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

With no annotations provided, the description carries full burden but only mentions the return format ('as markdown') and basic operation. It omits critical behavioral details like error handling (e.g., for invalid slugs), performance aspects (e.g., response time), or authentication requirements, leaving significant gaps for a read operation.

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

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

The description is a single, well-structured sentence that front-loads key information (action, resource, method) and efficiently includes the return format without unnecessary details. Every word serves a clear purpose, making it highly 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?

For a simple read tool with one parameter and no output schema, the description covers basic purpose and return format. However, without annotations or output schema, it lacks completeness in areas like error cases or response structure, making it adequate but with gaps in behavioral 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 the schema fully documents the 'slug' parameter. The description adds no additional parameter semantics beyond implying the slug identifies the page, aligning with the baseline score when schema handles documentation adequately.

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 ('Retrieve'), resource ('full content of a documentation page'), and method ('by its slug or URL path'), with specific differentiation from sibling tools list_sections (which lists sections) and search_docs (which searches). It provides a complete purpose statement without redundancy.

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 suggests usage when needing full page content via slug/URL, contrasting with search_docs for broader searches. However, it lacks explicit guidance on when to use this versus list_sections or clear exclusions, such as for partial content retrieval.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the tool's function and usage context but lacks details on behavioral traits such as permissions needed, rate limits, pagination, or response format. The description doesn't contradict any annotations, but it's minimal in behavioral information beyond the basic operation.

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

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

The description is concise and well-structured, consisting of two sentences that efficiently convey the tool's purpose and usage guidelines without any wasted words. It's front-loaded with the core function and follows with practical advice, making it easy to understand quickly.

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

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

Given the tool's low complexity (1 optional parameter, no output schema, no annotations), the description is somewhat complete but has gaps. It explains what the tool does and when to use it, but lacks details on behavioral aspects like response format or error handling. Without annotations or output schema, the description should ideally provide more context, but it's 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?

The input schema has 100% description coverage, with the parameter 'section' documented as 'Filter to a specific section's children by section name.' The description doesn't add any additional meaning or details about parameters beyond what the schema provides. With high schema coverage, the baseline score is 3, as the description doesn't compensate but also doesn't detract.

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: 'List the documentation structure showing all sections and their page counts.' This specifies the verb ('List'), resource ('documentation structure'), and output details ('sections and their page counts'). However, it doesn't explicitly differentiate from sibling tools like 'get_page' or 'search_docs' beyond mentioning discovery before searching, which is implied but not direct comparison.

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

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

The description provides clear context for usage: 'Use this to discover what documentation is available before searching.' This indicates when to use the tool (for discovery prior to searching) and implies an alternative (use 'search_docs' after discovery). However, it doesn't explicitly state when not to use it or name the sibling tools as alternatives, keeping it from a perfect score.

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

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

With no annotations provided, the description carries the full burden. It discloses the tool returns a ranked list with excerpts, which is useful behavioral context. However, it lacks details on permissions, rate limits, error handling, or pagination, leaving gaps for a search tool.

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

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

The description is two sentences, front-loaded with the core purpose and efficiently adds return value details. Every sentence earns its place with zero waste, making it appropriately sized and well-structured.

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

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

Given the tool's moderate complexity (search with filtering), no annotations, and no output schema, the description is mostly complete but could improve by explaining the return format more (e.g., structure of results). It covers purpose and basic behavior adequately but lacks some operational details.

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

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

Schema description coverage is 100%, so the schema fully documents all parameters. The description adds no additional meaning beyond what the schema provides (e.g., it doesn't explain 'section' filtering nuances or 'limit' defaults beyond the schema). Baseline 3 is appropriate as the schema does the heavy lifting.

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 with a specific verb ('Search') and resource ('documentation'), and distinguishes it from sibling tools by specifying it returns ranked results with excerpts, unlike 'get_page' (likely retrieves a single page) and 'list_sections' (likely lists sections without search).

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 keyword/phrase-based searches, providing clear context. However, it does not explicitly state when to use this tool versus alternatives like 'get_page' or 'list_sections', or any exclusions (e.g., 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.