Server Quality Checklist

Tool Scores

• generate_resume_from_textC
  2.7/5.0
  Behavior2/5

  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 generates PDF files and supports templates, but lacks critical details: whether this is a read-only or write operation (implied write but not confirmed), authentication requirements, rate limits, error handling, or what happens to the input text. For a tool with no annotations and 3 parameters, 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.

  Conciseness4/5

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

  The description is concise and front-loaded, stating the core purpose in the first sentence. It uses two sentences to cover key features (template support, no manual JSON processing), with minimal redundancy. However, it could be slightly more structured by separating usage notes from functionality.

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

  Completeness2/5

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

  Given the complexity (3 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain the output (e.g., PDF file format, return type), error conditions, or behavioral nuances. For a tool that generates files and has sibling tools, more context is needed to ensure correct usage by an AI agent.

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

  Parameters2/5

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

  Schema description coverage is 0%, so the description must compensate. It mentions '简历文本内容' (resume text content) for 'resumeText', '多种模板' (multiple templates) and '简历模板' (resume templates) for 'templateName', and '定制选项' (customization options) for 'options'. However, it doesn't explain parameter formats, constraints, or examples (e.g., what template names are valid, what 'options' object contains). With 3 parameters and low coverage, this adds only basic meaning.

  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: '将简历文本转换为精美PDF简历' (convert resume text to beautiful PDF resume). It specifies the verb (convert), resource (resume text), and output format (PDF). However, it doesn't explicitly differentiate from sibling tools like 'convert_resume_text' or 'analyze_resume_text', which likely have different functions.

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

  Usage Guidelines2/5

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

  The description provides minimal guidance on when to use this tool. It mentions '支持多种模板' (supports multiple templates) and '可选择不同简历模板和定制选项' (can choose different resume templates and customization options), but doesn't clarify when to use this vs. alternatives like 'convert_resume_text' or 'get_templates'. No explicit exclusions or prerequisites are stated.

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

• analyze_resume_textC
  2.9/5.0
  Behavior2/5

  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 the tool provides analysis and suggestions, but lacks details on permissions, rate limits, output format, or whether it's read-only or mutative. This is inadequate for a tool with potential complexity in analysis.

  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 concise and front-loaded, stating the core purpose in the first sentence. The second sentence elaborates on analysis aspects without redundancy. However, it could be more structured with explicit sections for usage or output.

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

  Completeness2/5

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

  Given no annotations, no output schema, and 0% schema description coverage, the description is incomplete. It doesn't explain the return values, error conditions, or behavioral traits needed for effective tool use, leaving significant gaps for an analysis tool.

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

  Parameters3/5

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

  The description implies the parameter 'resumeText' is the text to analyze, but adds minimal meaning beyond the schema's basic type (string). With 0% schema description coverage and 1 parameter, the baseline is 4, but the description doesn't compensate with details like format expectations or constraints, so it scores slightly lower.

  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: '对简历文本进行深度分析，提供专业评估和改进建议' (deeply analyze resume text, provide professional evaluation and improvement suggestions). It specifies the action (analyze) and resource (resume text), though it doesn't explicitly differentiate from sibling tools like 'convert_resume_text' or 'generate_resume_from_text' beyond the analysis focus.

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

  Usage Guidelines2/5

  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 mentions analyzing resume text for completeness, keywords, and skill matching, but doesn't specify prerequisites, exclusions, or compare it to sibling tools like 'convert_resume_text' or 'generate_resume_from_text'.

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

• convert_resume_textB
  3.1/5.0
  Behavior2/5

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

  With no annotations provided, the description carries full burden. It mentions intelligent section recognition and international standard compliance, but lacks details about error handling, processing time, limitations (e.g., language support, format constraints), or what happens with malformed input. The behavioral disclosure is insufficient for a transformation tool.

  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 appropriately concise with two sentences that directly address the tool's function and benefits. It's front-loaded with the core purpose and avoids unnecessary elaboration, though the second sentence could be slightly more focused.

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

  Completeness3/5

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

  For a single-parameter transformation tool with no annotations or output schema, the description provides basic purpose and parameter context but lacks sufficient behavioral details. It doesn't explain the output structure or potential errors, leaving gaps in understanding how the tool behaves in practice.

  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?

  With only 1 parameter (resumeText) and 0% schema description coverage, the description compensates well by explaining what the parameter should contain: '纯文本格式的简历内容' (plain text format resume content). This adds meaningful context beyond the bare schema, though it doesn't specify format expectations or constraints.

  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: converting plain text resumes to JSON Resume format with intelligent section recognition. It specifies both the input (plain text) and output (structured JSON Resume), though it doesn't explicitly distinguish from sibling tools like 'analyze_resume_text' or 'generate_resume_from_text'.

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

  Usage Guidelines2/5

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

  No explicit guidance on when to use this tool versus alternatives. The description mentions it's for '方便后续编辑和格式转换' (facilitating subsequent editing and format conversion), but doesn't specify scenarios where this conversion is preferred over direct analysis or generation from text.

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

• get_templatesB
  3.1/5.0
  Behavior2/5

  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 describes the tool as a read operation ('获取' - get) and lists return details, but lacks behavioral context such as whether it requires authentication, has rate limits, returns paginated results, or handles errors. This is inadequate for a tool with zero annotation coverage.

  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 concise and front-loaded, stating the core purpose in the first clause. Both sentences add value: the first defines the action and outputs, and the second explains the user benefit. There is no wasted text, though it could be slightly more structured for clarity.

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

  Completeness3/5

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

  Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. It covers the purpose and outputs but lacks behavioral details like error handling or performance characteristics. For a read-only tool with no complex schema, this is acceptable but leaves gaps in transparency.

  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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately does not discuss parameters, focusing instead on the tool's purpose and outputs. This meets the baseline for tools with no parameters.

  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: '获取所有可用的简历模板' (get all available resume templates) with specific outputs like template ID, name, and thumbnail. It distinguishes from siblings by focusing on template retrieval rather than analysis, conversion, or generation. However, it doesn't explicitly differentiate from potential similar tools beyond the given siblings.

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

  Usage Guidelines2/5

  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 mentions '帮助用户选择最适合的简历风格' (help users choose the most suitable resume style), which implies a context of template selection, but offers no explicit when/when-not rules or comparisons to sibling tools like analyze_resume_text or generate_resume_from_text.

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