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 algorithm type ('字符匹配算法' - character matching algorithm) and the tool's suitability for quick verification/location. However, it doesn't mention potential limitations (e.g., accuracy, speed, rate limits), authentication needs, or error handling. It adds some behavioral context but leaves gaps for a tool with no 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 well-structured and concise. It starts with the core purpose, adds usage guidelines, and includes clear sections for Args and Returns. Every sentence adds value, though the 'ctx' parameter note could be more integrated. It's appropriately sized for a single-parameter 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?

Given the tool's moderate complexity (1 parameter, 100% schema coverage, output schema exists), the description is fairly complete. It covers purpose, usage, parameters, and return values. The output schema handles return details, so the description doesn't need to explain them. However, with no annotations, it could benefit from more behavioral context like limitations or prerequisites.

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%, so the baseline is 3. The description adds value by explaining the parameter 'query' as '论文标题或关键词' (paper title or keywords), which clarifies its semantic purpose beyond the schema's basic description. However, it doesn't provide additional details like format examples or constraints beyond what the schema already covers (minLength: 1).

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: '快速查找与输入标题最匹配的 CNKI 论文' (quickly find the best matching CNKI paper for an input title). It specifies the verb (find), resource (CNKI papers), and scope (best match). However, it doesn't explicitly differentiate from sibling tools like 'search_cnki' beyond mentioning it uses a 'character matching algorithm'.

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 some usage context: '适合用于验证论文标题或快速定位特定论文' (suitable for verifying paper titles or quickly locating specific papers). This implies when to use it, but it doesn't explicitly state when NOT to use it or mention alternatives like 'search_cnki' or 'get_paper_detail'. The guidance is helpful but incomplete.

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 of behavioral disclosure. It states this is a retrieval operation ('获取'), which implies read-only behavior, and describes the comprehensive return format. However, it doesn't mention potential limitations like rate limits, authentication requirements, error conditions, or whether the tool caches results. The description adds value by specifying the scope ('完整信息' - complete information) but lacks operational 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?

The description is well-structured with clear sections (purpose, Args, Returns) and efficiently conveys essential information. The purpose statement is front-loaded, and every sentence serves a clear function. Minor improvement could be made by integrating the parameter guidance more seamlessly rather than as a separate Args section note.

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 single parameter with full schema coverage, the existence of an output schema (implied by the Returns section detailing the dictionary structure), and clear differentiation from sibling tools, the description is complete enough. It covers purpose, parameter context, and return format without unnecessary detail. The output schema information in the Returns section compensates for any missing behavioral 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?

With 100% schema description coverage, the schema already fully documents the single 'url' parameter. The description adds meaningful context by specifying that URLs '通常从 search_cnki 结果中获取' (usually obtained from search_cnki results), which provides practical guidance on parameter sourcing. This goes beyond the schema's technical documentation to offer usage semantics.

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 ('获取' meaning 'get/retrieve'), the resource ('CNKI 论文详情页的完整信息' meaning 'complete information from CNKI paper detail page'), and distinguishes from siblings by focusing on detail extraction rather than searching (search_cnki) or matching (find_best_match). The verb+resource combination is precise 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 clear context for when to use this tool: after obtaining a URL from search_cnki results. It implicitly distinguishes from search_cnki (which finds papers) and find_best_match (which likely matches queries to papers). However, it doesn't explicitly state when NOT to use this tool or mention alternatives beyond the implied workflow.

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 pages parameter has a range (1-10) and each page returns about 20 results, which adds some behavioral context. However, it doesn't cover important aspects like rate limits, authentication requirements, error conditions, or whether this is a read-only operation. For a search tool with no annotation coverage, 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 well-structured with clear sections (Args, Returns) and uses bullet points for enumerations. It's appropriately sized for a tool with 4 parameters. However, the first sentence could be more front-loaded with key information, and some parameter details are redundant with the schema.

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's an output schema (the Returns section describes the response structure), the description doesn't need to explain return values in detail. It covers the basic purpose and parameters adequately. However, for a search tool with no annotations, it could provide more context about limitations, performance characteristics, or error handling.

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 thoroughly. The description repeats some parameter information (search_type options, pages range, sort options) but doesn't add significant meaning beyond what's in the schema. The baseline of 3 is appropriate when the schema does the heavy lifting, though the description does provide some additional context about page size ('每页约20条结果').

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: '搜索 CNKI 论文，返回论文列表' (Search CNKI papers, return paper list). It specifies the verb ('搜索' - search) and resource ('CNKI 论文' - CNKI papers). However, it doesn't explicitly differentiate from sibling tools like 'find_best_match' or 'get_paper_detail', 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 no guidance on when to use this tool versus its siblings ('find_best_match' and 'get_paper_detail'). It doesn't mention any prerequisites, exclusions, or alternative scenarios. The only usage context is implied by the tool name and description, but no explicit guidelines are given.

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