Sleepwalker

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

Annotations provide basic hints (not readOnly, not idempotent, not destructive). The description adds valuable context: it queues work, returns quickly with run_id, instructs to poll for completion, and mentions billing fields on response. This goes beyond annotation details without 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?

The description is five sentences, each contributing essential information. It front-loads the main action, then provides usage notes. No filler or redundancy.

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

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

Given the output schema exists (not shown), the description need not explain return values. It covers core behavior, usage constraints, polling advice, and billing context. It lacks error handling or prerequisites but is largely complete for a tool with 6 parameters and rich 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%, so baseline is 3. The description repeats the url/test_id choice and mentions idempotency_key's purpose, but does not add new meaning for country, language, or analysis_depth beyond the schema descriptions. Marginal added value over 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 queues a persisted Content Intelligence run, specifying input options (url or test_id). It distinguishes the action from sibling tools like create_sleepwalker_visibility_run but does not explicitly differentiate beyond the core function.

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

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

The description advises using only after explicit user confirmation and recommends polling status to avoid duplicates. However, it does not specify when not to use this tool or mention alternatives, leaving usage context implied rather than explicit.

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

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

Description discloses that the tool starts queued work, returns quickly with a run_id, and requires polling for terminal state. It also notes that credit fields are included in the response. This adds significant behavioral context beyond the annotations (readOnlyHint=false, idempotentHint=false).

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?

Description is five sentences, each earning its place: purpose, when to use, polling guidance, platform aliases, and credit fields. No unnecessary words, front-loaded with key action.

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 9 parameters, 2 required, and an output schema (not shown), the description covers async behavior, idempotency, platform aliases, and response credits. It could mention that 'url' and 'target_entity' are required, but those are in the schema. Overall complete for agent decision-making.

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 clarifying platform aliases (e.g., 'openai/ChatGPT, grok, gemini') and explaining the 'probes' parameter as 'Advanced explicit prompt and platform objects.' This supplements the schema without redundancy.

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 explicitly states 'Queue a saved AI Visibility run from prompts x platforms or explicit probes.' The verb 'queue' and resource 'visibility run' are specific and distinguish it from sibling tools like 'create_sleepwalker_content_run' and 'suggest_sleepwalker_visibility_prompts'.

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?

Clear usage guidance: 'Use this when the user wants reportable probe results, not just prompt ideas.' Also advises polling 'get_sleepwalker_visibility_run_status' to avoid duplicate runs, and explicitly mentions idempotency_key for retries.

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 non-readOnly and openWorldHint. The description adds that it runs extraction/serialization and returns data only, but does not clarify side effects (e.g., whether it creates runs or persists data). Minimal extra 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?

The description is concise with two sentences: first states the core action, second explains internal process and output. No unnecessary words, and it is front-loaded with the main 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?

Given the existence of an output schema and comprehensive annotations, the description is largely complete. However, it lacks guidance on when to use this tool versus similar siblings, which would improve completeness.

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

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

Schema description coverage is 100% with detailed parameter descriptions (e.g., URL, country, language, extraction mode). The tool description adds no additional parameter meaning, so baseline score of 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: 'Find relevant content trends for a URL'. It also specifies that it runs extraction and serialization internally and returns compact industry, trend, and citation data, which distinguishes it from siblings like serialize_sleepwalker_page_content.

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 by mentioning internal integration, but it does not explicitly state when to use this tool over alternatives like create_sleepwalker_content_run or serialize_sleepwalker_page_content. No when-not or exclusion criteria are provided.

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

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so the description does not need to repeat those. The description adds the context of 'across recent runs' and 'recurring', which is consistent. No behavioral traits beyond what annotations provide are disclosed, but that is acceptable since annotations cover the key aspects.

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

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

The description is a single sentence that immediately states the verb and resource. It is front-loaded with the core action and context, with no unnecessary words. Every word earns its place, making it concise and effective.

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 an output schema (so return values are already documented), the description covers the essential function: finding recurring recommendations across recent runs for a known test. It does not explain the minimum frequency threshold, but that is in the parameter schema. The complexity is moderate, and the description is sufficient for an agent to understand what the tool does.

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% description coverage, meaning each parameter (runs, test_id, min_frequency) already has a description. The tool's description does not add additional meaning to the parameters beyond what the schema provides. Based on the guidelines, baseline for high schema coverage is 3, so this score 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: 'Find recurring Content Intelligence recommendations across recent runs for a known test.' It specifies the verb 'find', the resource 'recurring Content Intelligence recommendations', and the scope 'across recent runs for a known test'. This distinguishes it from siblings like get_sleepwalker_test_results which return all results, not just consistent ones.

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

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

The description implies usage when looking for recurring recommendations across runs, but it does not explicitly state when to use this tool versus alternatives. There is no mention of exclusions or specific scenarios. Given the sibling list includes many similar get/list tools, more guidance would be helpful, but the purpose itself provides some implicit 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 indicate read-only and idempotent behavior. The description adds value by explaining the polling pattern and when to include the result payload, aligning with annotations without 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?

The description is concise with two front-loaded sentences. Each sentence provides essential information without unnecessary fluff.

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

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

Given the tool's low complexity, good schema, annotations, and output schema, the description is largely complete. It covers main purpose, polling usage, and result inclusion. Minor improvements could include explicit differentiation from sibling tools for result retrieval.

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 documents both parameters well. The description rephrases the guidance for include_result but does not add significant new meaning beyond what the schema descriptions provide.

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 reads status and optional full result for a persisted direct-URL Content Intelligence run. The verb 'Read' and resource 'status and optional full result' are specific, and the mention of 'Content Intelligence run' helps distinguish from similar sibling tools like get_sleepwalker_visibility_run_status.

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 implicit guidance by indicating to poll while queued or running and to set include_result only after completion. However, it does not explicitly compare to alternatives like get_sleepwalker_run_result or state when not to use this tool.

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

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

Annotations already provide readOnlyHint, idempotentHint, destructiveHint. The description adds context about 'capped' response and pagination via offset/max_chars, which is useful but not extensive. No contradictions 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 concise with two sentences. The first clearly states the purpose, and the second provides essential parameter usage guidance. No redundant or wasteful 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?

Given the tool has 7 parameters and an existing output schema, the description covers the core purpose and parameter selection logic. It could be more complete by explaining the nature of 'prompt response' or the 'capped' behavior, but overall sufficient for understanding tool 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 100% schema description coverage, the schema already documents each parameter. The description adds significant value by explaining the selection logic (e.g., use result_index or prompt_index, or platform + prompt_index), clarifying parameter relationships 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 fetches one capped AI Visibility prompt response, specifying the resource and action. However, it does not explicitly differentiate from sibling tools like get_sleepwalker_run_result, leaving some ambiguity about when to use this specific 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 guidance on parameter usage (result_index, prompt_index, platform) but does not explain when to choose this tool over alternatives like get_sleepwalker_run_result or get_sleepwalker_summaries. No when-not-to-use or context for comparison.

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 read-only, idempotent, non-destructive. Description adds that it searches owned tests and fetches latest UI-visible runs, which is valuable behavioral context beyond annotations. No 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?

Single sentence, front-loaded, no wasted words. Efficiently communicates core function.

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

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

Covers essential purpose. With full schema and output schema (signal shows output schema exists), description is adequate. Minor omission: behavior when no results not mentioned, but not critical.

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

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

Schema has 100% coverage; description adds context about 'owned' tests and 'UI-visible' runs, supplementing parameter descriptions. Adds meaning beyond the schema.

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

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

Clearly states 'Find owned CI/AC tests by URL and fetch their latest UI-visible runs.' Provides specific verb (Find) and resource (owned CI/AC tests) and action (fetch runs). Distinguishes from sibling tools that create runs, get status, etc.

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 usage: when you have a URL and need to find tests and latest runs. But no explicit guidance on when to use vs alternatives or when not to use. Context is provided but not extensive.

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 idempotentHint=true. The description adds context that the result is 'full structured' and that AC raw responses are not included, which is useful. 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, no wasted words. The main purpose is stated first, and additional guidance is provided concisely.

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

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

Given the presence of an output schema (though not shown), the description's mention of 'full structured' is adequate. It also clarifies what is not included (raw AC responses). The tool is simple with one parameter and safe 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?

The schema has 100% coverage with a clear description for run_id. The description does not add additional semantics beyond that, but the schema is sufficient. 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 uses a specific verb ('Fetch') and identifies the resource ('one full structured CI/AC run'). It distinguishes from the sibling tool get_sleepwalker_prompt_response by noting that AC raw responses are fetched separately.

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 mentions when to use the sibling tool (for AC raw responses), implying that this tool is for the structured run result. However, it does not provide guidance on when to use this vs. other siblings like get_sleepwalker_content_run_status or get_sleepwalker_consistent_recommendations.

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 the tool as read-only, idempotent, and non-destructive, so the description is not required to reiterate those. It adds useful context about the summary nature and date range, but does not disclose pagination, maximum results, or empty result behavior. This is acceptable given the annotations' completeness.

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

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

The description is a single, front-loaded sentence that conveys the core purpose efficiently without extraneous words. 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 5 optional parameters, rich schema, and output schema (present but not shown), the description suffices for an initial scan tool. It could mention that it returns summaries (not full data) and the abbreviation 'CI/AC' might be clarified, but overall it is sufficiently complete for agent understanding.

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?

All 5 parameters have exhaustive descriptions in the schema (100% coverage), so the description adds minimal value beyond restating the date lookback. Baseline of 3 is appropriate as the schema carries the semantic load.

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 retrieves compact CI/AC run summaries for a date range, positioning it as a lightweight overview tool distinct from sibling tools that provide full run details or specific analyses. The verb 'scan' and the phrase 'before drilling into full runs' effectively signal its role.

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 implicitly advises using this tool for initial exploration before diving into more detailed tools, but it does not explicitly exclude scenarios or name specific alternatives. The guidance is clear enough for most agents but lacks explicit boundary conditions.

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 signal read-only and idempotent behavior. The description adds that the tool returns 'compact latest run history', which provides temporal context and format hint. 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, no redundancy, front-loaded purpose, and efficient reference to sibling tool.

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

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

With only 2 parameters, rich annotations, and an output schema present, the description fully covers necessary context: what the tool does, when to use it, and output format hint.

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% description coverage for both parameters (test_id and limit). The tool description adds no extra parameter-specific context beyond what the schema provides, so baseline score of 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 verb 'Fetch' and the resource 'compact latest run history for a known test'. It distinguishes from the sibling tool get_sleepwalker_run_result, which provides full details.

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 advises to use get_sleepwalker_run_result for full details, providing clear when-to-use and alternative guidance.

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

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description adds value by explaining polling behavior and when to retrieve results. However, it could mention potential rate limits or expected polling intervals for better 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 short sentences that front-load the purpose and immediately provide actionable guidance. Every word contributes meaning without redundancy.

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

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

Given the presence of an output schema (context signal: Has output schema: true), the description sufficiently covers usage context. Could potentially mention any limitations on polling frequency, but overall complete for a status-check 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 coverage is 100% with descriptions for all three parameters. The description adds usage context for include_results (prefer false while polling), which enhances semantic understanding beyond the 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?

The description clearly states 'Read status, probe progress, and optional results for a queued infrastructure AI Visibility run.' It uses a specific verb ('Read') and identifies the resource ('AI Visibility run status'), and distinguishes from sibling tools like get_sleepwalker_content_run_status by targeting visibility runs specifically.

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 guidance: 'Poll compact status while queued or running. Set include_results only after completion or when the user explicitly needs full response and citation data.' This tells when to use the tool (polling) and when to set parameters, effectively differentiating from 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 provide readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds 'persisted direct-URL' context, but no additional behavioral details like pagination or rate limits. Description 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?

A single, front-loaded sentence of 14 words with no fluff. Every word contributes to stating the tool's purpose efficiently.

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

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

Given rich annotations and an output schema, the description is largely sufficient. It lacks details on ordering or default filters but is adequate for a simple list 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 coverage is 100% and both parameters have clear descriptions. The tool description adds no new information beyond what the schema already provides, meeting the 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 verb 'List' and resource 'persisted direct-URL Content Intelligence runs created through Sleepwalker infrastructure actions,' distinguishing it from sibling tools like list_sleepwalker_visibility_runs by specifying the run 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?

No explicit when-to-use or when-not-to-use guidance is provided. The purpose is implied, but the description does not differentiate from alternatives like get_sleepwalker_content_run_status or suggest filters.

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 the tool as safe and idempotent. The description adds context about user-specific scoping ('authenticated user's'), which is valuable beyond annotations. 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?

The description is a single, efficient sentence of 12 words, with no redundancy. 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?

The tool is simple with 3 optional params and an output schema. The description covers the core purpose and scope, though it could mention return type or pagination but these are covered by 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 coverage is 100%, so the baseline is 3. The description adds minimal parameter insight beyond the schema, only implicitly linking to test_type values.

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

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

The description clearly states the tool lists only 'Content Intelligence and AI Citations' tests for the authenticated user, with a specific verb and resource. The title and name align, and it distinguishes from sibling tools that list runs.

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 listing tests (as opposed to runs from siblings), but no explicit when-to-use or when-not-to-use guidance is provided. It is clear in 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 declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds that runs are 'for the authenticated user', which is implicit. It does not contradict annotations but provides minimal additional behavioral context.

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

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

Single sentence, front-loaded with key action and resource, 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 presence of an output schema and full parameter coverage, the description is adequate but lacks important details: it misleads by stating 'queued' while the tool lists all statuses by default, and does not clarify the default behavior or the effect of the `status` parameter.

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 both parameters fully described. The description does not add extra meaning beyond the schema, so baseline score of 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 verb 'List' and resource 'infrastructure AI Visibility runs' are clear and specific to the tool. It distinguishes from sibling `list_sleepwalker_content_runs`. However, the qualifier 'queued' is inaccurate as the tool can list runs of any status via the optional `status` parameter.

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 (e.g., `list_sleepwalker_content_runs`). The description does not mention prerequisites, recommended status filters, 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?

Annotations indicate readOnlyHint=false and destructiveHint=false, so the tool is neither read-only nor destructive. The description adds behavioral context: it does not save a run (so no persistent state), and omitting trends slows performance. No contradiction with annotations; description provides useful behavior 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 long, with the first sentence stating the purpose and the second providing usage guidance. No unnecessary words; every sentence earns its place.

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

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

Given 6 parameters (1 required), 100% schema coverage, and an output schema (not shown but indicated as present), the description covers the core action, optimal usage with trends, and distinguishes from sibling tools. No gaps remain; it is complete for the tool's complexity.

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

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

Schema description coverage is 100%, so baseline is 3. The description adds value by advising to pass 'compact trends from discover_sleepwalker_content_trends', which clarifies the source and optimization for the trends parameter. This goes beyond the schema's description and helps agents understand parameter usage.

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: 'Score a URL with Content Intelligence without saving a run.' It uses a specific verb ('score') and resource ('URL with Content Intelligence'), and distinguishes itself from saving a run, which differentiates it from siblings like create_sleepwalker_content_run.

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: 'Prefer passing compact trends from discover_sleepwalker_content_trends; omitting trends makes Sleepwalker discover them first and can be slower.' It tells when to use trends and notes the alternative (omitting trends leads to slower discovery), offering clear context for when to use this tool vs. others.

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 transparency by stating the tool does not save a run, but annotations are incomplete (readOnlyHint=false, openWorldHint=true). It does not disclose authentication needs, rate limits, or whether it modifies any state beyond not saving a run, leaving behavioral 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 highly concise: one sentence with a clear core purpose and a negative list to differentiate. It is front-loaded and contains no superfluous 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 presence of an output schema and full parameter schema coverage, the description is fairly complete. It explains the tool's non-behaviors but could briefly state what the output contains (e.g., 'returns structured text content'). Still, it adequately covers the essential context for selection.

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 all parameters. The tool description adds no additional meaning to the parameters beyond what the schema provides, meeting the baseline of 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 clearly states the tool provides 'Sleepwalker's normalized page content view', which aligns with the name serialize. However, it could more explicitly state that it extracts and returns raw page content from a URL, making the purpose slightly ambiguous.

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

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

The description instructs 'Use this only when you need Sleepwalker's normalized page content view' and lists what it does not do (score, discover, suggest, save), effectively guiding the agent to alternatives like score_sleepwalker_content or discover_sleepwalker_content_trends. It lacks explicit when-not-to-use 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?

Annotations provide readOnlyHint=false and other hints, but the description adds critical context: it does not query or save, clarifying it is effectively read-only despite the hint. This is valuable beyond the 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 extremely concise with two sentences, no extraneous information, and the purpose is front-loaded in 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?

Given the tool's simplicity and the presence of an output schema, the description is complete: it states what it does, what it does not do, and implies its non-destructive nature. No gaps remain.

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 each parameter is already explained. The tool description does not add further parameter details beyond the schema, so baseline score of 3 applies.

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

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

The description clearly states it suggests AI visibility prompts for a URL, with a specific verb ('suggest') and resource ('prompts'). It explicitly distinguishes itself from other tools by noting it does not query or save, which differentiates it from siblings like 'create_sleepwalker_visibility_run'.

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 includes explicit usage guidance: 'Use this for prompt ideas only; it does not query AI platforms or save a visibility run.' This tells the agent when to use it and what it does not do, though it does not name alternative tools directly.

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