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

With no annotations, the description carries the full burden. It adds a useful behavioral detail about GoDaddy apex domains being rejected before API creation and suggests a workaround. However, it does not discuss other side effects, failure modes, or whether this is a mutating 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 concise and front-loaded with the purpose. The GoDaddy caveat is useful but slightly extends length; overall it is efficient without fluff.

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 provides key workflow context and a notable edge case, but given the tool's complexity (6 params, no annotations), it omits guidance on several parameters and does not mention the output schema or post-add behavior. It is adequate but leaves 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 only adds meaning for two of six parameters ('provider_name' and 'dns_zone'), leaving 'project_id', 'domain', 'mode', and 'app_id' unexplained. This is insufficient for a 6-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 states a specific action ('Add a custom domain') and a temporal context ('after provider detection'), making the purpose clear. However, it does not differentiate from the sibling tool 'attach_custom_domain', which may overlap in function.

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 clearly indicates when to use this tool ('after provider detection') and specifies required inputs ('confirmed provider_name and authoritative dns_zone'). It lacks explicit alternatives/exclusions, but the context is helpful.

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 burden. It indicates a read-only analysis ('show how...'), but does not explicitly state that no changes are made, nor does it disclose any prerequisites like valid project_id or YAML parsing behavior. It is not misleading, but lacks explicit behavioral detail.

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 sentence that is concise, front-loaded with the verb, and contains no redundancy. Every word contributes to the meaning.

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 analysis tool with an output schema, the description covers the core purpose and the three specific output categories. It does not explain return values (covered by output schema) but lacks usage guidance and parameter format details. Overall, it is reasonably complete for its complexity.

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 partially compensates. It implicitly maps compose_yaml to a docker-compose.yml, but does not specify the expected format (raw YAML string, file path, etc.) and project_id is entirely unexplained. The lack of parameter descriptions in the schema and minimal elaboration in the description leave significant ambiguity.

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 'analyze' and identifies the resource 'docker-compose.yml', clearly stating the output: 'show how PlugLayer will split it into marketplace databases, separate compose services, and local-build services.' This distinguishes it from siblings like deploy_compose (which deploys) and get_compose_local_build_commands (which returns commands).

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 action is clear but there is no explicit guidance on when to use this tool versus alternatives. It implies a planning/preview use case, but doesn't mention exclusions or mention that it should be used before deploy_compose. Context is clear enough to infer usage, but no explicit alternatives 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 transparency burden. It discloses that this is an import operation, may restart the app, does not return values, and expects content rather than paths. This is strong, though it doesn't mention merge/replace behavior or permissions.

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 only three sentences, front-loaded with the core purpose, and every sentence adds value. There is no fluff or repetition of schema defaults.

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 7 parameters, no annotations, and a sparse schema. The description covers the essential import formats and critical warning about return values, but omits behavioral details for merge and restart modes. This makes it minimally viable but not comprehensive.

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 0% and there are 7 parameters. The description clarifies input_format by listing dotenv/KEY=VALUE, JSON, YAML, and direct object, and env_content by stressing content over paths. However, merge, restart_mode, and redeploy_strategy are not explained, leaving significant gaps.

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 ('Import'), identifies the resource ('runtime env vars into an existing app'), and enumerates the accepted input formats. This clearly distinguishes it from siblings like get_app_connection_env_vars or sync_database_env_to_app, which have different objectives.

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 guidance: pass file content, never a path, and notes that values are not returned, implying it shouldn't be used when output is needed. However, it doesn't name alternatives or explicitly state when to prefer another tool.

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 burden of disclosing side effects. It mentions the make_primary=true effect (becoming the app's main URL), which is useful. However, it does not disclose whether the operation is reversible, whether it replaces an existing primary domain, or any permission requirements. The mutation nature is implicit from 'attach', but deeper behavioral context is missing.

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, front-loaded with the primary action. Every word earns its place, and the description is efficient and clear.

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 the tool's simplicity and the presence of an output schema, the description covers the essential usage and the primary flag behavior. It could mention what happens to the existing primary domain when make_primary=true, but the description is largely complete for an experienced user.

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, so the description must compensate. It explains the make_primary parameter's effect ('become the app's main URL'), but does not elaborate on app_id or domain_id. These are self-explanatory from their names, but the description adds no additional meaning 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 clearly states the action with a specific verb and resource: 'Attach a verified custom domain to an app.' It also distinguishes from sibling tools like add_custom_domain, verify_custom_domain, and detach_custom_domain by emphasizing the 'attach' action and the 'verified' prerequisite.

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: use this tool to attach a domain that is already verified to an app, with an optional make_primary flag. It implies that unverified domains should be verified first (via another tool), but it does not explicitly name alternatives or state when not to use this tool.

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 burden and discloses two key behavioral traits: owner-only permission and idempotency. It also implies the node must be 'available dedicated,' adding meaningful context. It does not cover failure modes or return specifics, but the disclosed traits are valuable.

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 concise, front-loaded sentences. The first sentence states the core action and constraints, the second gives a critical next step. 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 simple two-parameter attach operation, the description covers purpose, constraints, and a necessary follow-up. Given that an output schema exists, not detailing return values is acceptable. A minor gap in explicit parameter semantics prevents a perfect score.

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 0%, so the description must compensate. It does not explicitly define node_id or project_id, but the phrase 'one available dedicated node' implies node_id must reference such a node, and the follow-up call reinforces project_id's role. This adds some semantic meaning beyond the bare parameter 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 states the tool attaches one available dedicated node to a project, using a specific verb and resource. It naturally distinguishes itself from sibling tools like detach_node_from_project and list_attachable_project_nodes.

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 clear usage context: owner-only restriction and an explicit follow-up action (call get_compute_summary before deploying). It does not explicitly mention alternatives or when not to use, but the guidance is sufficient for correct invocation.

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. The verb 'Check' clearly implies a read-only, non-destructive operation, and 'before provisioning or renaming' signals it is a pre-validation step. It does not describe return format, but an output schema is present, so this is acceptable.

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, focused sentence that immediately states the purpose and context. No filler or redundancy; every word 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?

The description is brief but adequate for the core use case. However, it omits the important use case of excluding a database ID (relevant when renaming) and does not explain behavior when the slug is unavailable. Given the output schema, this is not critical, but the missing parameter context makes it 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 description coverage is 0%, so the description must compensate, but it only hints at 'slug' and 'project' without explicitly mapping to parameters. The optional parameter 'exclude_database_id' is not mentioned at all, leaving a significant gap for agents to understand its purpose.

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 the verb ('Check'), the resource ('database/Data Layer slug'), and the scope ('in a project'), making it distinct from the sibling tool 'check_slug_availability' which appears generic. The phrase 'before provisioning or renaming a database' adds clear intent.

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 explicit usage context: 'before provisioning or renaming a database.' This tells the agent when to use this tool, but it does not name alternative tools or explicitly state when not to use it, 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 must convey behavioral traits. The verb 'check' implies a read-only operation, and the phrase 'inside a project' clarifies scope. However, it does not explicitly state that the tool is side-effect-free or describe what happens when the slug is unavailable, leaving some ambiguity in 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 a single, front-loaded sentence that directly states the purpose and context. Every word contributes value, with no filler or redundancy.

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 the simplicity of the tool and the presence of an output schema, the description conveys the core purpose effectively. However, the under-explained exclude_app_id parameter and the lack of explicit guidance about the sibling database-specific tool leave gaps in completeness for an agent selecting and invoking the tool 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%, so the description must compensate. It mentions 'slug' and 'project,' mapping conceptually to the slug and project_id parameters, but it fails to explain the exclude_app_id parameter entirely. Without explanation, the agent cannot know when to set exclude_app_id (e.g., for rename scenarios), making parameter usage incomplete.

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's function: 'Check whether a PlugLayer slug is available inside a project before deploying or renaming an app/database.' It uses a specific verb ('check') and resource ('slug availability'), and distinguishes itself from the sibling check_database_slug_availability by covering both app and database contexts.

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 a clear usage context: 'before deploying or renaming an app/database.' This implies when to use the tool, though it does not explicitly mention alternatives or exclusions. Since there is a sibling tool for database-specific checks, the description could have differentiated further, but the context is sufficient for most cases.

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 discloses a significant behavioral trait: the tool automatically resolves DB names and secret-like fields, including random password generation, before sending a deploy request. This is useful, but it doesn't mention permissions, async behavior, reversibility, or error conditions, so it remains 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 two sentences, front-loaded with the main purpose, and contains no filler. Every word adds value, clearly stating what the tool does and a key behavioral nuance.

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?

Despite having an output schema, the description is too sparse for a tool with 11 parameters. It does not explain how the template_id and app_name relate, what optional fields do, or how this tool connects to other database-related tools (e.g., list_database_templates). The overall context is underspecified for the tool's complexity.

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 description coverage is 0%, and the description does not compensate. It vaguely refers to 'DB names and secret-like template fields' but does not map these to any of the 11 parameters. It fails to explain the meaning of template_id, app_name, cpu_limit, storage_gb, etc., leaving the agent without crucial parameter 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 clearly identifies the action ('Provision a database') and the resource ('from a ready marketplace template'), distinguishing it from generic deployment tools. It also highlights unique behavior (resolving DB names and generating random passwords) that separates it from siblings like deploy_marketplace_template.

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 provisioning a database from an existing marketplace template. It also hints at prerequisites ('ready marketplace template') and what the tool handles internally. However, it does not explicitly mention alternatives or when not to use it, 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 full burden for behavioral disclosure. It discloses the auth requirement and the compute prerequisite for deployment, but does not explain what happens on duplicate names, idempotency, or what the response contains. These gaps prevent a higher score.

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 sentences with no filler. The first sentence states the core action, and the second adds a relevant caveat about deployment compute, earning 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?

An output schema exists, and the description covers the key contextual point: creation is auth-only while deployment requires compute. This is nearly complete for a simple create tool, though the absence of any parameter documentation slightly 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 0%, and the description provides no information about the 'name', 'description', or 'domain_type' parameters. The agent receives no guidance on parameter meaning, defaults, or valid values beyond the raw schema, which is inadequate.

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 the specific verb 'Create' and clearly identifies the resource as a 'PlugLayer project namespace,' which distinguishes it from sibling tools like list_projects, get_project, rename_project, and delete_project. The action 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?

The description offers clear context by stating that project creation only requires authentication and that deployment still requires account-level compute, with a pointer to check get_compute_summary before deploying. This implies when to use the tool (before deployment) and highlights a prerequisite, though it does not explicitly contrast with other project-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, and the description discloses no behavioral traits. It does not mention that deleting an app is destructive, irreversible, or requires permissions. The description is a single sentence with no behavioral detail.

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 extremely short, but this is under-specification rather than efficient conciseness. It provides minimal value and lacks necessary details about the tool's 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?

With only one parameter and an output schema, the description still needed to explain the purpose, side effects, and usage context. Instead, it merely references another tool, leaving the agent without essential information 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?

The schema has 0% description coverage for the app_id parameter, and the description does not mention the parameter at all. The agent gets no explanation of what app_id is or how to use it, leaving the parameter completely underspecified.

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 it is an alias for remove_app(), implying the same functionality (deleting an app). However, it does not directly state what the tool does; it relies on the reader knowing remove_app. This is clearer than a pure tautology but still vague.

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 no explicit guidance on when to use this tool versus alternatives. It merely notes it is an alias for remove_app() with 'app wording', which implies interchangeability but does not specify preferred contexts 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?

With no annotations, the description carries the full burden of behavioral disclosure. It fails to mention that the tool deletes a database, any destructive side effects, permission requirements, or reversibility. The word 'delete' does not even appear in the description.

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 extremely short, but it is under-specified rather than concise. The single sentence merely notes the alias and provides no functional explanation, so it does not earn 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?

Given the lack of annotations and minimal description, this is completely inadequate. It does not explain the tool's purpose, behavior, or side effects, and relies entirely on the reader knowing what remove_database() does. The presence of an output schema doesn't compensate for the missing context.

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 one parameter 'database_id' with 0% description coverage. The description adds no meaning to this parameter, such as its format, purpose, or relation to the remove_database function it aliases.

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 only states 'Alias for remove_database()', which references another tool without explaining what the tool does. It does not specify the verb+resource or distinguish it from siblings beyond the alias relationship, making it essentially a tautological reference.

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 provided on when to use this tool versus alternatives such as remove_database or delete_project. The alias statement gives no context about preferred use cases or exclusion criteria.

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 burden. It only states that it is an alias for remove_app(), without disclosing that the operation is destructive, any side effects, authentication requirements, or the exact nature of the deletion. The agent cannot infer the behavioral profile from this description alone.

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 sentence with no wasted words. It front-loads the alias relationship and usage context, earning every word.

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 alias with an output schema, the description conveys the core fact (alias) and usage context, but it omits behavioral details and parameter semantics, instead relying on the agent knowing remove_app(). This is minimally viable but has clear gaps for safe and 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% and the description does not mention deployment_id or its relationship to remove_app()'s parameters. The parameter name is self-explanatory, but for an alias it is ambiguous whether deployment_id is an app ID or a deployment-specific ID, so the description adds little semantic value.

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 this is an alias for remove_app(), which implies deletion of a deployment, and distinguishes it as a compatibility wrapper for legacy terminology. It doesn't explicitly say 'deletes a deployment' but the tool name and alias make purpose clear.

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 context for when to use: 'for clients still using deployment wording.' It implies that remove_app() is the canonical tool and this is for legacy compatibility, though it doesn't explicitly mention alternatives or exclusions.

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 does not mention that this action deletes a project, whether it is destructive or irreversible, or any required permissions or side effects.

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 extremely short, but it is under-specified rather than appropriately concise. It does not provide enough information to be useful, so the brevity is a defect, not a strength.

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 deletion tool with one parameter and an output schema, a complete description could be one sentence. This description omits the core semantics entirely, leaving the agent dependent on the sibling tool 'remove_project' for meaning.

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 lists 'project_id' as a required string without description, and the description adds zero meaning to the parameter. Since schema description coverage is 0%, the description should compensate but does not.

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 only states 'Alias for remove_project()', which does not actually say what the tool does. It requires the agent to infer behavior from the tool's name and the sibling tool 'remove_project', making the purpose indirect and vague.

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 provided about when to use this tool versus alternatives. The alias relationship implicitly suggests using it interchangeably with remove_project, but no explicit context, conditions, or exclusions are given.

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 provides good transparency: it explains the multi-step process, mentions the Data Layer for databases, and specifies the local build behavior with local_image_archives. It doesn't cover idempotency or permissions, but the key side effects and conditional behavior are disclosed.

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 sentences with every clause serving a purpose: the first sentence encloses the entire workflow, and the second adds a conditional instruction. No fluff or redundancy exists.

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 offers a good high-level overview and the local build nuance, but for a complex tool with 7 parameters, no annotations, and many sibling tools, it lacks context about prerequisites, idempotency, and relationship to planning/analyzing tools. The presence of an output schema mitigates return-value explanations but not these 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%, and the description only elaborates on local_image_archives and indirectly compose_yaml. Parameters like project_id, app_name, route_slug, compute_placement, and redeploy_strategy are not explained beyond their schema titles, leaving a significant gap for a tool with 7 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 clearly states the tool's function: analyze docker-compose.yml, split into deploy units, provision databases, and deploy the remaining services as apps. This distinguishes it from sibling tools like deploy_image which handles single images, making the purpose 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?

The description implies use for docker-compose files by mentioning 'docker-compose.yml' and the deployment flow, but it does not explicitly mention alternatives or when not to use this tool. Sibling tools like analyze_compose_deploy_plan are not referenced, so guidance is only implied.

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 of disclosing behavior. It discloses a key non-obvious trait: the image is mirrored into a verified private managed repository, and there is no bypass. This is valuable context beyond the schema. However, it does not elaborate on side effects (e.g., creating a new deployment versus updating an existing app) or potential failure conditions, so it is not fully 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 two sentences, front-loaded with the core action, and includes a clear alternative reference. Every sentence earns its place with no redundancy or fluff, making it highly concise and well-structured.

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 the tool's complexity (14 params, no schema descriptions, no annotations), the description is too sparse to be fully contextual. It explains the conceptual model but does not cover parameter roles, required inputs beyond 'image', or runtime behavior expectations. While an output schema exists, the description alone leaves the agent with significant ambiguity about how to invoke the tool 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 does not compensate. It only hints that 'image' must be pullable, but gives no explanation of the other 13 parameters (e.g., 'name', 'ports', 'env_vars', 'registry_id'). This is a significant gap for a tool with 14 parameters, leaving the agent without enough param-level meaning.

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: 'Deploy a pullable Docker image' and explains the process (mirroring into a verified private managed repository). It distinguishes this from sibling tools by explicitly noting there is no public/direct-image bypass and naming an alternative for local-only images, which clarifies its scope.

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 explicit when-to-use and when-not-to-use guidance: it is for pullable Docker images, not local-only images, and explicitly directs users to 'upload_image_archive_and_deploy()' for the local-only case. This directly addresses alternatives and exclusions, making it highly actionable.

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 a key behavior (auto-resolving secret-like env vars) and the dual project-create/use scenario, adding value beyond the schema. However, it omits many other behavioral aspects such as whether the call is synchronous, error handling, or the effect of setting conflicting parameters like project_id and project_name.

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 exactly two sentences that convey the core purpose and a key behavioral nuance. Every word contributes value; there is no fluff or repetition.

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 the tool's complexity (11 parameters, no annotations), the description is too sparse. It does not explain when certain parameters are required, how project_id and project_name interact, or what the output schema will contain. While an output schema exists, the overall context for a multi-option deployment flow is left largely undefined.

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 fails to do so. It indirectly references env_overrides ('Secret-like required env vars') and project selection, but it does not explain the meaning, usage, or relationships of the 11 parameters. Only minimal context is provided, leaving the agent reliant on parameter titles alone.

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 ('Deploy') and resource ('marketplace template'), and further specifies the deployment context ('existing project or a brand-new project created during the same flow'). This clearly distinguishes it from sibling tools like deploy_image or deploy_compose, which target different deployment resources.

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 by stating it can target an existing or new project, and highlights a distinguishing feature: auto-resolution of secret-like env vars. However, it does not explicitly mention alternatives or exclusions, 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 burden. It discloses one key behavioral trait ('keeping verification') but omits other important details such as side effects, whether the operation is reversible, or any required prerequisites. More context is needed for a mutation-like 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 a single, front-loaded sentence that concisely states the action and a key nuance. 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 simple one-parameter tool, the description is minimally adequate, but it lacks context on return values, error cases, or what happens to the domain's verification state in practice. The presence of an output schema may offload some return-value documentation, but the description still leaves room for more 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 0%, so the description must compensate. It does not explain what 'domain_id' refers to or how to obtain it. The single parameter is named clearly in the schema but the description adds no additional semantic meaning beyond the obvious.

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 'Detach' with a clear resource 'a custom domain from its app', and adds a distinguishing behavioral detail 'while keeping verification'. This clearly differentiates it from siblings like attach_custom_domain and verify_custom_domain.

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 detaching a domain but retaining verification) but does not explicitly state alternatives or exclusions. It does not mention other sibling tools that might be relevant (e.g., remove or update domain operations).

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 active apps block the operation and that user confirmation is required via the confirm flag. This adds meaningful operational context beyond the schema, though it does not cover reversibility or permissions.

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 concise sentences with the action front-loaded and no extraneous words. The critical caveats (blocking and confirmation) are included efficiently.

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 is sufficient for a moderate-complexity detach operation: it states the action, a key blocking condition, and the confirmation requirement. The output schema likely documents the return value. It omits rare edge cases but is reasonably complete for typical usage.

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 confirm parameter ('only after the user explicitly confirms this change'), but project_id and node_id are only self-explanatory from their names. The confirm semantics are valuable, but the other parameters lack explanation.

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 ('Detach') and the resource ('a dedicated node from a project'), making it distinct from sibling tools like attach_node_to_project. No ambiguity in what the tool does.

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 practical usage guidance with the blocking condition ('Active apps block detachment') and an explicit confirm flag instruction ('Set confirm=true only after the user explicitly confirms this change'). However, it does not explicitly name alternative tools or when to prefer them, 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 must carry the burden. It discloses the data source ('public NS records'), which implies a read-only operation, and notes the result is 'likely', indicating probabilistic behavior. Yet it fails to mention potential errors, rate limits, or exact output structure. Some transparency is present but not exhaustive.

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 sentence, front-loaded with the verb and resource, followed by context. No unnecessary words. It efficiently conveys both what the tool does and why it should be used.

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 a provided output schema, the description covers the main use case and context. It explains the purpose (detection) and the intended workflow (confirm before showing steps). It doesn't detail failure handling or return values, but the output schema likely covers that. Adequate overall.

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?

With 0% schema description coverage, the description must compensate. It mentions 'custom domain' which gives a hint about the domain parameter's expected type (an apex domain, not a subdomain). However, it doesn't specify required format, whether schemes are allowed, or other constraints. Minimal added meaning beyond the parameter name.

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's function: detecting the DNS/domain provider for a custom domain using public NS records. The verb 'Detect' and specific resource make intent obvious. It doesn't explicitly distinguish from sibling tools like verify_custom_domain, but the action is conceptually 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 context on when to use the tool: before showing tailored DNS steps, and it advises confirming results with the user. However, it doesn't explicitly mention when not to use it or name alternatives among the many domain-related sibling tools. 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?

No annotations are provided, so the description must carry the burden. It discloses the return value (offer link) and instructs the agent to present it as a confirmation step. However, it does not mention side effects, whether the operation is read-only, or if it creates a quote/reservation. This is a moderate gap for a tool that leads to purchase actions.

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 sentences, front-loaded with the core purpose, and each sentence meaningfully contributes. It avoids redundancy and communicates the tool's role and required agent behavior efficiently.

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 conveys the tool's purpose and output but omits parameter usage entirely and lacks behavioral details like side effects or prerequisites. Although an output schema exists, the input side is severely underdescribed; agents would not know what workload information to collect or how to populate the four parameters, making the description incomplete 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% and the description does not mention any of the four parameters. The phrase 'described workload' implicitly points to the use_case parameter but does not name it or clarify how to fill components, expected_requests_per_minute, or expected_monthly_active_users. Agents receive no guidance on what values to provide, making effective invocation unlikely.

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 'estimate' with a specific resource ('compute needed for a described workload') and a concrete output ('tailored PlugLayer offer link'). It distinguishes itself from sibling compute tools by positioning itself as the 'preferred first step' before purchasing/reserving compute, which is a clear 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?

Explicitly states when to use this tool: 'preferred first step before telling the user to purchase, reserve, or add more compute.' It also gives a clear instruction on the next action ('present the returned link as the user's next confirmation step'), providing both when-to-use and post-invocation 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 provided, the description carries the full burden of behavioral disclosure. It covers the core behavior (executes command, returns result), the fixed 360-second timeout, input limits (10,000 chars, ~350 lines), and the scope restriction to the caller's pod. Missing details like error handling or exit-code behavior, but the provided context is solid for a command execution 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 consists of three concise sentences, each adding distinct value: the main purpose, the timeout, and input/scope constraints. It is front-loaded with the verb+resource, and no words are wasted. The structure is ideal for quick parseability.

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 only two parameters and an output schema present, the description covers the essential behavioral and constraint information. It explains what the tool does, its limits, and its scope. It does not elaborate on working directory, shell type, or environment variables, but those are not critical for basic usage and may be implied or handled elsewhere. Overall, it is sufficiently complete for a command execution 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 implies that app_id identifies the app container and command is the shell command, but it does not explicitly map these schemas to their meanings. While it adds some semantic value beyond the bare schema titles, it lacks clear parameter-level elaboration, such as the format or allowed command syntax.

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 primary action: 'Run a shell command inside the user's own deployed app container and return the result.' It specifies the resource (the app container) and distinguishes this from sibling tools like get_app_logs or restart_app by focusing on command execution. The scope is further clarified with 'limited to the caller's app pod only.'

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 on when to use this tool: to run shell commands in the user's app container. It also gives practical guidelines via constraints (360-second timeout, input size limits), implying this is for short, bounded commands. However, it does not explicitly mention alternatives or contraindicate use for long-running tasks, 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 exist, so the description must convey behavioral traits. It states the generated workflow's purpose but does not clarify that the tool itself only generates YAML (doesn't execute it), nor mention side effects or authentication needs.

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 contains the core action and context with no redundant 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?

Given the 4-parameter schema with 0% coverage and no annotations, the description leaves significant gaps about required inputs and precise usage. The output schema exists but is not referenced, and sibling tools are not differentiated in terms of fit.

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 descriptions are entirely absent (0% coverage), and the description does not explain any of the four parameters. Parameter names like app_id and project_id offer minimal hints, but repo and repo_path remain ambiguous.

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 generates a GitHub Actions workflow YAML with specific build/upload behavior, distinguishing it from direct deployment tools like deploy_image or upload_image_archive_and_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?

No when-to-use or alternative guidance is provided. The description does not explain when to choose this over sibling deployment tools, nor any exclusions.

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 correctly implies a read-only operation via 'Get,' and adds the constraint that it should be used after provisioning. However, it does not explicitly state side-effect-free behavior, whether the values are sensitive, or any prerequisites beyond provisioning. For a retrieval tool with an output schema, this 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 sentences with no redundancy. The first sentence states the function, the second provides usage guidance. Every word earns its place, and it is appropriately sized for the tool's complexity.

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 the simple one-parameter tool with an output schema, the description covers purpose, usage context, and the nature of the result (URLs/connection strings). It doesn't mention error handling or edge cases, but for a straightforward getter, it is sufficiently complete. The description also helps differentiate it from other env-related tools in the sibling list.

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 one parameter 'app_id' with no description (0% coverage). The description does not directly explain the parameter, but the tool name and description make it obvious that app_id refers to the app whose env vars are fetched. For a single self-explanatory string parameter, this is minimally sufficient, especially since the description says 'for an app'.

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: 'Get env vars and connection fields for an app.' This is a specific verb+resource combination that distinguishes it from related tools like get_database_connection_details (database-specific) or apply_app_env_vars (modifying env vars). The mention of 'connection fields' adds specificity beyond just 'get env vars.'

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 explicit context: 'Use this after provisioning so you can update dependent apps with the right URLs or connection strings.' This clearly indicates when to use it (after provisioning) and why, without naming alternative tools. It lacks explicit exclusions or mention of alternatives, but the context is clear enough for an agent to choose it appropriately.

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, and the description carries no behavioral details. It does not disclose return format, pagination, side effects, authentication needs, rate limits, or any constraints. The phrase 'using app terminology' is too vague to inform 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?

While the description is short and readable, it is under-specified. One sentence that merely references another tool does not earn its place for a tool description; it lacks defining information. This is over-conciseness, not efficiency.

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 the presence of an output schema but zero annotations and zero parameter descriptions, the description is woefully incomplete. It fails to explain the tool's purpose, when to use it, parameter behavior, or return semantics. The description relies entirely on external knowledge of get_logs.

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 with no parameter descriptions, and the description adds no meaning to `app_id` or `lines`. It does not explain that `app_id` is the app identifier or that `lines` controls the number of log lines. The description's 'app terminology' hint is insufficient to disambiguate 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 says 'Alias for get_logs() using app terminology.' This does not directly state what the tool does (e.g., 'retrieve application logs'); it only references another tool. For an agent, the action is unclear without prior knowledge of get_logs. This is close to a tautology, though it hints at app-specific logs.

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 versus alternatives like get_logs or get_database_logs. The word 'alias' implies it is interchangeable with get_logs, but it does not explain when one should be preferred over the other. No context, prerequisites, or exclusions are given.

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 burden of indicating safety. The verb 'List' implies a read-only operation, which is helpful. However, it provides no other behavioral traits (e.g., whether it requires specific permissions, how it handles missing projects, or what fields are returned). Since it's a simple list operation, a score of 3 is appropriate—minimally transparent 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 three sentences, with the core purpose in the first sentence and additional guidance in the following sentences. Every sentence adds value; there is no redundancy or filler. It is front-loaded and easy 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?

Given that an output schema exists (has output schema: true) and the tool has a single straightforward parameter, the description covers the essential aspects: what it does, when to use it, and decision-making guidance. The only gaps are the lack of explicit alternative tool names and minor behavioral details, but for a list operation with an output schema, this is mostly 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 description coverage is 0%, and the description does not elaborate on project_id beyond the phrase 'for a specific project,' which merely restates the parameter name. It fails to clarify the expected format (e.g., UUID, slug) or any constraints. For a single required parameter, the schema alone might be sufficient, but the rubric explicitly requires compensation when coverage is low, and the description does not provide 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 opens with 'List apps for a specific project,' providing a specific verb and resource scope. This clearly distinguishes it from sibling tools like list_projects (which lists projects) and list_deployments (which lists deployments). The additional context about using it before a deploy reinforces its unique purpose.

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: 'Use this before a new deploy when the project may already contain the same app.' It also provides a when-not scenario by advising 'prefer update or replace flow instead of a brand-new app' when a similar app exists and namespace is full. However, it does not name specific alternative tools, so it stops short of a full alternative reference.

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 must carry full behavioral disclosure. The description states it 'return[s] exact commands,' implying it does not execute them, which is a useful behavioral hint. However, it does not explicitly state whether the tool is read-only, whether it modifies the compose file or any resources, or if it requires any special permissions. This leaves meaningful gaps in safety 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?

The description is a single, well-structured sentence that front-loads the core action ('Analyze') and the key output ('return exact commands'). Every word contributes meaning, with no redundant or filler content. It is appropriately concise and easy 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?

Given that an output schema is present (as indicated by 'Has output schema: true'), the description does not need to explain return values. It provides the main purpose, the input (compose_yaml), and the usage context ('before upload to PlugLayer'). However, it lacks elaboration on prerequisites (e.g., Docker installed, project access) or the meaning of 'local-build services,' leaving a minor gap for full 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 0%, so the description must compensate by explaining parameter meanings. It does not mention any of the four parameters (project_id, compose_yaml, workspace_root, image_tag_prefix) beyond the generic reference to 'a docker-compose.yml.' The description adds no value for understanding these parameters, leaving the agent without guidance on how to populate them correctly.

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's function: it analyzes a docker-compose.yml and returns exact buildx, smoke-test, and OCI-export commands for local-build services. This specific verb+resource+scope distinguishes it from sibling tools like deploy_compose or analyze_compose_deploy_plan, which focus on deployment planning rather than command generation.

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 'before they are uploaded to PlugLayer' provides important usage context, indicating this is a pre-upload preparation step. However, it does not explicitly state when to avoid using this tool or mention alternatives such as deploy_compose or analyze_compose_deploy_plan, so it lacks explicit exclusions or alternative 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 burden. 'Show' implies read-only, and the explanation of project-scoped behavior adds transparency. It does not mention permissions or potential side effects, but none are expected for a read 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?

Two tightly written sentences, front-loaded with purpose and parameter behavior, followed by usage guidance. No wasted words, every sentence 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?

The tool has an output schema, so return values are covered. The description sufficiently explains the tool's scope, the optional parameter's effect, and when to recommend an alternative. It is complete for the tool's complexity.

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 has zero description coverage, but the description fully explains the project_id parameter: passing it yields a project-scoped view with node attachments and per-node usage. This adds concrete meaning 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 clearly states the tool shows accessible compute, with a specific scoping behavior when project_id is provided. It differentiates from sibling tools like estimate_compute by describing the project-scoped view including nodes and per-node usage.

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?

Explicitly instructs to prefer estimate_compute() when the user is planning capacity, and to use get_compute_summary otherwise. This provides clear when-to-use vs alternative 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 burden of indicating behavior. The verb "Show" implies a read-only operation, and "from Authentik" adds source context, but it does not explicitly state that there are no side effects, nor does it mention authentication requirements or what happens if not authenticated. For a simple getter, this is adequate but not fully 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 a single, front-loaded sentence: "Show the authenticated PlugLayer user and roles from Authentik." Every word earns its place; there is no redundant or vague wording.

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-only tool with an output schema, the description provides sufficient information about what the tool returns. It is concise and clear, but it could improve by mentioning how it differs from `get_user_context` or by explicitly noting the read-only nature. However, given the simplicity, it is largely 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, so the baseline for this dimension is 4. The description appropriately adds no parameter information because there are none, and the schema already confirms this with an empty properties object.

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 "Show" and specifies the resource "authenticated PlugLayer user and roles from Authentik", which clearly states what the tool does. It adds detail about roles, but does not explicitly differentiate from the sibling tool `get_user_context`, 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?

No guidance is provided on when to use this tool versus alternatives such as `get_user_context`. The description simply states what it shows without mentioning any conditions, prerequisites, or exclusions, leaving the agent to infer 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 the burden of disclosing behavior. It describes what is returned (connection strings, env vars, docs) but does not explicitly state that it is a read-only operation, mention access prerequisites, or explain potential side effects. This is adequate for a getter but not fully 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 a single sentence, concise and front-loaded. Every word contributes meaning; no filler or redundancy.

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 with an output schema, the description adequately covers what the tool does and why it might be used. The output schema handles return value details, so no further elaboration is necessary.

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 does not elaborate on the database_id parameter beyond referring to 'a provisioned database.' It does not explain the ID format, how to obtain it, or what constitutes a valid input, leaving the agent with only the parameter name to infer meaning.

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 ('Get') and resource ('a provisioned database's connection strings, env vars, and docs'), clearly distinguishing it from sibling tools like get_database_logs or get_app_connection_env_vars. The scope is precise and actionable.

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 clear context ('so you can wire other apps automatically') indicating when this tool is useful. It does not explicitly name alternatives or exclusions, but the intent is sufficiently 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 must disclose behavioral traits. It only says 'Get', implying a read operation, but does not mention permissions, output size, pagination, or any side effects. This lacks transparency beyond the obvious read-only nature.

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 concise sentence with no filler or repetition. It communicates the essential purpose efficiently.

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 output schema exists, so return values are covered. However, the description lacks context about what 'recent' means, how many lines are returned, or how the database_id parameter should be obtained. It is minimally adequate for a simple read tool but leaves gaps in usage context.

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?

Input schema has two parameters (database_id, lines) with zero description coverage. The description does not explain either parameter, failing to compensate for the schema's lack of detail. The word 'database' hints at database_id but does not clarify the 'lines' parameter or its default behavior.

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's function: retrieving logs from a database. It uses a specific verb ('Get'), a resource ('logs'), and a qualifier ('from a provisioned database') that distinguishes it from sibling tools like get_app_logs or get_logs.

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 no guidance on when to use this tool versus alternatives. It does not mention prerequisites, exclusions, or contrast with get_app_logs or get_logs, leaving the agent without decision-making information.

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. The verb 'Get' implies a read-only operation, which is helpful, but the description does not disclose any potential side effects, permission requirements, or what happens with an invalid deployment_id. It is adequate for a simple read operation but lacks explicit safety context.

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 redundancy. It conveys the essential function ('Get current app/deployment status and public URL') and nothing more, making it highly efficient.

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 get-status tool with an output schema (which likely documents return values), the description is sufficient. It could be improved by explicitly connecting the deployment_id to the status query, but the tool's low complexity and the presence of an output schema mean the description does not need to explain much more.

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 the description does not explain the deployment_id parameter's format or origin. However, the parameter name is self-explanatory, and the description's mention of 'app/deployment status' implies that the ID refers to a deployment. The baseline is low because coverage is 0%, but the single parameter is simple enough that the lack of additional explanation is not a major gap.

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 the specific verb 'Get' and identifies the resource as 'current app/deployment status and public URL', which clearly distinguishes it from sibling tools like list_deployments (which lists all deployments) and get_task_status (which tracks async tasks). 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?

There is no guidance on when to use this tool versus its alternatives. It does not say 'use this after deploying to check if the app is live' or 'use list_deployments to see all deployments'. The description lacks any contextual direction, leaving the agent to infer appropriate usage from the name.

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 operation by referencing 'existing project domains', but it does not explicitly state safety, side effects, or error behavior. Calling it an alias delegates behavior to list_project_domains without additional 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 two concise sentences. The first sentence establishes the alias, and the second provides actionable usage guidance. Every word earns its place, with no redundant or filler content.

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 alias function with an output schema present, the description adequately covers purpose and usage. It does not address error cases or prerequisites beyond the schema, but the provided context is sufficient for a get/list operation, and the output schema covers return values.

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 one required parameter (project_id) with no description (0% schema coverage). The description does not explain what project_id is or how it should be used, leaving the agent to infer meaning from the parameter name alone. This fails to compensate for the low schema coverage.

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 that this is an alias for list_project_domains(), identifying the action (list/get) and resource (project domains). It distinguishes itself from the sibling tool list_project_domains by explicitly noting the project-first wording, making the purpose 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?

The description provides explicit when-to-use guidance: 'Use this before asking the user which domain they want so existing project domains can be offered as options.' It also names the underlying function (list_project_domains) as the canonical alternative, giving clear context for tool selection.

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 burden. It adds the ownership constraint (authenticated user), but does not disclose behavior for missing IDs, response format, or error cases. For a simple read operation this is average but not comprehensive.

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 sentence with no filler. It is front-loaded with the action and resource, making it immediately clear what the tool does.

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?

An output schema exists and the tool is simple (one param, no nested objects). The description covers the core purpose and ownership scope. It lacks explicit usage alternatives but is otherwise complete given the low complexity.

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 does not explain feedback_id beyond the schema's title. The parameter is self-explanatory from name, but the description adds no semantics such as format, source, or constraints, so it fails to compensate for the lack of schema documentation.

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 and resource: "Get one feedback ticket owned by the authenticated PlugLayer user." It clearly distinguishes from siblings like list_my_feedback (which lists all) by focusing on a single ticket and adding the ownership scope.

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 usage context: use this when you have a specific feedback_id to retrieve one ticket. It does not explicitly exclude alternatives or mention list_my_feedback, but the single-ticket focus makes the intended use 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?

No annotations are provided, so the description must carry the burden of disclosing behavioral traits. It only states 'Get recent logs' without revealing whether the operation is read-only, any rate limits, the meaning of 'recent', or output specifics. This is insufficient for safe invocation.

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 brief and front-loaded, but it is under-specified. It is not wasteful, yet it omits essential usage and parameter context. While efficient, it misses opportunities to add value without being lengthy.

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 the lack of annotations and 0% parameter description coverage, the tool description should provide richer context. It does not mention the required deployment_id, the purpose of the lines limit, or how this differs from sibling log tools. An output schema exists, so return format is covered, but invocation semantics remain 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 description coverage is 0%, and the description adds no explanation of the parameters. The phrase 'from an app' hints at deployment_id but doesn't explain the lines parameter or their roles. The description fails to compensate for the schema's lack of parameter descriptions.

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 ('Get') and resource ('recent logs from an app'). It is a specific, understandable statement. However, it does not distinguish this tool from sibling get_app_logs, which likely serves a nearly identical purpose, so it lacks 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 description provides no guidance on when to use this tool versus alternatives like get_app_logs or get_database_logs. There is no mention of preferred contexts, exclusions, or trade-offs, leaving the selection decision entirely to the agent without further clues.

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 adds useful behavioral context by noting that the template includes env var requirements, aiding in resolving secrets and choosing project flow. However, it doesn't disclose potential errors, permissions, or confirm read-only behavior beyond the verb 'Get'.

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 just two sentences, both of which provide essential information—what the tool does and when to use it. No fluff or redundancy.

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 get operation with an output schema, the description is mostly complete. It states the purpose, the key output detail (env var requirements), and the usage context. It doesn't mention error behavior, but the output schema likely covers return structure. The main gap is no explicit parameter semantics, though the parameter name mitigates that.

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 does not directly explain the parameter format. However, the parameter name 'template_id_or_slug' is self-explanatory, and the description's mention of 'one marketplace template' implies the parameter identifies which template. The description adds minimal 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?

The description clearly states the verb 'Get' and the resource 'one marketplace template', which distinguishes it from the sibling tools for listing all templates or deploying them. However, it does not explicitly mention the alternative tools by name, only implying the singular nature.

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 explicit 'when to use' guidance: 'Use this before template deployment'. This is clear context, though it doesn't mention when not to use or name alternative 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 only states the output is end-user friendly and implies capacity might be ambiguous, but it does not disclose whether the operation is read-only, potential rate limits, or what 'available compute' means. This is insufficient for full 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?

The description is two sentences: the first clearly states the tool's purpose, the second adds a key usage guideline. Every sentence earns its place, with no fluff or redundancy.

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 tool with an output schema, the description provides a clear purpose and a fallback action. It could elaborate on what 'end-user friendly format' entails, but the output schema likely covers return values, making the description sufficiently 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 with an empty schema, making schema description coverage 100%. As per the rubric, 0 params earns a baseline of 4, and there is no need for parameter explanation.

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 ('show') and a specific resource ('current user's available compute') in an end-user friendly format, making the purpose clear. However, it does not explicitly distinguish itself from the sibling tool 'get_my_available_computes' or other compute-related tools, so it lacks 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?

It gives explicit guidance to call estimate_compute() when capacity is unclear, providing a clear alternative and condition. However, it does not offer broader selection guidance for other compute-related siblings, so it's not a full when/when-not guide.

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 must disclose behavioral traits. However, it only states it is an alias and provides usage advice; it does not describe what the tool returns, whether it is read-only, or any side effects. This leaves significant ambiguity for the agent.

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 consists of two concise sentences: the first identifies the tool as an alias, and the second provides key usage guidance. There is no redundant information, and it is appropriately front-loaded with the alias relationship.

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 offers some contextual guidance (when to use estimate_compute first) but does not explain what 'available computes' are or how this tool relates to other compute-related siblings. Since an output schema exists, return value details are not required, but the tool's overall purpose and placement are only partially covered.

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. According to the guidelines, a baseline of 4 is appropriate when there are no parameters because the description need not explain parameter details. The description adds no parameter information, but none is 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 clearly states it is an alias for get_my_available_compute(), which specifies the action (get) and resource (available computes). It also distinguishes itself from estimate_compute by mentioning when that tool should come first. While it relies on familiarity with the singular form, the alias reference and tool name make the purpose discernible.

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 says that estimate_compute() should usually come first when the user has not sized their workload yet, providing a clear usage guideline relative to a sibling tool. It does not mention other alternatives like get_shared_compute_pricing or get_compute_summary, but the given guidance is specific and actionable.

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 of disclosing behavior. It states the tool is an alias, implying it behaves identically to list_projects(), which suggests a read-only listing operation. However, it does not provide details on outputs, pagination, or potential side effects, leaving room for ambiguity.

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 that efficiently communicates the tool's identity as an alias. It contains no unnecessary words and is appropriately concise for such a simple 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?

Given the tool's simplicity (zero parameters, output schema present), the description is adequate. It confirms the tool is an alias for list_projects(), which suggests it returns project data. The lack of a return value explanation is mitigated by the presence 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 tool has zero parameters, and the input schema already reflects this with an empty properties object. The description adds nothing about parameters because there are none to explain, so the 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 clearly identifies this as an alias for list_projects(), making the action (listing projects) apparent through the reference to a known sibling tool. It distinguishes itself by noting it uses end-user wording, but does not directly state 'lists projects' as its own verb+resource.

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 explicit guidance is given on when to use this tool versus the alternative list_projects(). The phrase 'using end-user wording' vaguely implies a user-facing context, but there is no clear directive or exclusion criteria to help the agent choose between the two.

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 is the only source of behavioral disclosure. It adds the constraint that the project must belong to the 'authenticated user', which is useful context. However, it does not explain error handling, permission requirements, or what exactly 'details' includes, leaving 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?

The description is a single, front-loaded sentence that delivers the core purpose without wordiness. Every word earns its place, and it is structured clearly with the verb and object first.

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 the tool's low complexity (1 parameter) and the presence of an output schema, the description is minimally viable. It covers the basic purpose and ownership constraint, but lacks usage guidance and parameter semantics. It is complete enough for a trivial get-by-ID operation, but not exemplary.

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 for the lack of parameter documentation. The description does not explicitly mention project_id, its format, or how it relates to the user's projects beyond the general phrase 'for one of the authenticated user's projects'. The parameter name is self-explanatory, but the description adds no meaningful semantic value beyond what the schema's property name already provides.

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's function: 'Get project details' for a specific project belonging to the authenticated user. This distinguishes it from sibling tools like list_projects or get_my_projects, which imply listing multiple projects rather than retrieving a single one by ID.

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 usage when you have a project_id and need its details, but it does not explicitly mention alternatives or conditions for use. No exclusions are stated, so the guidance is minimal but not misleading.

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 explicitly states the operation is read-only, which is a key behavioral trait, and further clarifies that purchasing is out of scope. This adds meaningful context beyond simply naming the tool's function.

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 exactly two sentences, with the core purpose front-loaded and no extraneous content. The second sentence adds valuable behavioral and follow-up guidance, making every word earn 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 zero-parameter read-only tool with an output schema, the description fully covers what the tool does, what information it returns (pricing and unreserved pool), and what it does not do (purchase). This is complete and actionable for an AI 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, so the schema covers everything (vacuously 100%). The description does not need to explain parameters, and the baseline for zero-parameter tools is 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 clearly states the tool 'Show[s] the admin-defined unit pricing for shared compute reservations plus the currently unreserved shared pool.' It uses a specific verb and resource, and distinguishes from purchase-related actions by directing users to the web app for buying.

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 says 'Read-only' and instructs to 'direct the user to the PlugLayer web app' for purchasing, providing clear when-not-to-use guidance. It does not explicitly name alternative sibling 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?

Since no annotations are provided, the description carries the disclosure burden. It mentions the types of output (status, progress, result URL, error) but does not address read-only nature, polling behavior, side effects, or authentication requirements. For a simple status checker, 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 a single concise sentence that is front-loaded with the action and object. Every word adds value with no filler or repetition.

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 one simple parameter and an output schema, the description is fairly complete. It covers the main return elements (status, progress, result URL, error). It does not mention how to obtain task_id or any integration context, but this is not critical for such a straightforward 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?

There is only one parameter, task_id, which is self-explanatory given the description. Schema description coverage is 0%, so the description must add meaning; it implies task_id is the identifier for the async operation but adds no format, type, or lifecycle context beyond the name.

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 'Check' and the resource 'async operation status', and expands on what is returned (status, progress, result URL, or error). It is specific enough to know what the tool does, though it does not explicitly distinguish it from sibling status tools like get_deployment_status or get_logs.

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. No mention of prerequisites, exclusions, or typical scenarios for checking async operation status.

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 transparency burden. 'Load' implies a read operation, but it does not disclose behavior such as what happens when no stored context exists, whether a default is returned, or any side effects. This is a minimal but not misleading 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 two sentences, with the action front-loaded ('Load the caller's stored PlugLayer user context memory') and a concise secondary sentence providing usage context. Every sentence earns its place 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 simple zero-parameter getter with an output schema (though not shown), the description sufficiently covers purpose and usage context. It does not need to explain return values because an output schema is present, making it 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 the schema is empty with 100% coverage. The description adds no parameter semantics, but none are needed; the baseline of 4 for zero-parameter tools 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 uses a specific verb ('Load') and identifies the resource ('stored PlugLayer user context memory'), clearly distinguishing it from siblings like get_current_user and update_user_context. It also hints at the resource's purpose, making the tool's function 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?

The description gives explicit usage context: 'Use this at the start of a session when prior project/app/domain preferences may matter.' It does not explicitly mention when not to use it or name alternatives, but the guidance is clear and actionable.

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 must carry the burden of behavioral disclosure. It implies a read-only check by using 'Check', and lists the exact conditions verified. However, it does not explicitly state that the tool makes no modifications, nor does it describe behavior when the repo does not exist or lacks a git origin.

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 that conveys all necessary information without redundancy. Every word contributes value.

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 single-parameter tool, the description is fairly complete. An output schema exists, so return values don't need to be described. Minor gaps include lack of edge-case behavior (e.g., nonexistent path) and usage timing, but overall it is sufficient for an agent to understand the tool's core function.

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 for the sole parameter `repo_path`. The description does not mention this parameter at all, leaving its semantics to be inferred from its name and default value. This fails to compensate for the lack of schema documentation.

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's function with a specific verb ('Check') and resource ('local repo'), and enumerates three specific criteria (exists, git initialized, GitHub origin). This distinguishes it from sibling tools, which are all cloud/deployment focused.

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 versus alternatives, no prerequisites, and no exclusion cases. It is implied that this is a preflight check, but that is never stated explicitly.

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 the output categories (available, attached here, attached elsewhere) and implies authentication via 'authenticated project owner.' However, it does not explicitly state that the operation is read-only or mention any side effects, though 'List' strongly implies read-only 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 two sentences, each earning its place. The first sentence explains what the tool does, and the second provides usage context. No filler or repetition.

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 with an output schema, the description is complete: it states the purpose, the exact output categories, and when to use it. The output schema covers return details, so the description does not need to explain them.

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 one parameter (project_id) with 0% description coverage. The description implies that project_id identifies the project being checked, but it does not explicitly define the parameter or its format. Since the parameter name is self-explanatory and the context is clear, the description partially compensates but not fully.

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 lists the authenticated project owner's dedicated nodes and their attachment status (available, attached here, attached elsewhere). It distinguishes itself from sibling tools like list_nodes by focusing on project-specific attachable nodes and their statuses.

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 says 'Use this when project compute is missing before a deploy,' which provides clear when-to-use context. It does not mention when not to use it or name alternatives, so it lacks exclusions or alternative 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 provided, the description must carry the behavioral disclosure burden. It only states the action without mentioning read-only nature, side effects, or required auth, leaving the agent to infer safety.

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 concise sentences with front-loaded purpose and a clear usage directive. Every word 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?

The tool is simple with no parameters and an output schema, so the description covers purpose and usage sufficiently. Lacks a read-only hint, but this is a minor gap given the obvious list nature.

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 no parameters, making schema coverage trivially 100%. The baseline for 0 parameters is 4, and no additional parameter explanation is 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 the function clearly as 'List database-ready marketplace templates', using a specific verb and resource. It distinguishes itself from sibling tools like list_marketplace_templates through the 'database-ready' qualifier and the explicit provisioning 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?

Provides explicit guidance: 'Use this first when the user asks to provision a database through PlugLayer', which tells the agent when to invoke it. However, it doesn't name alternatives or give when-not conditions, so it falls short of a perfect 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 disclosing behavior. It provides no details about access requirements, rate limits, pagination, response scope, or any operational caveats.

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 only two sentences, but it is under-specified and misleading. Brevity is not conciseness when it fails to convey the essential purpose and 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?

Despite having an output schema, the description is incomplete: it does not clarify the deployment/app distinction, and provides no differentiation from many sibling tools. This leaves the agent unable to confidently select the correct 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 description adds that project_id is an optional filter, which is not stated in the schema (which only provides type and default). This provides basic meaning, though it does not explain format or edge cases.

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 says 'List apps' but the tool is named list_deployments, which is misleading. It does not mention deployments at all, and sibling tools like get_apps_by_project suggest apps and deployments are different resources. This misidentification directly conflicts with the tool's name.

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 offers no guidance on when to use this tool versus alternatives. It only mentions an optional filter, with no reference to sibling tools or exclusions.

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 burden. It accurately states the tool lists templates, implying a read-only operation, but does not disclose details like filtering behavior, pagination, or potential side effects. 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 only two sentences, front-loaded with the core action, and every word adds value. It is concise and directly supports tool selection.

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 primary use case and output schema exists, so return values are handled. However, with four optional parameters and no explanation of their semantics, especially test_state, the description leaves a clear gap for an agent needing to filter results.

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 0%, and the description provides no explanation of the parameters (search, category, test_state, featured_only). The agent cannot infer the meaning of test_state or how filtering works from the description, so it fails to compensate for the schema gap.

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 and resource: "List deployable marketplace templates." It clearly distinguishes this tool from siblings like list_database_templates and get_marketplace_template by focusing on deployable templates and connecting to the deploy workflow.

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 usage context: "Use this before deploying a ready-made template through PlugLayer." This tells the agent when to invoke it, though it does not mention alternatives 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?

With no annotations, the description carries the full burden of behavioral disclosure. It adds the useful trait that feedback is filtered to the authenticated user's own submissions, but it does not mention whether the operation is read-only, how the limit parameter affects results, or any other behavior. This is minimal but not completely silent.

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 concise sentence that front-loads the action and resource. Every word earns its place, with no redundancy 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?

The tool is simple and has an output schema, so return values are covered. However, the description is incomplete regarding the 'limit' parameter's behavior and does not discuss pagination or ordering. It is adequate for a basic list operation but leaves some 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 has one parameter (limit) with 0% description coverage, and the tool description does not mention it at all. Although the name 'limit' is self-explanatory, the description adds no elaboration or confirmation of its effect, missing the opportunity to compensate for the schema gap.

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 ('List') and resource ('feedback') with an explicit scope ('submitted by the authenticated PlugLayer user'). This distinguishes it from siblings like submit_feedback and get_feedback, which have different purposes.

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 that this tool lists feedback submitted by the current user, which implies when to use it. However, it does not explicitly mention alternatives or offer exclusion criteria, so it falls short of the 'explicit when/when-not' standard.

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 adds useful context about authentication scope and the dedicated/shared node relationship, but it does not disclose return format, pagination, ordering, or any other behavioral traits. For a read-only list tool, this 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 sentences, front-loaded with the main purpose, and every word adds value. It efficiently covers the core function and the key parameter behavior without redundancy.

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 is simple (one optional parameter) and an output schema exists, so return values need no explanation. The description covers the essential behavior, authentication scope, and parameter semantics. It could mention pagination or sorting, but for this scope the description is largely 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 input schema provides only the parameter name, type, and default, with 0% schema description coverage. The description fully compensates by explaining that passing project_id lists only nodes backing that project and clarifies the dedicated vs shared node distinction, which the schema lacks entirely.

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's action ('List compute nodes') and scope ('accessible to the authenticated user'), using a specific verb and resource. It also distinguishes behavior by describing project_id filtering and the dedicated vs shared node distinction, which helps separate it from sibling tools like list_attachable_project_nodes.

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 for when to pass project_id (to filter to a project's nodes) but does not explicitly mention when to use this tool over alternatives such as list_attachable_project_nodes or list_my_available_compute. Usage is implied rather than explicitly contrasted.

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 clarifies that the tool lists purchasable options (implying a read-only operation), but omits details about authentication, side effects, or filtering behavior. The absence of annotations raises the need for more context, yet the description is not contradictory or 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 two sentences, front-loaded with the action verb 'List', and every word earns its place. It efficiently communicates the core purpose and the recommended usage context without redundancy.

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 listing tool with an output schema, the description provides adequate context: what it lists and when to use it relative to estimate_compute. It doesn't explain filtering semantics or prerequisites, but the optional parameters are fairly self-evident and the output schema covers return structure. Slightly more detail on what 'compute options' entails would elevate it.

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 adds no parameter context. While parameter names like min_cpu_cores and min_ram_gb are self-explanatory, 'tags' and 'tshirt_size' remain vague and lack examples or format guidance. The description does not compensate for the schema's lack of parameter documentation.

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 lists PlugLayer marketplace compute options that can be purchased. It also distinguishes itself from estimate_compute by contrasting real purchasable machines with abstract resource units, making its purpose specific and 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?

It explicitly says to use this tool after estimate_compute() when real purchasable machine choices are needed instead of abstract resource units. This provides clear timing and relationship to an alternative, though it doesn't mention other siblings like get_my_available_compute.

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