain_id, but it does not explain how to obtain it, and it adds nothing about idempotency_key beyond the schema's own description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'verify the sender domain' after DNS records are added, and names concrete checks ('DKIM and domain status'). This clearly distinguishes it from siblings like mail_domain_add and mail_domains_list, which cover adding and listing domains.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives explicit contextual timing: 'Use after adding DNS records to verify the sender domain' / 'Khi đã thêm DNS'. This tells an agent when in the domain-setup workflow to invoke it, though it does not explicitly name alternatives or state when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It conveys a read/search intent but says nothing about result format, pagination, default limits, ordering, or which statuses are included (e.g., queued vs. sandbox). The content largely restates purpose rather than revealing behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two compact sentences with the usage context front-loaded. The bilingual repetition (Vietnamese and English saying the same thing) is a minor redundancy, but there is no filler or irrelevant detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given zero schema descriptions, no annotations, and no output schema, this description leaves important gaps: what the response looks like, the role of the limit parameter, and how results relate to mail_status/mail_stats. It is adequate for recognizing the tool's purpose but not for confidently invoking it with full expectations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It maps three parameters to filter concepts ('trạng thái, người nhận hoặc thời gian' = status, recipient, time), which adds mild meaning. However, it ignores the limit parameter entirely and adds little beyond what the self-explanatory parameter names already suggest.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific action and resource: 'search sent email history', plus the filter dimensions (status, recipient, time). This is enough to distinguish it as a history-listing tool, though it never explicitly differentiates from mail_status or mail_stats among siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Khi tra lịch sử gửi' ('when checking send history') provides an implicit usage context. However, there are no exclusions or alternative tool references — an agent cannot determine when to pick mail_list over mail_status (single-message status) or mail_stats (aggregate statistics) without opening other definitions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the behavioral burden. It indicates a read/compare action via 'đọc' and 'compare', implying non-mutating behavior, but it does not describe output format, whether all plans are returned, or any other side effects. This is adequate but minimal.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loads the triggering condition and the core action. The Vietnamese and English sentences are near-duplicates, adding minor redundancy, but there is no filler beyond the bilingual restatement.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter lookup tool, the description covers enough: it names the object (email plans), the data of interest (price and quota), and the action (compare/read). It lacks an output schema, but the simplicity of the operation makes the description reasonably complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters and an empty input schema with 100% schema coverage, so there are no parameter semantics for the description to add. Per the zero-parameter baseline, this is not a deficiency.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a clear verb and resource: compare/read current email plans, including price and quota. It is distinct from mail_plan_set and other mail tools, though it does not explicitly name an alternative, so it stops short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Khi chọn gói gửi mail' gives an explicit condition: use this when choosing a mail-sending plan to read current pricing and quota. It provides clear context, but it does not state exclusions or sibling alternatives such as mail_plan_set for changing a plan.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the behavioral burden. It discloses an important side effect – paid plans deduct from the VND wallet and insufficient balance should trigger cloud_topup. However, it does not say whether the change is immediate, whether existing mailboxes/data are affected, or whether downgrades are possible.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loaded: it gives the condition, the action, and the billing fallback in two compact clauses. The trailing English sentence mostly repeats the title, which is slightly redundant but not harmful.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter tool, it covers the trigger, the action, and the payment fallback, which is useful. However, with no annotations and no output schema, it leaves unstated what the agent should expect after the call succeeds – immediate confirmation, asynchronous job status, or any prerequisites beyond wallet balance.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description needed to explain the plan parameter meaning, but it only says 'chọn gói' generically. It does not map the enum values (free, khoi-nghiep, kinh-doanh, doanh-nghiep) or clarify which plans are paid versus free beyond a general mention of 'gói trả phí'.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('change') and resource ('email plan' / 'đổi quota'), and ties it to MONA Mail. It is clear enough to know this is a plan-change operation, though it does not explicitly contrast with sibling tools like mail_plans.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives an explicit trigger: 'Khi cần đổi quota, chọn gói' – when a quota change is needed, select a plan. It also covers a fallback path by directing the agent to call cloud_topup if wallet funds are insufficient, though it does not mention when to prefer mail_plans for inspecting plans.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so the description carries the full behavioral burden. It discloses verified-domain requirements, sandbox side effects, and the onboarding address limitation. However, it does not mention real-send costs/quota, idempotency behavior, template versus subject requirements, or how suppression lists affect delivery.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short and front-loads the most critical constraint: verified domain usage. The bilingual repetition is somewhat redundant but serves a mixed-language audience, and there is no filler or excessive detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 12 parameters, no annotations, and no output schema, a two-sentence description is insufficient. It omits the subject/template selection rule, retry semantics, quota/cost behavior for real sends, and what a successful response means. An agent would need to inspect the schema and infer significant behavior before invoking this side-effecting tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 25%, and the tool description adds useful meaning for sandbox behavior and the from-address requirement. It does not compensate for the many undocumented parameters such as template_id, variables, reply_to, tags, idempotency_key, and unsubscribe_url, leaving important invocation details to inference.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action: sending transactional email, and it mentions concrete use cases: OTP or notifications and sandbox testing. It does not explicitly contrast itself with sibling tools like mail_template_create or mail_suppressions_list, but the send/test framing is distinct enough.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear usage context: use a verified domain, sandbox for zero-charge tests without Internet delivery, and a special restriction on the onboarding@monamail.vn address. It does not name sibling alternatives or state when not to use this tool, so it falls short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It implies a read-only action ('đọc'/'review') and names the metrics involved (delivered, bounce), but it does not disclose output shape, aggregation granularity, data latency, or whether both metrics are always returned. For an unannotated tool this is thin coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loads the evaluation context, but the Vietnamese and English halves are largely redundant restatements of the same idea. A single merged sentence would convey the same information, so not every clause earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a low-complexity tool (two optional date params, no output schema, no annotations), the description is minimally adequate: it states the purpose and the key metrics. But an agent still lacks clarity on what the response contains and how from/to shape the query, and with no output schema to fall back on, those gaps matter.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. The phrase 'theo thời gian' (over time) loosely hints that the from/to date parameters define a time window, but it never maps from→start and to→end, never mentions optionality, and gives no format guidance beyond the schema regexes. This is marginal compensation for a 0%-coverage schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a concrete activity — reviewing email delivery statistics, specifically delivered and bounce rates over time. This distinguishes it from send/provisioning tools like mail_send or mail_domain_add. However, it does not differentiate itself from close siblings such as mail_status or monapay_email_stats, and the weak verb 'review/đọc' leaves the exact operation somewhat open.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The Vietnamese clause 'Khi đánh giá khả năng giao thư' supplies a scenario-based trigger ('when evaluating mail delivery capability'), which is a legitimate usage signal. But it gives no exclusions and never points to alternatives, leaving an agent uncertain whether to pick this over mail_status, mail_list, or monapay_email_stats.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full transparency burden. It does signal a non-mutating inspection through 'đọc/read/inspect' and discloses the elements inspected (status, events, sandbox_preview). However, it does not explain what sandbox_preview contains, any polling or waiting semantics after sending, or what happens for an invalid or missing email_id.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short clauses, front-loaded with the trigger condition and closing with the plain-English purpose. The bilingual duplication is mild redundancy, but nothing is wasted and the key scoping detail ('after sending') is prominent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter read tool, the description covers the basics — what to inspect and when. Yet with no output schema and no annotations, an agent is left guessing at the shape of the returned status/events objects, the semantics of sandbox_preview, and the provenance of email_id. Adequate but not self-sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the schema itself provides no meaning for email_id. The description compensates only partially: it implies the ID identifies a just-sent email, but it never states where the ID originates (e.g., from mail_send's response) or gives any format guidance beyond the schema's raw length constraints.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action — inspecting/reading an email's status, events, and sandbox_preview after sending — rather than merely restating the name or title. It differentiates itself from email-family siblings (mail_send, mail_list, mail_stats) by context, though it never names the alternatives explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The Vietnamese opening supplies an explicit trigger condition ('when needing to confirm the email was delivered'), and the English clause adds sequencing context ('after sending'). No exclusions or named alternatives, but the when-condition is concrete enough for an agent to route to this tool over mail_send or mail_list.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden. It discloses the operation's scope (account-level only) and a practical precondition, but does not mention whether removal is idempotent, what happens if the email is not suppressed, required permissions, or the response format. Moderate transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two compact sentences conveying condition, action, and limitation, with the key English summary up front. The Vietnamese and English phrases partly repeat, creating slight redundancy, but nothing is wasted overall.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter, no-output-schema tool, the description covers what the tool does and when to use it, but leaves open questions about error behavior, idempotency, and the exact input mapping. Adequate for selection and basic invocation, with clear gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description needed to explain the email parameter's role, but it never mentions 'email' or maps 'tài khoản' (account) to the email identifier. The parameter is simple and named, but the description adds no semantic value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('remove') and resource ('account-level suppression'), with a clear scope limitation that system-wide suppressions cannot be removed via this tool. This differentiates it from listing tools like mail_suppressions_list and from any broader suppression-removal operation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit precondition: use only after the blocking cause has been handled ('Khi đã xử lý nguyên nhân chặn'). It also states an exclusion: system-wide suppressions are not removable. It does not name a specific alternative tool, so it stops short of a full when/when-not/alternatives statement.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does add that the operation is a read/view returning addresses plus reasons, which is meaningful, but it says nothing about output shape, scope (mail vs monapay), ordering, or pagination. For a tool with zero annotation coverage, this is thin.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences in Vietnamese and English, with the scenario front-loaded before the action. Every word earns its place and there is no filler; the only minor inefficiency is the bilingual duplication being partially redundant.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given there is no output schema and no annotations, the description should clarify what the response looks like and any scope constraints; it reveals only that addresses and reasons are returned. For a simple zero-parameter list tool it is close to adequate, but it omits sibling differentiation and any hint of output structure that an agent would need without an output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema declares zero parameters with trivially complete coverage, so per the rubric the baseline for 0 params is 4. There is nothing about parameters for the description to add, and the schema needs no compensation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action and resource: "xem địa chỉ và lý do ngừng gửi" (view addresses and the reason for suppression), and the English gloss 'diagnose suppressed recipients' reinforces the read/list nature. It is distinguishable from the sibling mail_suppression_remove by direction (view vs remove), though it does not explicitly name that sibling or the cross-domain monapay_list_email_suppressions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The English sentence 'Use to diagnose suppressed recipients' gives a clear trigger condition for when to call the tool, which is more than just implied usage. However, it provides no exclusions and names no alternatives — an agent gets no guidance on when to prefer this over monapay_list_email_suppressions or when to pair it with mail_suppression_remove.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full disclosure burden. It usefully discloses the {{ten_bien}} variable-substitution convention, but it doesn't state what happens on success or error, whether template names must be unique, overwrite behavior, or the response format — a bare 'create' with no consequences leaves an agent guessing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences, roughly 20 words, with the when-condition front-loaded. But the bilingual halves are partially redundant (both convey 'create reusable template'), and the English 'Use to create...' is grammatically awkward, which slightly undermines clarity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 5-parameter, 3-required creation tool with no annotations and no output schema, this is underspecified. An agent still cannot tell what name/subject/text should contain, whether text is optional despite existing, or what a successful creation returns — the description must carry more weight given how little structured context exists.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.