Server Quality Checklist

Tool Scores

• search_content_detailA
  3.8/5.0
  Behavior4/5

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

  With no annotations, the description bears full burden. It explains the search behavior, pagination (current_page, total_pages), and the need to handle 'next page' prompts. It also notes the match_logic preference for 'OR'. However, it does not disclose potential side effects, but as a read-only search, this is adequate.

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

  Conciseness2/5

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

  The description is excessively long and mixes parameter documentation with LLM instructions (citation format, pagination prompting). While all content is valuable, it is not concise and could be restructured to separate behavioral guidelines from parameter details.

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

  Completeness4/5

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

  Given the tool's complexity (8 parameters, no output schema), the description covers return fields, pagination behavior, and citation requirements. It lacks details on error handling or empty results, but overall is fairly complete for invocation.

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

  Parameters5/5

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

  Schema description coverage is 0%, but the description compensates fully by explaining each parameter's purpose, type, default, and usage notes (e.g., match_logic choices, keywords as list). It adds significant value beyond the bare schema, making parameters self-explanatory.

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

  Purpose4/5

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

  The description clearly states the tool's purpose: querying report detail pages with multiple condition combinations. It uses a specific verb (查询) and resource (报告详情页面). While it does not explicitly distinguish from siblings, the purpose is distinct from search_report_profile and get_similar_content_by_rag.

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

  Usage Guidelines3/5

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

  The description implies usage based on user input to extract parameters and provides detailed instructions for presenting results (citation, pagination). However, it does not specify when not to use this tool or compare to alternatives, lacking explicit usage context.

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

• search_report_profileA
  4/5.0
  Behavior3/5

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

  No annotations provided, so description must carry the burden. It discloses that it's a read-only search and pagination behavior, but doesn't mention authentication, rate limits, or side effects. Adequate but not comprehensive.

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

  Conciseness3/5

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

  The description is lengthy and mixes parameter definitions, usage instructions, and output format. While structured, it could be more concise. The markdown citation instructions add verbosity.

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

  Completeness4/5

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

  Given 8 parameters and no output schema, the description covers the return structure, pagination, and parameter usage. It lacks error handling or no results guidance, but is fairly complete for an LLM-oriented tool.

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

  Parameters4/5

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

  The description explains most parameters (keywords, title, content, publisher, dates, match_logic) with details like default and priority for match_logic. The page_index parameter is not described, but the overall coverage is high.

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

  Purpose5/5

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

  The description clearly states the tool is for querying overall report profiles with multiple conditions. It distinguishes itself from sibling tools like search_content_detail by focusing on summary profiles.

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

  Usage Guidelines4/5

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

  The description provides explicit instructions for LLM to extract parameters from user messages, and how to cite results and handle pagination. It does not explicitly state when not to use, but the context is clear.

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

• get_similar_content_by_ragA
  4.1/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries full burden. It describes the tool as computing similarity and returning matched content, including warnings about citing results. It is transparent about the read-only nature (similarity search) but does not detail any side effects or permissions. Good overall, but lacks depth in 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.

  Conciseness4/5

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

  The description is well-structured with sections for purpose, usage notes, parameters, and return fields. It is somewhat verbose due to detailed citation formatting instructions, but the core information is front-loaded and clear. Minor redundancy reduces conciseness.

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

  Completeness4/5

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

  With no output schema, the description thoroughly explains return fields (page_number, file_name, download_url, etc.) and provides usage context. It covers when to use and how to cite results. However, it does not explain technical details like similarity computation method or limits, leaving minor gaps.

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

  Parameters4/5

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

  Schema description coverage is 0%, but the description compensates by listing the parameter (user_query: str 必填) and its required status. While the schema lacks description, the tool description adds value by clarifying the parameter's role and requirements.

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

  Purpose5/5

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

  The description explicitly states that the tool computes similarity between user input and document content vectors to find the most similar documents (RAG). It clearly distinguishes from sibling tools (search_report_profile, search_content_detail) which serve different purposes.

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

  Usage Guidelines4/5

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

  The description provides a clear when-to-use instruction: '当LLM无法从用户输入中提取明确指令时，优先使用此方法' (When LLM cannot extract clear instructions, prefer this method). It also includes citation formatting guidelines. However, it does not explicitly state when not to use or mention alternatives.

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