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

No annotations are provided, so the description carries the full burden. It mentions the tool's purpose and use cases but lacks details on behavioral traits such as error handling, response format, or any constraints like rate limits or authentication needs. This leaves gaps in understanding how the tool behaves beyond its basic function.

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

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

The description is appropriately sized and front-loaded, with two sentences that directly state the purpose and provide usage guidance without any wasted words. Each sentence adds value, making it efficient 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 (2 parameters, no output schema, no annotations), the description covers purpose and usage well but lacks details on behavioral aspects and output. Without annotations or an output schema, it should ideally provide more context on what to expect from the tool's response, leaving 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?

Schema description coverage is 100%, so the schema already documents both parameters ('project_path' and 'crate_name') with clear descriptions. The description does not add any additional meaning or context about the parameters beyond what the schema provides, resulting in a baseline score 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 specific action ('Get crate's main documentation page') and resource ('crate'), distinguishing it from sibling tools like 'list_symbols' and 'search_doc' by focusing on retrieving primary documentation rather than listing symbols or searching within documentation.

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 provides when to use this tool ('Useful for unresolved imports... or understanding crate features') with a concrete example ('e.g. use get_crate_doc when seeing 'unresolved import tokio::sync''), effectively guiding the agent on appropriate contexts without mentioning alternatives, which is sufficient for clear usage.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions what the tool shows (structs, enums, traits with paths), but doesn't cover critical aspects like whether it's read-only, safe, requires specific permissions, handles errors, or provides pagination/formatting details. For a tool with zero annotation coverage, this is a significant gap in 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 appropriately sized and front-loaded, with two sentences that efficiently convey purpose and usage. It avoids unnecessary details, though it could be slightly more structured (e.g., separating purpose from guidance). Overall, it's concise with minimal 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's complexity (2 parameters, no output schema, no annotations), the description is incomplete. It lacks information on behavioral traits (e.g., safety, error handling), output format, and explicit usage boundaries. Without annotations or an output schema, the description should do more to compensate, but it falls short.

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

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

The schema description coverage is 100%, with both parameters ('project_path' and 'crate_name') fully documented in the schema. The description doesn't add any parameter-specific details beyond what the schema provides, such as format examples or constraints. This meets the baseline for high schema coverage, but doesn't enhance 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's purpose with a specific verb ('List') and resource ('symbols in a crate'), and distinguishes the types of symbols included (structs, enums, traits with paths). However, it doesn't explicitly differentiate from sibling tools like 'get_crate_doc' or 'search_doc', which prevents 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?

The description provides implied usage guidance ('Use when implementing traits or exploring available types'), which gives some context for when to invoke the tool. However, it lacks explicit guidance on when not to use it or alternatives (e.g., compared to 'search_doc'), and doesn't mention prerequisites like needing a valid Rust project, leaving room for improvement.

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 mentions the tool's purpose and use cases but fails to describe key behavioral traits like whether it requires specific permissions, how results are returned (e.g., format, pagination), or any rate limits. This leaves significant gaps for an agent to understand how to invoke it effectively.

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 in two sentences: the first states the purpose, and the second provides usage context. There is no wasted text, and it is front-loaded with the core functionality. However, it could be slightly more efficient by integrating the use cases more seamlessly.

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 a search tool with 3 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral aspects (e.g., result format, error handling) and doesn't compensate for the absence of structured output information, making it insufficient for an agent to fully understand the tool's 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?

The input schema has 100% description coverage, providing clear details for all three parameters (project_path, crate_name, query). The description adds no additional parameter semantics beyond what the schema already states, such as examples of valid queries or constraints on crate names. With high schema coverage, the baseline score of 3 is appropriate as the schema handles 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: 'Search crate docs for specific features, error messages, or usage examples.' It specifies the verb ('Search') and resource ('crate docs'), and mentions the target content types. However, it doesn't explicitly differentiate from sibling tools like 'get_crate_doc' or 'list_symbols', which likely have related but distinct functions.

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 implied usage guidance by stating it 'Helps debug compilation issues or learn new APIs,' suggesting contexts where this tool is appropriate. However, it lacks explicit guidance on when to use this tool versus its siblings (e.g., 'get_crate_doc' and 'list_symbols'), such as comparing search functionality to direct documentation retrieval or symbol listing.

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