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 states the tool returns a 'JSON string containing a list of detailed location points,' which adds some context about the output format. However, it doesn't cover critical behavioral aspects such as error handling (e.g., invalid IDs), rate limits, authentication needs, or whether it's a read-only operation. For a tool with no annotations, this is insufficient.

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: the first sentence clearly states the purpose, followed by structured 'Args' and 'Returns' sections. There's no wasted text, and each part adds value. It could be slightly more concise by integrating the parameter explanation into the main sentence, but overall it's 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 the context: 1 parameter with 0% schema coverage, no annotations, but an output schema exists (implied by 'Returns' note). The description covers the basic purpose and parameter semantics adequately. However, it lacks details on behavioral traits (e.g., error cases) and usage guidelines relative to siblings. With an output schema, it doesn't need to explain return values deeply, but overall completeness is minimal viable with clear gaps.

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

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

The description adds meaningful semantics beyond the input schema: it explains that 'subject_id' is 'The Bangumi ID of the anime,' clarifying its purpose and format (an ID for anime). Since schema description coverage is 0% (no descriptions in schema properties), the description compensates well by providing this context, though it could elaborate more (e.g., where to find Bangumi IDs). With 1 parameter, this is 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: 'Get the detailed seichi junrei (anime pilgrimage) locations for a specific anime using its Bangumi ID.' It specifies the verb ('Get'), resource ('detailed seichi junrei locations'), and key identifier ('Bangumi ID'). However, it doesn't explicitly differentiate from sibling tools like 'get_anime_lite_info' or 'search_bangumi', which likely serve different purposes (lite info vs. 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 provides minimal usage guidance: it mentions using a 'Bangumi ID' for a 'specific anime,' implying this tool is for known anime IDs. However, it lacks explicit when-to-use rules, alternatives (e.g., when to use 'get_anime_lite_info' instead), or exclusions (e.g., not for searching by name). This leaves gaps in guiding the agent on tool selection among siblings.

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 that the tool returns 'JSON string containing the lite info, including `litePoints` which are the top 10 iconic locations,' which adds some context about the return format and content. However, it lacks details on error handling, rate limits, authentication needs, or whether this is a read-only operation (though 'Get' implies reading). This provides minimal but not comprehensive behavioral insight.

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. The first sentence clearly states the tool's purpose, followed by structured 'Args' and 'Returns' sections that efficiently provide additional details without redundancy. Every sentence earns its place, making it easy to scan and 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 parameter, no nested objects) and the presence of an output schema, the description is reasonably complete. It explains the purpose, parameter semantics, and return content ('litePoints' as top 10 iconic locations). However, it lacks usage guidelines and could benefit from more behavioral context, such as error cases or performance notes, to be fully comprehensive for an AI agent.

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

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

The description adds meaningful semantics beyond the input schema. The schema has 0% description coverage, only defining 'subject_id' as an integer with a title 'Subject Id'. The description explains that 'subject_id' is 'The Bangumi ID of the anime,' clarifying its purpose and format. This compensates well for the low schema coverage, though it doesn't detail constraints like valid ranges or examples.

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: 'Get the lite info of seichi junrei (anime pilgrimage) locations for a specific anime using its Bangumi ID.' It specifies the verb ('Get'), resource ('lite info of seichi junrei locations'), and scope ('for a specific anime using its Bangumi ID'). However, it doesn't explicitly differentiate from sibling tools like 'get_anime_detail_points' or 'search_bangumi', which would be needed for 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 no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_anime_detail_points' or 'search_bangumi', nor does it explain prerequisites, exclusions, or specific contexts for usage. The only implied context is needing a Bangumi ID, but this is basic parameter information rather than 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?

No annotations are provided, so the description carries the full burden. It discloses that the tool performs a search operation and returns a JSON string with search results and Bangumi IDs, which is useful behavioral context. However, it lacks details on potential limitations like rate limits, authentication needs, or error handling. The description adds value but does not fully compensate for the absence of 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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by concise sections for Args and Returns. Every sentence earns its place by providing essential information without redundancy, making it easy to scan and 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 parameter) and the presence of an output schema (which handles return values), the description is mostly complete. It covers the purpose, parameter semantics, and return format adequately. However, it could improve by addressing behavioral aspects like search limitations or prerequisites, especially since no annotations are provided to fill those gaps.

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

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

The input schema has 0% description coverage, so the description must compensate. It adds meaning by explaining that the 'keyword' parameter is 'The name of the anime to search for,' and specifies it can be in Chinese, Japanese, or English. This clarifies the parameter's purpose beyond the schema's basic type definition, though it does not detail format constraints like length or special characters.

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 for a bangumi (anime) by Chinese/Japanese/English name to get its Bangumi ID.' It specifies the action (search), resource (bangumi/anime), and scope (by name in multiple languages). It also distinguishes from siblings by explaining the ID is 'required for querying seichi junrei locations,' which suggests a different use case than get_anime_detail_points or get_anime_lite_info.

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

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

The description provides clear context for when to use this tool: to search for an anime by name to obtain its Bangumi ID, which is needed for subsequent queries. However, it does not explicitly state when not to use it or name alternatives (e.g., when you already have the ID, use get_anime_detail_points). The guidance is implied but not exhaustive.

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