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

The description discloses the state-changing behavior ('Marks the suggestion as accepted and links it to an existing budget') and adds the prerequisite/ownership constraint. However, with destructiveHint=true in annotations, it does not clarify whether accepting is irreversible or what happens to the suggestion after acceptance, so some behavioral context is still 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?

The description is three concise sentences, front-loaded with the core purpose, followed by the mechanism and prerequisite. It contains no redundant fluff and every sentence adds 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 moderate-complexity action tool with 4 parameters, no output schema, and destructive annotation, the description covers the purpose, state change, prerequisite ordering, and an account ownership constraint. It could additionally mention response behavior or explicitly contrast with dismiss_budget_suggestion, but it is sufficiently complete 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 already describes budgetId, customerContext, and editedBeforeAccept (75% coverage). The description adds useful relational context for budgetId by explaining the prerequisite and that the budget must belong to your account. However, the `id` parameter is not explicitly defined in either the schema or the description, relying on the tool name and context.

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 ('accept') and resource ('budget suggestion'), and clearly distinguishes this from sibling tools by stating that it 'Marks the suggestion as accepted and links it to an existing budget.' This differentiates it from dismiss_budget_suggestion and list_budget_suggestions.

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: create the budget first via `POST /analytics/v1/budgets`, then pass its id as `budgetId`. It also notes the budget must belong to your account. It does not explicitly name an alternative tool for dismissing suggestions, but the context is clear enough.

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

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

The description discloses key behaviors: tag normalization (trim + lowercase), prefixing with 'customer_tag/' for customer-submitted tags, no-op on duplicate tags, and response echoing actual stored strings. These details go beyond the annotations and give a clear expectation of 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 concise and well-organized in two paragraphs. The first sentence ('Create and manage support tickets with DoiT.') is generic and somewhat redundant, but the rest is focused and efficient. No unnecessary verbosity.

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 operation's side effects, normalization, and idempotency, and mentions the response echoes stored strings. It does not discuss error conditions or authorization requirements, but for a mutating tag-add operation, the provided context is sufficient for an agent to understand the tool's 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 description adds significant meaning to the tags parameter by explaining normalization, prefixing, and the no-op behavior. It also clarifies that ticketId refers to an existing support request, supplementing the schema's minimal description and complementing the customerContext parameter's schema description.

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

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

The description clearly states the tool's function: adding one or more tags to an existing support request. It explicitly mentions that the operation is surgical and preserves existing tags, distinguishing it from broader ticket update tools.

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

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

The description implies when to use this tool (when adding tags without affecting other ticket fields) but does not explicitly compare it to alternatives like update_ticket or remove_ticket_tags. The mention of 'surgical' and 'no-op on re-add' provides behavioral context but lacks explicit usage guidance.

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

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

Beyond readOnlyHint=true annotation, description discloses latency for complex questions and error handling behavior. Does not contradict annotations. Could add more about response structure but sufficient.

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

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

Two sentences plus a note, no wasted words. Front-loaded with purpose. Every sentence adds 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?

Given the open-ended Q&A nature with no output schema, description covers usage scope, latency, and error recovery. Could mention follow-up capabilities but overall sufficient.

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

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

Schema coverage is 100% with clear descriptions for each parameter. Description does not add new parameter details beyond schema. Baseline score adequate.

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 purpose: asking DoiT AVA questions about cloud costs, infrastructure, etc. It specifies the verb 'ask', the resource 'AVA', and the domain, distinguishing it from general-purpose AI queries.

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 to use only for DoiT or cloud-specific questions, not general AI. Mentions latency and error handling guidance. Lacks explicit sibling tool alternatives but provides clear context boundaries.

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?

Annotations already declare destructiveHint=true and openWorldHint=true, covering mutation and side effects. The description adds the confirmation requirement but does not elaborate on permissions, error states, or operation details.

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

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

Three sentences, each serving a purpose: usage context, confirmation guideline, and exclusion of sibling tools. Front-loaded with purpose, 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?

Describes operation and provides usage guidance, but lacks information about return values, success/error responses, or behavior of simultaneous add and remove. Given no output schema, the agent may need more context on expected outcomes.

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

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

Schema description coverage is 100%, so the schema fully documents the parameters. The description adds no additional semantic value beyond stating 'assign or unassign cloud resources' – no extra detail on add/remove arrays or object types.

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?

Clear verb+resource: 'assign or unassign cloud resources to a label'. Explicitly distinguishes from sibling tools create_label and get_label_assignments, leaving no ambiguity about 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?

Explicitly states when to use (user wants assign/unassign) and when not to (creating labels or viewing assignments), naming alternative tools. Also advises to ask user confirmation before executing.

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

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

The description richly discloses behavior beyond the annotations: immediate 202 response, Location header pointing to status, required Idempotency-Key for at-most-once submission, deduplication returning the existing in-flight operation, and dry-run validation. This is especially valuable given the annotations only convey read/write/open-world flags and the tool has a side-effecting async workflow.

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, moving from the operation to response behavior to required header to deduplication and dry-run validation. The first sentence is broad and somewhat generic, but every later sentence adds concrete, useful information.

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

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

Given the complexity of the tool and the absence of an output schema, the description adequately covers invocation, required header, duplicate behavior, and dry-run mode. It intentionally leaves polling/result retrieval to sibling tools like get_async_operation and get_async_operation_results, which is a reasonable boundary.

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

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

Schema coverage is only 50%, but the description adds important semantic meaning to Idempotency-Key (at-most-once deduplication) and dryRun (validate without creating an operation), which the schema itself does not explain. The config and customerContext parameters are already reasonably described in the schema, so the description compensates for the gaps where it matters most.

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

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

The description names a specific operation: submitting an async report execution job using an inline configuration and receiving a 202 with a Location header. It distinguishes from async_run_report_by_id by emphasizing 'inline configuration', though it never names the sibling or states the contrast explicitly.

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

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

It provides useful context: use for async submissions with inline configs, and use ?dryRun=true to validate without creating an operation. However, it gives no explicit guidance on when to prefer this tool over async_run_report_by_id or any other alternatives.

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

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

Annotations mark this as destructive and non-read-only; the description adds the key side effect that a normal call creates an operation, while dryRun avoids it. It also discloses the immediate 202, Location header, and required Idempotency-Key header—information not present in the annotations. It does not mention downstream result retrieval or potential cost, but it is substantially 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 compact and front-loaded: the operation is stated in the second sentence, followed by response shape, idempotency requirement, and dryRun behavior. The first 'Manage Cloud Analytics reports and get reports data in JSON format' sentence is somewhat generic and could be trimmed, but the rest 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?

It covers the essentials for invoking the tool: required header, dryRun validation, async creation, and the Location header. But because there is no output schema, the description should also point toward polling or result retrieval via the async operation endpoints, and it does not clarify the date/timeRange override parameters. The destructive annotation also makes it worth explaining more about what executing a report entails.

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

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

The description adds meaning beyond the bare schema for the central parameters: id is the saved report identifier, Idempotency-Key is a required header, and dryRun validates without creating an operation. However, with schema description coverage at only 14%, the startDate, endDate, and timeRange parameters remain unexplained in both schema and description, leaving a real gap for optional date-range control.

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

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

The description names a concrete operation—submitting an async execution job for a saved report by ID—and states the immediate 202 response with Location header. This distinguishes it from related report tools like get_report_results, async_run_inline, and run_query. The opening sentence is broad, but the specific clauses carry the meaning.

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

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

The description gives clear context: use this tool when you need to execute a saved Cloud Analytics report asynchronously, and use dryRun=true to validate without side effects. It also makes the Idempotency-Key prerequisite explicit. It does not name alternative tools or explicitly say when not to use it, so it stops short of full routing guidance.

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

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

Annotations indicate destructiveHint and readOnlyHint false, so the tool mutates state. The description adds only 'help improve response quality', which is vague. It does not clarify what gets changed (e.g., feedback record created, model retraining triggered) or any side effects like rate limits or required 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 two sentences, but the first sentence 'Interact with Ava, DoiT's AI-powered cloud assistant' is somewhat redundant. The second sentence carries the true purpose. It is efficiently short, but the first sentence could be trimmed without loss.

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 destructive nature, nested schema, and no output schema, the description is minimally adequate. It does not explain where to find conversationId/answerId, how customerContext works, or what happens after submission. It lacks guidance for proper usage in the broader context of Ava interactions.

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 high (all four parameters have descriptions), setting a baseline of 3. The description adds no additional meaning beyond what the schema provides for parameters like conversationId, answerId, or feedback. No syntax, format, or relationship between parameters is clarified.

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 'submit feedback' and the resource 'Ava answer'. While it begins with a broad 'Interact with Ava', it quickly narrows to feedback submission. It differentiates from sibling tools like ask_ava_streaming and ask_ava_sync by its distinct purpose, though not explicitly.

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

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

No guidance on when to use this tool versus alternatives. It does not advise against using it for asking questions, nor does it mention prerequisites like having a conversation or answer ID. The description leaves usage context entirely implicit.

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?

Annotations indicate this is a non-read-only, non-destructive operation, but the description adds valuable behavior: it streams real-time progress, returns the created flow's ID, the builder's answer, and the build steps that ran. This goes beyond the annotation flags and helps the agent set expectations about the tool's side effects and result format.

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, front-loads the trigger condition, and includes the key usage distinction and output summary. Every sentence earns its place without redundancy or unnecessary detail.

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

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

Given the lack of an output schema, the description adequately covers return values and the streaming behavior. It omits only minor details such as the exact meaning of 'builder's answer' and how streaming is delivered, but the core information an agent needs to call this tool correctly is present.

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

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

Schema description coverage is 100%, and the schema already documents both `question` and `conversationId` clearly. The description adds general context about the natural-language build process and return values but does not materially deepen parameter-level understanding beyond what the schema 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 a specific action ('build a brand-new CloudFlow automation from scratch') and specifies the output: the new flow's ID, the builder's answer, and the build steps. It also differentiates itself from the sibling tool refine_cloudflow, making its scope 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 when to use the tool ('when the user wants to build a brand-new CloudFlow automation from scratch using natural language') and when not to, naming the alternative: 'Use refine_cloudflow to change an existing flow; use this only to create a new one.' This gives clear selection 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?

Beyond the destructiveHint annotation, the description discloses idempotent behavior for already-terminal operations, a 404 for nonexistent or cross-tenant operationIds, and a dryRun mode that performs validation without modifying state. This is strong behavioral context that helps an agent predict 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 cancellation behavior, idempotence, 404 condition, and dryRun guidance are concise and useful. The first sentence about managing reports and getting JSON data is unrelated boilerplate that does not earn its place and adds confusion.

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 important behavioral details and error conditions, which is good for a destructive async-cancellation tool. However, it omits explanation of the required Idempotency-Key, does not describe the response format, and does not mention the customerContext scoping rule that the schema only partially covers.

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

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

The description adds meaning for dryRun (validate without state changes) and operationId (the operation to cancel), but it does not explain the required Idempotency-Key parameter at all. With schema coverage at only 25%, this leaves a key parameter under-documented; customerContext is described only in 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 core sentence 'Cancels a pending or running async report operation' clearly identifies a specific verb and resource, and distinguishes it from sibling operations like get_async_operation or get_async_operation_results. However, the opening sentence about managing reports and getting JSON data is generic and could mislead an agent about what this tool actually 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?

The description makes it clear this tool is for canceling pending or running async operations, and mentions dryRun for validation. However, it does not explicitly contrast it with alternatives such as get_async_operation or get_async_operation_results, nor does it state when not to use it.

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

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

Annotations already indicate destructive and non-read-only, but the description adds significant context: soft cancel behavior, retention of invite document, visible cancelled status, token invalidation, and error cases. No contradiction with annotations.

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 6 sentences covering purpose, behavior, errors, and permissions. It is well-structured and front-loaded with key info, though the first sentence is somewhat generic ('Manage users...') and could be trimmed.

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?

No output schema exists, but the description explains the effect (soft cancel, token invalidation, status) and error codes. It mentions required permission. Lacks detail on dryRun and Idempotency-Key, but overall sufficient for a cancel operation.

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

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

Schema coverage is only 25% (one parameter has description), and the tool description does not explain dryRun, Idempotency-Key, or the id format. The description only implies id is the invite ID. Given low schema coverage, 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 clearly states the tool marks an invite as Cancelled and invalidates the token, distinguishing it from full deletion via DELETE. It specifies the verb and resource, and differentiates from sibling tools like delete_user and invite_user.

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 tells when to use this tool (soft cancel) versus DELETE for full removal. Also mentions error conditions (404, 409) and required permission (usersManager), providing clear context for when to invoke.

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?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the description doesn't need to restate safety. The description adds that period1 includes the current month, which is useful behavioral context. No contradictions.

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 sentences, front-loaded with purpose, no unnecessary words. Every sentence adds value. 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 moderate complexity (4 params, 1 required, no output schema) and comprehensive annotations, the description is fully adequate. It explains the two-period concept, provides usage guidance, and doesn't miss critical 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?

Schema description coverage is 100%, so parameters are already documented. The description adds context about rolling lookback vs explicit range, which is a nuance beyond the schema. But it doesn't significantly impact parameter 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 the tool's purpose: compare spend between two time periods, with examples. It also distinguishes it from run_query for multi-period analysis, making the 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?

Explicitly tells when to use (two-period comparison) and when not to (more than two periods, use run_query). Also explains the difference between period1 (rolling lookback) and period2 (explicit range), providing clear context.

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

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

The description states this tool finalizes a pending write action including 'deleting a resource,' which is inherently destructive, yet the annotations declare destructiveHint=false. This is an annotation contradiction. The extra details about user confirmation and token expiry are useful but cannot overcome the contradiction.

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 sentences with no redundant filler, front-loaded main purpose (what it finalizes) before usage conditions. 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?

For a single-parameter confirmation tool, the description covers the call condition, negative condition, and token handling. No output schema is present, but return value descriptions are not essential for correct invocation here; still, a mention of expected response could make it fully complete.

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

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

Schema coverage is 100%: the schema already documents 'token' with exactness requirements. The description repeats 'Pass the token exactly as it was returned,' adding no new semantics beyond the schema, so it stays at baseline 3.

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

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

The description names a specific verb ('finalizes') and a specific resource ('a pending write action ... previously staged by another tool'). It distinguishes this from all sibling read/write tools by clarifying it is the confirmation step, not the operation itself.

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 call ('only after the user has explicitly confirmed the action summary') and when not to ('If the user declined, do not call this tool'), including the fallback behavior (token expires automatically).

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?

Annotations already declare readOnlyHint=true and destructiveHint=false. Description adds behavioral details: returns top-N items ranked by cost descending, default months=1 includes current month. This goes beyond annotations with specific operational 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?

Two sentences, minimal and efficient. First sentence states purpose with examples, second provides alternative. No redundant information.

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

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

No output schema, but description notes returns top-N ranked list. Lacks details on cost format (e.g., currency), but sufficient for typical use. Annotations and schema fill gaps well, making it nearly complete.

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

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

Schema coverage is 100% with descriptions for all parameters. Description does not add significant new meaning; it restates the grouping dimension and cloud alias, which are already in schema. Baseline 3 is appropriate as schema fully documents 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?

Description states 'simple cost breakdown by service, project, or cloud provider' with examples, clearly indicating the tool's function and output (top-N ranked by cost descending). This distinguishes it from siblings like run_query for complex queries.

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 says 'Use this when the user wants a simple cost breakdown' and provides an exclusion: 'For complex multi-filter or multi-metric queries, use run_query instead.' This gives clear when-to-use and when-not-to-use with an alternative 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?

Annotations already provide readOnlyHint: true and destructiveHint: false, so the description carries less burden. It adds value by stating returns 'monthly cost data points' and the optional breakdown. No contradictions. The description could mention auth or rate limits, but annotations cover safety, so a small deduction is appropriate.

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 purpose and examples. Every sentence is valuable and non-redundant. It achieves high information density without waste.

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 has 4 optional parameters and no output schema, the description adequately explains the output ('monthly cost data points, optionally broken down'). It covers the main use case and distinguishes from siblings. Minor gap: could mention the default months=6 explicitly, but the schema already has a default.

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

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

Schema description coverage is 100%, so baseline is 3. The description adds minimal extra meaning: it mentions 'optionally broken down by service/project/cloud' which maps to groupBy, but the schema already describes it. The usage context is slightly enriched but not enough to raise the score above baseline.

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 purpose: to show monthly spend over time. It uses specific verbs ('see', 'returns') and identifies the resource ('monthly cost data points'). The examples ('Show me my cost trend') make it concrete. It also distinguishes from sibling tools by noting the alternative for daily/custom intervals.

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?

Explicit when-to-use guidance with examples ('when the user wants to see monthly spend over time'). Explicit when-not-to-use: 'For daily granularity or custom time intervals, use run_query instead.' This is a clear alternative, satisfying the highest level of this dimension.

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

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

The description adds a couple of behavioral details beyond annotations: it does not update Firestore channel documents and does not require a CloudFormation stack ID. The annotations already indicate destructive and open world behavior. The description could be improved by mentioning side effects, permissions required, or rate limits, but the provided details are helpful.

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, but the first sentence is overly broad ('Manage cloud provider connections and check feature availability') and could be misleading. The core action is in the second sentence. A more concise, front-loaded description would improve clarity. The current structure is adequate but not optimal.

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 there is no output schema, the description should explain what the tool returns (e.g., the created/updated document). It also does not define what a CloudConnect document is, nor does it elaborate on 'check feature availability.' The tool has 6 parameters and annotations indicating destructive behavior, but the description lacks details on the expected outcome and broader 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 input schema has 100% parameter description coverage, so the schema itself documents each parameter's meaning and constraints. The tool description does not elaborate on parameters beyond what the schema provides. It mentions 'check feature availability' which could relate to enabledFeatures, but this is not explicit. Therefore, the description adds minimal value in this dimension.

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 the tool creates or updates a CloudConnect document for an AWS account. The verb 'creates or updates' and the resource 'CloudConnect document' are specific. However, the first sentence 'Manage cloud provider connections and check feature availability' is vague and not directly aligned with the tool's primary action. It differentiates from a CloudFormation variant but not from sibling tools like delete_account_role or update_aws_feature.

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 comparison to the CloudFormation variant, noting that this endpoint does not update Firestore channel documents or require a CloudFormation stack ID. This offers some context for choosing this tool over an alternative. However, it does not explicitly state when to use this tool versus other account role management tools (e.g., delete_account_role), nor does it mention prerequisites or typical scenarios.

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?

Description adds behavioral context beyond annotations by instructing the agent to confirm with the user before executing. Annotations already indicate destructive nature, but confirmation step is a valuable addition.

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 sentences, front-loaded with purpose and usage guidelines. Every part 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?

Given the complexity of the nested config object and no output schema, the description provides adequate context. It could mention return values or idempotency but adds enough for a confident agent invocation.

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

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

Schema description coverage is 100%, so the schema already explains parameters thoroughly. The description adds minimal extra semantics (e.g., 'thresholds' maps to config.value). Baseline 3 is appropriate.

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

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

The description clearly states the tool's purpose: setting up a new cost alert with thresholds and notification settings. It also distinguishes it from sibling tools like create_budget and list_alerts.

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 provides when-to-use (setting up a new cost alert) and when-not-to-use (not for budgets or viewing alerts), with specific sibling tool names as alternatives.

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

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

Annotations already indicate destructiveHint=true, so the description adds value by instructing to confirm parameters before execution. However, it does not elaborate on what exactly is destroyed or other behavioral traits like necessary permissions or side effects, leaving some gaps.

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

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

The description is concise, with three sentences that front-load the purpose and provide clear boundaries. No extraneous information, every sentence is valuable.

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 (nested objects, mutually exclusive rule vs. rules), the description is too brief. It does not explain the structure of rules or guide on choosing between 'rule' and 'rules'. The schema helps, but more context is needed for full agent comprehension.

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

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

Schema description coverage is 100%, so the baseline is 3. The description does not add any additional meaning beyond the schema; it only generically mentions 'allocation parameters' without deepening understanding of the rich nested structures.

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 is for creating a new cost allocation rule, using a specific verb and resource. It also distinguishes it from sibling tools like list_allocations (viewing) and create_label (labels), avoiding ambiguity.

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 tells when to use (user wants to create a new allocation rule), when not to use (viewing existing allocations or creating labels), and provides alternatives. Also instructs to ask user for confirmation before executing, setting clear usage expectations.

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?

Annotations already indicate readOnlyHint false and destructiveHint true, but the description adds the valuable context to ask user for confirmation, mitigating the potential destructive nature. No contradiction with annotations.

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 sentences convey purpose, usage boundaries, and a confirmation step with no extraneous information. Front-loaded and 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?

Given 4 parameters and no output schema, the description covers the core purpose and usage context. It lacks details on return behavior but is sufficient for an informed 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?

Schema coverage is 100% with descriptions for all 4 parameters. The description does not add additional parameter semantics beyond what the schema provides, meeting the baseline expectation.

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 adds a new annotation to mark a specific date or event in cost data. It explicitly distinguishes from sibling tools create_label and create_alert, eliminating ambiguity.

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 when-to-use (user wants to mark a date/event) and when-not-to-use (for labels or alerts), and instructs to ask user for confirmation, offering clear 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?

Annotations indicate destructiveHint=true and readOnlyHint=false, which align with creating an asset. However, the description adds no behavioral details beyond what annotations already convey, such as idempotency, side effects, or required 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 short (two sentences) but the first sentence is generic and could be removed. It front-loads the action but does not earn its place with specific details. Conciseness is adequate but not optimal.

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 has 5 parameters with zero required fields, no output schema, and many siblings, the description fails to provide sufficient context. It does not explain what an asset is, how parameters like mode or type affect the creation, or what the outcome looks like.

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

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

Schema description coverage is only 20% (one parameter described), but the description does not provide any parameter guidance. The parameter names (mode, type, rootEmail, accountName) are left unexplained, relying solely on their names which may be 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 states 'Creates a new asset' which gives a general purpose, but it is vague and does not differentiate from many other create_* siblings (e.g., create_account_role, create_budget). The first sentence 'Manage cloud resources or services' is overly broad and does not specify what constitutes an asset.

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

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

No guidance is given on when to use this tool versus alternatives like create_account_role or create_budget. There is no mention of prerequisites, required parameters, or scenarios where this tool is appropriate.

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?

Annotations already indicate destructive and non-read-only behavior. The description confirms creation but does not add details beyond that. It includes a confirmation step but omits information about permissions, side effects, or that the tool can create alerts within the budget. The open world hint suggests additional unspecified behaviors.

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

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

The description is extremely concise at three sentences, front-loading the purpose, then required parameters, then usage guidelines and exclusions. Every sentence serves a clear purpose with no unnecessary 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 tool's complexity (19 parameters, including nested objects), the description is somewhat minimal. It doesn't explain that alerts can be created within the budget, nor does it describe the return value. However, it does distinguish from create_alert and provides basic context. The absence of an output schema is partially mitigated by the annotations.

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

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

Schema description coverage is 100%, so the description does not need to add much parameter information. The description briefly mentions required parameters but does not elaborate on optional ones like alerts or collaborators. This is adequate given the schema already explains each parameter in detail.

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

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

The description clearly states the tool creates a new cloud budget with spending limits and alert thresholds. It specifies required parameters and explicitly distinguishes from sibling tools like list_budgets, get_budget, and create_alert, ensuring the agent knows when to use this tool.

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

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

The description provides explicit usage guidance: use when the user wants to create a budget, and it lists what not to use (viewing or alert creation) with alternative tools. It also instructs the agent to ask the user to confirm parameters before executing, which is a clear usage guideline.

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

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

Annotations already indicate readOnlyHint=false and destructiveHint=true. The description adds behavioral context: the tool is for creation, requires confirmation, and that it connects an account for automation. It does not detail potential side effects (e.g., costs), but provides useful beyond-annotation guidance.

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, concise, and front-loaded with the core purpose. Every sentence adds essential information with no 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 tool's complexity (nested objects, no output schema), the description covers purpose, usage constraints, and confirmation needs. It does not explain return values or error scenarios, but for a create tool with clear sibling differentiation, it is 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?

Schema coverage is 100%, so baseline is 3. The description adds value by emphasizing the mutual exclusivity of gcpConfig and awsConfig and the need for user confirmation. It does not repeat parameter schemas but adds contextual usage hints.

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 creates a new CloudFlow cloud provider connection (GCP or AWS). It uses a specific verb ('create') and resource ('CloudFlow connection'), and distinguishes from sibling tools like update_cloudflow_connection and trigger_cloud_flow.

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 the user wants to create...' and provides when-not-to-use guidance (do not use for updates or triggering). It also specifies the constraint that exactly one of gcpConfig or awsConfig must be supplied, and advises confirming with the user before executing.

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?

Annotations already indicate mutation (readOnlyHint=false, destructiveHint=true). Description adds only permission requirement, not additional behavioral context like overwrite behavior or limits.

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?

Single sentence, no waste, front-loaded with action. Could include more context without being verbose.

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?

Covers creation and permission but lacks output info, error cases, or naming constraints. Adequate for a simple create tool with good 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?

Schema description coverage is 100%, so baseline is 3. Description adds no extra parameter meaning beyond 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?

Description clearly states the verb ('creates') and resource ('custom color theme'), distinguishing it from update_theme, delete_custom_theme, and get_theme siblings.

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

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

Mentions required permission but no guidance on when to use vs alternatives (e.g., update_theme) or when not to use.

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

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

Description adds the behavioral trait of requiring user confirmation before execution, which is not captured by annotations. Annotations indicate destructiveHint=true, which aligns. No contradictions.

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

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

Three sentences that are front-loaded with purpose, followed by usage guidance and exclusions. No unnecessary 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 tool with two parameters and no output schema, the description fully covers purpose, usage conditions, and exclusions. An agent can correctly invoke the tool.

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

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

Schema description coverage is 100%, so the schema already documents both parameters adequately. Description does not add additional semantic detail beyond what is in 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 explicitly states 'Use this when the user wants to create a new DataHub dataset' and distinguishes from sibling tools for viewing and sending events, providing a specific verb and 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?

It clearly tells when to use (create) and when not to use with explicit alternatives (list_datahub_datasets, send_datahub_events), and advises to ask for user confirmation before executing.

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?

Description mentions creation and confirmation step, but does not elaborate on destructive potential (destructiveHint=true). Annotations already indicate mutation and destructiveness; description adds minimal extra transparency.

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

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

Two sentences, front-loaded with purpose, no redundant information.

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

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

No output schema exists; description does not mention return value (e.g., created folder ID). Otherwise adequate for a create tool with good annotations.

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 covers all three parameters (name, description, parentFolderId) with descriptions. The tool description adds no additional meaning beyond the schema. Baseline 3.

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?

Clearly states 'create a new Cloud Analytics folder' with specific verb and resource. Distinguishes from siblings by explicitly naming create_report and create_label as different tools.

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

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

Explicitly says 'Use this when...' and 'Do NOT use this for...' with specific alternatives. Also instructs to ask user for confirmation before execution.

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?

Annotations already mark the tool as readOnlyHint=false, destructiveHint=true, and openWorldHint=true, so the description does not need to restate those. It adds useful behavioral context about ownership and permission requirements, but it does not explain what destructive side effects may occur when creating a region or whether it can overwrite/replace existing configurations.

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

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

The description is short and efficient, three sentences with no filler. It opens with the overall purpose, quickly narrows to the specific creation action, and then lists the critical constraints. Every sentence contributes useful information.

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

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

The description provides key constraints and permission requirements, but leaves gaps around parameter details, side effects, and the meaning of a custom region in the broader geographic access model. It is adequate for basic invocation but not fully complete for an agent that has no other context, especially given the low schema description coverage and the absent 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?

Schema description coverage is only 25%, with only customerContext described. The description does not clarify the meaning of name, countryCodes, or X-Tenant-Id. It provides high-level context about country-based access and tenant ownership, but does not compensate for the lack of parameter-level documentation in 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 states a clear action ('Creates a custom region') with a specific resource ('custom region owned by the authenticated tenant'). It also provides meaningful context ('country-based access to tenants in your customer hierarchy') that distinguishes it from the many get/list/update/delete geographic access sibling tools.

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

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

The description gives explicit prerequisites: the tenant must be a customer-hierarchy root and the caller must have the UsersManager permission. It does not explicitly state when to use this tool versus alternatives, but the creation purpose and conditions are clear enough for an agent to select 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?

Annotations already indicate destructiveHint=true and openWorldHint=true. The description adds the instruction to confirm with the user before executing, which reinforces cautious behavior. While it doesn't detail further side effects, it aligns with annotations and adds practical guidance.

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 sentences, front-loaded with purpose, no wasted words. Essential information is presented 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?

Given the tool's simplicity (2 required params, no output schema), the description covers purpose, usage boundaries, and a safety step. It is complete enough for effective agent use, though could mention the scope (e.g., workspace).

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 covers 100% of parameters with descriptions, so schema alone is sufficient. The description does not add extra semantic detail beyond what the schema provides, maintaining baseline adequacy.

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 purpose: 'create a new resource label'. It distinguishes from sibling tools like list_labels and create_annotation, ensuring the agent can select the correct tool.

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

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

Explicitly states when to use (user wants to create a label) and when not to use (viewing labels or annotations), with alternatives. Also instructs to ask user for confirmation, providing clear action boundaries.

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?

Annotations indicate destructiveHint=true, so the description's mention of 'save' aligns. It adds the behavioral note to confirm parameters before execution. No contradictions, but could disclose more about side effects 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 sentences, no unnecessary words. Front-loaded with core purpose and usage guidance. Every sentence adds 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?

Given the complexity of the config object and no output schema, the description provides sufficient context: when to use, how to use (confirm, use dimension tool), and exclusion cases. Could elaborate on return value but not essential.

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

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

Schema coverage is 100%, so baseline is 3. The description adds value by referencing the dimension tool for valid IDs and advising parameter confirmation, which aids correct usage 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 is for saving a new Cloud Analytics report with a specific configuration, using the verb 'save' and specifying the resource. It also distinguishes from run_query for one-time queries, 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?

Explicitly states when to use (user wants to save a new report) and when not to use (one-time queries, directing to run_query). Also advises to ask user to confirm parameters, providing clear usage instructions.

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?

Annotations already indicate destructiveHint=true and readOnlyHint=false. The description adds the important behavioral trait that user confirmation is required before execution, providing context beyond the annotations. It does not contradict annotations.

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 long: the first states the purpose, the second provides usage guidance and exclusions. It is front-loaded and every sentence is necessary with no 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?

Despite the nested object parameters and lack of output schema, the description covers when to use, confirmation requirement, and exclusions. It is adequate for a simple creation tool but could mention response or validation behavior. Still, it is sufficiently complete for the task.

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 does not describe any parameters. The input schema has a nested object with 6 required properties, each with descriptions, but the description adds no meaning beyond the schema. With 0% schema description coverage, 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 clearly states the tool creates a new support ticket and explicitly distinguishes it from viewing tickets (list_tickets) and cloud incidents (get_cloud_incidents). The verb and resource are 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?

The description provides explicit when-to-use (user wants to create a new support ticket) and when-not-to-use (viewing existing tickets, cloud incidents) with sibling tool names. It also instructs to ask the user to confirm details before executing.

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?

Discloses that for customers comments are always public, and for employees the private flag controls internal notes. Adds context beyond annotations, which only indicate read/write and destructiveness.

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 sentences, front-loaded with purpose and then behavioral nuance. No unnecessary 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?

Covers essential behavioral differences and parameter roles. Lacks mention of return value or success indication, but given no output schema, this is minor.

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

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

Schema coverage is 100% with descriptions, so description adds minimal extra value. The description reinforces the private flag behavior already in schema, but includes role-based context.

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 verb 'adds' and resource 'comment to existing support ticket'. It distinguishes from sibling tools like list_ticket_comments (lists) and create_ticket (creates ticket).

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?

Describes when to use (to add comment) and includes context about public vs private for customers vs employees. Does not explicitly state when not to use or mention alternatives like list_ticket_comments.

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

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

The description adds behavioral details beyond annotations: latency (up to 15 minutes), file format constraints (CSV, ZIP, GZ), and max file size (30 MB). It does not contradict annotations. The destructive hint is appropriately supported by the 'Ingest' action. However, it does not clarify authorization needs or what exactly gets modified.

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. No wasted words. The first sentence covers the core action, and the second adds essential constraints and latency info.

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

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

For a tool with no output schema, the description does not mention what the response or return value is (e.g., success confirmation). It covers the main use case, constraints, and latency, but lacks details on error handling or result format. Given the simplicity, it's adequate but not fully complete.

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

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

Schema coverage is 100%, so the schema already describes all parameters. The description adds no new information about parameter semantics beyond what's in the schema. According to the rule, baseline is 3 when schema coverage is high.

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 ingests third-party data via CSV file. The verb 'Ingest' and 'Sends' with resource 'events to DataHub' are specific. However, it does not explicitly differentiate from its sibling 'send_datahub_events', which likely serves a similar purpose but perhaps with different input format.

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 for sending batch CSV data but provides no explicit guidance on when to use this tool versus alternatives like 'send_datahub_events' or 'delete_datahub_events_by_filter'. It mentions a latency of 15 minutes but no exclusions or prerequisites.

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

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

Annotations already declare destructiveHint=true, and the description reinforces this by saying 'Deletes a CloudConnect document.' It adds a bit of context by naming the specific resource and account type, but does not detail side effects, reversibility, or prerequisites.

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

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

The description is short but includes an extraneous first sentence that broadly describes cloud provider management. The relevant delete action is front-loaded only after that sentence, so the structure could be tighter.

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

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

For a simple delete operation with two straightforward parameters, the description is minimally adequate. It lacks details on return values, error cases, or whether the account role must exist, but the low complexity keeps these gaps from being severe.

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 no parameter-level meaning; the schema covers customerContext but not accountID. However, accountID is self-explanatory by name and is the required parameter, so the absence of description text 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 second sentence clearly states the tool 'Deletes a CloudConnect document for an AWS account,' specifying both the verb and resource. However, the first sentence about managing cloud provider connections and checking feature availability is broader than the delete action and could distract from the core 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?

No explicit guidance is given about when to use this tool versus alternatives like create_account_role or delete_cloudflow_connection. The usage is only implied by the word 'Deletes.'

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?

Annotations already indicate destructiveHint=true, so the description adds no behavioral context beyond stating 'Deletes'. It does not describe that deletion is irreversible, whether any permissions or dependencies exist, or what the side effects are. With annotations covering the destructiveness, the description could still add value by mentioning permanence.

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

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

The description is short with two sentences. The first sentence is misleading and irrelevant to the delete action; it could be removed. The second sentence is concise. Overall, it is minimally acceptable but has unnecessary 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 destructive tool with two parameters and no output schema, the description should cover permanence, authorization requirements, and consequences. It only states the basic action. Given the low complexity, a better description would add details about confirmation or revertibility.

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

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

Schema description coverage is 50% (only customerContext has a description). The description does not mention or explain either parameter. For the 'id' parameter, which has no schema description, the description offers no help. The description adds no meaning beyond what the schema 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 states 'Deletes the alert specified by the Id.' which clearly indicates the verb and resource. However, the first sentence about notifications is conceptually tangential and could cause confusion about the tool's purpose. The tool is well-distinguished from siblings like create_alert and update_alert.

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 delete versus alternatives (e.g., deactivating an alert). There is no mention of prerequisites, such as the alert needing to exist, or any conditions that should be checked before deletion.

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?

Annotations already declare destructiveHint=true, so the description's 'Deletes' is consistent but adds no additional behavioral context (e.g., reversibility, cascading effects, permission requirements). The confusing first sentence does not aid 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, but the first sentence ('Define how costs are distributed...') is unnecessary and could be removed to improve conciseness. The structure is otherwise adequate.

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 (delete by ID) and annotations providing destructive hint, the description is partially complete. However, it lacks context about when to use this tool, potential impacts on cost distribution, and any dependencies like required role permissions.

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

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

The description adds meaning to the 'id' parameter (specifies which allocation to delete), which lacks a schema description. The 'customerContext' parameter is described in the schema. With 50% schema coverage, the description partially compensates but does not detail the id format or constraints.

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

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

The description clearly states the action ('Deletes') and resource ('allocation'), and the identifier ('Id'). This distinguishes it from sibling tools like create_allocation, update_allocation, and get_allocation. However, the initial sentence 'Define how costs are distributed...' is a general definition of an allocation, not the tool's purpose, adding minor confusion.

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 (e.g., update_allocation or disabling an allocation). It does not mention prerequisites, such as the need for the allocation to exist, or any consequences of deletion.

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?

Annotations already mark destructiveHint=true, so description correctly implies destructive action. But it adds no additional behavioral context such as whether deletion is permanent, requires specific permissions, or has cascading effects. Minimal value beyond annotations.

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 sentences; the first sentence is unnecessary context about annotations in general and could be removed. The core deletion instruction is clear but could be more concise.

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

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

No output schema, so description should cover return behavior, error cases, or side effects. It leaves these unaddressed. For a destructive operation, more context is needed for safe 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?

Input schema covers 50% of parameters (customerContext has a description, id does not). The description merely references 'the Id' but does not explain the id parameter format or the optional customerContext. Schema coverage baseline is 3, and description adds little.

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 'Deletes the annotation specified by the Id,' specifying the verb and resource. It distinguishes from sibling tools like create_annotation, update_annotation, get_annotation, and list_annotations. However, the first sentence about 'Custom notes added to cost data' is redundant and may confuse, preventing a perfect score.

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

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

No guidance on when to use this tool versus alternatives like update_annotation or list_annotations. The description does not provide context on prerequisites, idempotency, or typical use 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?

Annotations already declare destructiveHint=true, so the description's mention of deletion aligns. However, no additional context is added (e.g., irreversibility, required permissions, or side effects). The description meets the baseline but does not enhance transparency beyond annotations.

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

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

The first sentence ('Interact with Ava...') is redundant and not specific to deletion, adding unnecessary fluff. The core purpose is in the second sentence. While short, it could be more concise and focused.

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 (2 params, no output schema, annotations present), the description covers the basic functionality. However, it omits any details about the result of deletion (e.g., success/failure indication) or potential side effects, making it somewhat 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?

The description explicitly ties the conversationId parameter to the object being deleted ('by its ID'), adding meaning beyond the schema's bare string type. The customerContext parameter is already described in the schema. This provides sufficient context for both 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 action ('Deletes') and the resource ('Ava conversation'), making it easy to distinguish from sibling tools like ask_ava_streaming or ava_feedback. The verb and target are specific.

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 (e.g., not mentioning that it's for deleting completed conversations). There is no advice on prerequisites, permissions, or scenarios where deletion is appropriate.

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?

Annotations indicate destructiveHint=true, but the first sentence misleadingly suggests a read-only tracking function. The description adds confusion rather than clarity.

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

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

The first sentence is irrelevant and misleading, making the description less concise and adding unnecessary confusion.

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?

Without an output schema, more behavioral context is needed (e.g., effects, reversibility). The description only states deletion without further details.

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

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

Schema coverage is 50% with only customerContext described. The description does not explain the id parameter or provide any additional parameter context.

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 second sentence clearly states deletion, but the first sentence about tracking spend contradicts the tool's actual purpose, causing confusion.

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

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

No guidance on when to use this tool versus alternatives like update_budget or list_budgets, and no indication of prerequisites or limitations.

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?

Annotations indicate destructiveHint=true, and the description adds that the tool is destructive ('Deletes a connection') and provides specific behavior: returns 409 if the connection is referenced by one or more flows. This adds value beyond annotations by disclosing a conflict scenario.

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 concise with two sentences. It front-loads the purpose and provides a key behavioral detail without any fluff. 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?

Given the tool's simplicity (delete operation with two parameters), the description is sufficiently complete. It covers the resource type, action, and a relevant error condition. No output schema exists, so return details are not needed. Minor missing context on success response, but acceptable.

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

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

Schema coverage is 50% (only customerContext has a description). The description does not mention either parameter or add meaning beyond the schema. For a tool with low schema coverage, the description should compensate but fails to do so.

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 'Deletes a connection' on a specific resource 'cloud provider connections used in CloudFlow workflows (AWS and GCP)'. It distinguishes from siblings like create_cloudflow_connection and update_cloudflow_connection by specifying the delete operation.

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

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

The description implies when to use the tool (to delete a connection) but does not explicitly state usage context or when alternatives (e.g., update or list) are more appropriate. It mentions a 409 error if referenced, which provides some guidance on a constraint, but lacks explicit when-to-use or when-not-to-use instructions.

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?

Beyond the annotations (readOnlyHint=false, destructiveHint=true), the description reveals idempotency ('Repeating the request is idempotent'), the resulting unassigned state, and the permission requirement. No contradiction with annotations; the destructive hint aligns with the delete semantics.

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

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

Five sentences, each carrying distinct information (action, result, preconditions, idempotency, permission). The opening 'Manage country-based access...' sentence is generic framing that adds little, but everything else earns its place and the core action is front-loaded in the second sentence.

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 destructive, hierarchy-sensitive operation, the description covers semantics, resulting state, preconditions, idempotency, and authorization. The only real gap is error behavior when preconditions fail (e.g., a non-root caller), and with no output schema, the return value is unspecified.

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

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

Schema description coverage is only 33%: only customerContext is documented in the schema. The description indirectly constrains targetCustomerId by stating the target must be the root or a child customer, but it never names the parameters explicitly, and X-Tenant-Id receives no semantics beyond its self-explanatory 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?

States a specific verb ('Clears') with the resource ('the geographic scope') and the resulting state ('leaving it unassigned'), making the action unambiguous. It is naturally distinguished from siblings like update_customer_geographic_access_scope and get_customer_geographic_access_scope, and from delete_user_geographic_access_scope by resource type.

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 concrete preconditions: the authenticated tenant must be the hierarchy root, the target must be that root or a child customer, and the UsersManager permission is required. It stops short of a 5 because it never explicitly names alternatives for setting or reading the scope (e.g., update_customer_geographic_access_scope).

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?

Annotations already indicate destructiveness. The description adds the permission requirement, but does not disclose additional behavioral traits like irreversibility or effect on active themes.

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

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

A single, front-loaded sentence with no filler words: verb, object, and permission requirement 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 covers the basic action and permission but lacks details on success/error responses, cascading effects, or validation, which would be helpful for a delete tool without an output schema.

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

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

With 50% schema description coverage, the description adds no new meaning to the 'id' parameter beyond stating it's the identifier. The 'customerContext' is already described in 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 'Deletes' and the resource 'custom theme specified by the Id', distinguishing it from sibling tools like create_custom_theme or update_theme.

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 mentions a required permission but does not explicitly guide when to use this tool vs alternatives (e.g., update_theme). Usage is implied but not 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?

The description is misleading by starting with 'Ingest...' which conflicts with the delete action. Annotations correctly mark destructiveHint: true, but the description adds confusion instead of clarity. No mention of consequences (e.g., irreversible deletion) beyond what annotations already indicate.

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 sentences, but the first sentence is irrelevant and misleading. The structure is not concise because it includes unnecessary information (ingestion) that harms clarity.

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

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

Given the tool is destructive, has no output schema, and one parameter lacks description, the description is critically incomplete. It fails to mention that deletion is permanent, error conditions, or any required preconditions.

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

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

Schema description coverage is 50% (only customerContext has a description). The tool description does not explain the 'name' parameter at all, leaving ambiguity about what name refers to (dataset ID? name string?). The description adds no 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 starts with 'Ingest third-party cost...' which suggests a create/ingest action, then contradicts with 'Deletes a specific DataHub dataset.' The purpose is vague and inconsistent, and it does not distinguish from sibling tools like 'delete_datahub_datasets' (plural).

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

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

No guidance on when to use this tool vs alternatives. No prerequisites (e.g., dataset must exist) or context for deletion. Sibling tools include delete_datahub_datasets, but no differentiation is 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?

Annotations already indicate destructiveHint: true. The description adds that it deletes 'all their associated data,' which clarifies the scope. However, it does not mention irreversibility, dependencies, or required 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 first sentence about ingestion is irrelevant and wastes space, making the description less concise than it could be. The second sentence is clear but could be more direct.

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 destructive bulk operation, the description lacks details on recovery, prerequisites, or differentiation from singular delete. It misses context needed for safe 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 coverage is 100%, so the parameters are fully documented. The description adds no additional 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 states 'Deletes one or more DataHub datasets and all their associated data,' which clearly identifies the action and resource. However, the first sentence about ingestion is misleading and irrelevant for a delete tool, reducing clarity.

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 like the sibling 'delete_datahub_dataset' (singular). There is no mention of prerequisites 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?

Description adds the important constraint that eventIds and time ranges are mutually exclusive, which is not in the schema. Annotations already indicate destructive and open-world behavior, so the bar is lower. However, it does not disclose irreversibility or data affected beyond filters.

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

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

The description is short but includes an irrelevant first sentence about ingestion, which is misleading and wastes space. The key deletion behavior and filter constraint are present, but the opening sentence should be removed for clarity.

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

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

For a destructive tool with no output schema, the description is incomplete. It does not mention post-deletion behavior, response format, required permissions, or safety warnings. The filter constraint is useful but insufficient for an agent to fully understand the tool's impact.

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 value by explaining that eventIds and time ranges are mutually exclusive, which clarifies parameter interaction beyond the schema. Schema coverage is high (80%), but this constraint is not in schema descriptions, so the description compensates well.

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 'Deletes specific events using filters', which aligns with the tool name. However, the first sentence about ingestion is misleading and could confuse the agent about the primary action. The distinction from sibling delete tools is implicit via the 'datahub_events’ context, but not explicit.

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

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

No guidance is provided on when to use this tool versus alternatives like delete_datahub_dataset or others. The only usage hint is the mutual exclusivity of filters, but no context on when deletion is appropriate 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?

Annotations already indicate destructiveHint=true. The description adds that nested folders will be deleted and reports/allocations are moved to root, going beyond annotations. It does not discuss permissions or reversibility, but the destructive behavior is clearly 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 three sentences: one for context, one for the action, and one for consequences. It is efficient and front-loaded with the core purpose.

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 what the tool does and its key side effects for a destructive operation without output schema. It does not specify error conditions or permission requirements, but the core behavior is sufficiently explained.

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 two parameters: 'id' (required, no description) and 'customerContext' (with description). Schema description coverage is 50%. The description does not mention either parameter, so it adds no value beyond the schema for parameter understanding.

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 deletes a folder, and distinguishes it from sibling tools like create_folder or update_folder by specifying the deletion effect and consequences (nested folders deleted, contents moved to root).

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 explains what happens when the tool is used (nested folders deleted, reports/allocations moved to root), providing clear context. It does not explicitly state when not to use it or mention alternatives, but the effect is well-described.

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?

Annotations already indicate destructive behavior, and the description adds important behavioral constraints beyond that: ownership by the authenticated tenant, the inability to delete assigned regions, and the permission requirement. No contradiction with the readOnlyHint/destructiveHint annotations.

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?

Four short sentences, each adding a distinct piece of information: domain context, action, constraint, and permission. The description is front-loaded and has 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 destructive tool with one required parameter and no output schema, the description covers the critical operational constraints: ownership, assignment state, and required permission. It does not mention return behavior or error cases, but these are less critical given the destructive annotation and the simplicity of the operation.

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

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

Schema description coverage is only 33%, and the tool description does not compensate. The required customRegionId is not explicitly described as the target region identifier, and X-Tenant-Id is left entirely unexplained. Only customerContext benefits from a schema-level description.

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

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

The description clearly states the tool deletes a custom region, naming the specific resource and action. It also distinguishes itself from sibling create/update/list tools by emphasizing deletion and the ownership/assignment constraints.

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

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

The description gives clear conditions for use: the region must be owned by the authenticated tenant, cannot be assigned, and requires the UsersManager permission. It does not explicitly name alternative tools for other operations, but the context is sufficient for an agent to choose this over similar geographic access 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?

Annotations already indicate destructive behavior. Description adds the permanence of deletion and the scope (associated results) and the public API restriction. No contradiction. Provides useful context beyond structured fields.

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

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

Three sentences, each earning its place: context, action, constraint. No superfluous text. Front-loaded with key information.

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

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

For a destructive action with annotations, the description covers key aspects (permanence, scope, constraint). Could mention authorization or failure behavior but overall sufficient.

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

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

Schema coverage is low (33%). The description indirectly explains sourceID via the public API constraint but does not describe insightKey or customerContext. Without description, agent must infer from schema 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?

Description clearly states it permanently deletes a single insight and associated resource results. It differentiates from sibling 'delete_insight_results' by specifying 'single insight' and adds a constraint (only public API insights).

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?

Implies use for single insight deletion and mentions the public API constraint, but does not explicitly compare to 'delete_insight_results' (plural) or provide alternative guidance. No 'when not to use' mentioned.

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

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

Adds behavioral context beyond the annotations: specifies that it removes the insight and all associated resource results. Annotations already indicate destructiveness, but description enriches with scope of deletion.

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?

Contains a generic first sentence that adds little value. The core action and alternative are clear, but the description could be more direct without the introductory phrase.

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?

Missing important context: no mention of what 'batch source' is, no sourceID parameter, no details on idempotency, errors, or return values. For a destructive operation with no output schema, more completeness is needed.

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 50% schema coverage and no description for insightKey, the description fails to add meaning beyond the schema. Only customerContext is described in schema, not in description.

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

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

The description clearly states it deletes all insights matching a key from the batch source, and distinguishes from the sibling tool delete_insight_result by mentioning single-insight deletion alternative.

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

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

Provides explicit guidance to use the alternative endpoint for single-insight deletion, implying this is for batch deletion, but does not elaborate on when to avoid using 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?

Annotations already indicate destructiveHint=true and readOnlyHint=false, so the description's mention of 'deletes' aligns but adds no new behavioral context. No additional traits (e.g., permissions, side effects) 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?

Two sentences, but the first sentence is verbose and introduces irrelevant functionality ('Create and manage'). The second sentence is clear. Could be trimmed to focus solely on deletion.

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?

As a destructive tool, the description lacks details on consequences (e.g., cascade effects on label assignments), return values, or required permissions. No output schema exists, so more context 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 coverage is 50% (only customerContext has description). The tool description does not describe the 'id' parameter or add meaning beyond the schema. It misses the opportunity to clarify that 'id' likely refers to the label's unique identifier.

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 'Deletes the label specified by the Id' which clarifies the delete action, but the opening phrase 'Create and manage labels' is misleading and suggests a broader purpose. The tool name 'delete_label' reinforces the delete function, but the description's first sentence conflicts.

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 like create_label or update_label. The description does not specify prerequisites, when not to use, or context for deletion.

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?

Annotations already indicate destructiveHint=true and readOnlyHint=false, consistent with deletion. The description adds no further behavioral context (e.g., whether deletion is permanent, cascading effects, or required 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 two sentences but includes a superfluous first sentence about managing and getting reports, which is irrelevant to deletion. Could be condensed to a single clear sentence.

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 delete tool with two parameters and no output schema, the description is adequate but marred by the misleading first clause. Missing details on prerequisites or effects, but not critically incomplete given the tool's straightforward 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?

With 50% schema description coverage, the description does not compensate. It fails to explain the 'id' parameter or clarify the purpose of 'customerContext,' which already has a good schema description. The description adds no 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 states the tool 'Deletes the specified Cloud Analytics report,' clearly identifying the action and resource. However, the first sentence about 'Manage Cloud Analytics reports and get reports data' is misleading and suggests broader functionality not supported.

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

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

No guidance on when to use this tool versus other delete or report management tools. Among siblings, there are many delete operations and report-specific tools (create_report, update_report, list_reports), but no distinctions 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?

Annotations already indicate destructiveHint=true, so the description's 'Deletes a user' is consistent. However, the description adds no extra behavioral context (e.g., irreversibility, permission requirements, cascading effects). It meets the minimum bar given the annotation.

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 has two sentences, the first being generic ('Manage users who have access to the DoiT platform.') which adds little value. The second sentence is direct. It could be more concise by removing the first sentence.

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 destructive operation with no output schema, the description is too sparse. It does not mention the outcome (e.g., confirmation, return status), whether the deletion is permanent, or any effects on related data. It lacks completeness for safe 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?

With only 50% schema description coverage, the description does not explain the parameters at all. The 'customerContext' parameter is described in the schema, but the required 'id' parameter lacks any description in both schema and tool description. The description adds no 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 that the tool deletes a user, which aligns with the tool name 'delete_user'. It distinguishes from sibling user tools like invite_user, update_user, and validate_user by explicitly using 'Deletes a user'.

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, such as when a user should be removed versus disabled, or any prerequisites like ownership of the user. It only states the action without context.

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

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

Annotations already mark the tool as destructive, and the description adds useful detail by specifying that the scope is cleared and left unassigned, that the operation is idempotent, and that specific hierarchy and permission conditions must hold. This goes beyond the annotation signals without contradicting them.

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 each sentence adds useful information: context, action, hierarchy prerequisites, idempotency, and permission. The opening 'Manage country-based access...' sentence is somewhat broad, but it is not redundant and the rest is tightly 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?

For a destructive tool with no output schema, the description adequately covers the effect, preconditions, idempotency, and required permission. It does not elaborate on tenant-header parameters, but the schema already documents customerContext and the core invocation requirements are 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?

Schema description coverage is only 25%, so the description needed to compensate, but it only indirectly addresses targetCustomerId and userId through 'target customer' and 'user'. It does not explain X-Tenant-Id or fully clarify how the authenticated-tenant constraint maps to parameters, leaving significant param semantics undocumented.

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

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

The description uses a specific verb ('Clears') and resource ('geographic scope assigned to a user'), which clearly distinguishes this tool from sibling delete tools like delete_customer_geographic_access_scope. The sentence 'leaving it unassigned' clarifies the resulting state, making the tool's 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 strong usage context by stating that the authenticated tenant must be the hierarchy root, the target must be the root or a child customer, and the UsersManager permission is required. It does not explicitly name alternatives or when-not conditions, but the constraints make intended invocation 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, the description needs to disclose behavioral traits. It states the tool marks the suggestion as dismissed and removes it from the pending list, which is useful. However, it does not mention what happens after dismissal (e.g., can it be undone? any side effects?) or the need for linking to a budget for acceptance, which is partially covered but not fully.

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 core purpose. It wastes no words, but could be more direct (the 'or dismiss' part might cause confusion). Overall, it's efficient but slightly ambiguous.

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 tool, the description covers the basic action and outcome but leaves gaps: it doesn't explicitly state the input parameter (id) semantics, doesn't mention if acceptance requires a budget link (suggested but not detailed), and doesn't clarify the relationship with accept_budget_suggestion. It's sufficient for a simple tool but not fully 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 schema is minimal (only 'id' required, no descriptions), and the description does not explain what 'id' represents or how to obtain it boundary. With schema_coverage being low (no property descriptions), the description fails to compensate by clarifying the parameter's meaning or format.

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 purpose: handling AI-generated budget recommendations by accepting or dismissing, with a specific focus on dismissing and marking as no longer pending. It distinguishes from siblings like accept_budget_suggestion, but it slightly conflates the action by mentioning both accept and dismiss, though the primary verb (dismiss) is 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?

It implies the tool is used for dismiss actions but mentions 'accept' as an option without explicitly directing to accept_budget_suggestion. It lacks explicit when-to-use/when-not-to-use guidance and does not clearly differentiate from the accept sibling beyond the tool 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?

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false. The description adds context about exporting 'full content' and 'all components and export metadata', but does not disclose additional behavioral traits beyond annotations.

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 wasted words. The first sentence provides context, the second states the action. It is front-loaded and 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?

Given no output schema and the complexity of exporting a diagram layer, the description is adequate but lacks details on the output format structure, what 'full content' entails, and how it relates to other diagram tools. Not fully 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 50% (customerContext described, id not). The description does not clarify what the id parameter represents (presumably the diagram layer ID) or provide meaning beyond the schema. No parameter details are added.

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 'Exports the full content of a diagram layer as a structured JSON document', specifying a specific verb (exports), resource (diagram layer), and output format. This distinguishes it from sibling tools like get_cloud_diagram_components.

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 for full layer export but does not explicitly state when to use this tool versus alternatives like get_cloud_diagram_components or get_cloud_diagram_layer_snapshot. No when-not or alternative guidance is 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?

Even with readOnlyHint=true and destructiveHint=false already present, the description adds substantial behavioral context: transitive subflow inclusion, tenant-neutral/credential-free output, rebinding of tenant-scoped references as named requirements, unsupported policy/Slack references, and explicit exclusions (credentials, tenant IDs, schedules, execution state). This goes far beyond annotations.

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 opening 'Manage CloudFlow.' is generic filler, but the remaining three sentences are information-dense and logically organized: what is serialized, how tenant references are handled, and what is excluded. The length is justified by 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?

The description is largely complete for a read-only export tool given no output schema: it specifies output type, portability constraints, and limitations. The main gap is the undocumented includeVariableValues parameter, and the description does not state how the bundle is returned or what happens on missing flows, but these are secondary.

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

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

Schema coverage is only 33%, and the description does not explain includeVariableValues or clarify the exact meaning/format of flowId. It provides only an indirect hint that 'flow' refers to flowId. The description does not compensate for the undocumented parameters, leaving a meaningful gap for agents.

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

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

The description names a specific operation (serializes a CloudFlow flow plus referenced subflows) and a concrete output (a tenant-neutral, credential-free JSON bundle). It distinguishes the tool from its import sibling by explicitly mentioning the import operation as the counterpart, and from list/management tools by focusing on export/transfer behavior.

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 makes the purpose clear and references the import operation, which implies a migration/backup use case, but it never explicitly states when to use this tool instead of alternatives such as list_cloudflows, build_cloud_flow, or export_cloud_diagram_json. No exclusions or when-not-to-use guidance is 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?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is clear. The description adds that it returns matching diagram files but does not elaborate on behavior like pagination or sorting. Given annotations cover the main safety concerns, a score of 3 is appropriate.

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 concise: three sentences covering when to use, what it returns, and negative usage with alternatives. Every word is essential, and the structure is front-loaded.

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

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

For a simple find tool with one parameter and no output schema, the description covers the essential: purpose, return type, and negative guidance. It could specify the return format more precisely (e.g., list of file paths), but it is mostly 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?

The input schema already fully describes the 'resources' parameter (array of resource IDs). The description adds no additional meaning beyond the schema. With 100% schema coverage, baseline is 3, and the description does not enhance it further.

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 specifies the tool's purpose: finding architecture/cloud infrastructure diagrams. It uses a specific verb ('find') and resource ('cloud diagrams'), and distinguishes it from siblings by stating what it does not cover (cost analysis, incidents) with explicit tool names.

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 guidance: when to use (user wants diagrams), and when not to use (cost analysis -> run_query, incidents -> get_cloud_incidents). This directly helps an agent decide between sibling 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?

Annotations already declare readOnlyHint=true and destructiveHint=false. Description adds useful context about sentinel 'default' value and return type. No contradictions.

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 sentences, front-loaded with usage condition, no wasted words. Perfectly concise.

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

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

Fully explains purpose, usage, and return value. No missing context considering zero parameters and simple behavior.

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?

No parameters, schema coverage 100%. Description correctly implies no inputs needed. Baseline 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?

Clearly states it returns the active theme id for user's account, and explains the sentinel 'default'. Distinguishes from siblings by explicitly saying not to use for listing themes or fetching a specific theme.

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 says when to use (user wants active theme) and when not to use (list_themes, get_theme), naming alternatives.

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

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=true, indicating a safe read operation. The description adds behavioral context: accepts partial name (case-insensitive) and warns against misuse, but doesn't contradict annotations.

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

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

Three sentences, no fluff. Front-loaded with core purpose, then acceptance criteria, then exclusions. Every sentence is essential.

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 no output schema and low complexity, the description is complete. It specifies inputs (ID or name), explains how they work (partial/case-insensitive), and clarifies scope (specific alert only, not 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?

Input schema has 100% coverage, with descriptions for both parameters. The description adds that the 'name' parameter is a 'partial name match (case-insensitive)' and explains it is used 'when ID is unknown', providing context 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's purpose: 'view the details of a specific cost alert'. It distinguishes from sibling tools by explicitly saying not to use for listing all alerts (list_alerts) or for anomalies (get_anomalies).

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 when-to-use ('when the user wants to view the details of a specific cost alert') and when-not-to-use ('Do NOT use this for listing all alerts... or anomalies'). It also references specific sibling tools as alternatives.

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

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

Annotations already indicate readOnlyHint=true. Description adds that it accepts ID or partial name (case-insensitive), providing useful behavioral context beyond annotations.

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 sentences, front-loaded with purpose, 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 read operation with clear annotations and schema, the description is complete and provides all necessary 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?

Schema coverage is 100%, so baseline 3. Description adds minor context (one of the two parameters needed, partial name is case-insensitive) but doesn't significantly enrich beyond 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 explicitly states the verb 'view details' and resource 'specific cost allocation', and distinguishes from siblings like list_allocations and run_query.

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?

Clearly explains when to use (view specific allocation) and when not to (listing, queries), naming 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?

Annotations already provide readOnlyHint=true. The description adds that it accepts ID or partial content match (case-insensitive), but does not discuss error handling or return format; still adequate for a simple read tool.

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

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

Two concise sentences that front-load the main purpose and include quick exclusions. No unnecessary 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?

Covers purpose, usage boundaries, and parameter behavior. Does not specify return format or error scenarios, but sufficient for the tool's simplicity given annotations.

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

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

Schema coverage is 100% and schema descriptions are clear. The description adds context about using one parameter over the other, but this is marginal beyond 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 'view details' and resource 'specific annotation', distinguishing it from sibling tools like list_annotations and list_labels.

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 tells when to use (user wants to view details of a specific annotation) and when not to use (listing all annotations or labels), with named alternatives (list_annotations, list_labels).

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