Server Quality Checklist

Tool Scores

• skillsmp_search_skillsA
  4/5.0
  Behavior4/5

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

  Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false. The description adds a 'Returns' section outlining the output fields (name, description, author, star count), which is useful given there is no output schema. It does not contradict the annotations.

  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 separate sections for args, returns, and examples, making it easy to scan. It repeats some schema information, but this is acceptable for completeness and does not make it excessively long.

  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 moderate complexity and lack of an output schema, the description covers all necessary aspects: purpose, when to use, parameters, return structure, and examples. It is complete enough for an agent to select and invoke the tool appropriately.

  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 provides thorough descriptions for all parameters (100% coverage). The description enhances the 'query' parameter with concrete examples that illustrate intended usage, though page, limit, and sortBy only repeat the schema's existing descriptions.

  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 it searches for AI skills using keywords from the SkillsMP marketplace, providing a specific verb and resource. It includes concrete examples like 'PDF manipulation' and 'web scraper', but it does not differentiate from the sibling tool 'skillsmp_ai_search_skills'.

  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 includes an explicit instruction to use this tool before starting any task to check for existing skills, which is strong usage guidance. However, it does not mention when not to use it or compare with the sibling search tool.

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

• skillsmp_ai_search_skillsA
  4.5/5.0
  Behavior4/5

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

  Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds that the search is semantic, returns a list of relevant skills, and gives example queries, which enriches behavioral understanding without contradiction.

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

  Conciseness5/5

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

  The description is well-organized with a clear main statement, usage guidance, args, return value, and examples. Every sentence earns its place and there is no redundancy.

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

  Completeness5/5

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

  For a single-parameter read-only search tool with no output schema, the description covers purpose, when to use it, parameter semantics, and expected return value. The examples make it immediately actionable.

  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 schema fully describes the single parameter, so baseline is 3. The description adds concrete examples of valid queries and clarifies that the query should be a natural language intent statement, providing value beyond the schema.

  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 this is an 'AI semantic search for skills using natural language descriptions,' with a specific verb and resource. It distinguishes itself from siblings by emphasizing intent-based search 'rather than specific keywords.'

  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?

  It explicitly says to use this tool when finding skills by desired outcome, and advises checking it before complex tasks. It doesn't explicitly name alternatives, but the semantic-vs-keyword contrast provides useful context.

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

• skillsmp_read_skillA
  4.7/5.0
  Behavior5/5

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

  The description goes far beyond the annotations by disclosing key behavioral traits: fully online (no local clone), no files written to disk, skill not installed, and optional local server startup (via uvx) for scanning. It also notes the prerequisite (uv) for the scan. This substantial extra context makes the tool's side effects and operational requirements clear.

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

  Conciseness5/5

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

  The description is well-structured with clear sections (purpose, behavior, usage note, args, returns, examples). It front-loads the core purpose, every sentence provides useful information, and the length is appropriate given the tool's complexity (3 parameters, optional scanning, side effects). No redundant or filler content.

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

  Completeness5/5

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

  Despite having no output schema, the description explicitly states the return value ('full content of the skill's instructions (SKILL.md) with security scan results'). It also covers prerequisites, side effects, and non-destructive nature. This provides an agent with a complete understanding of what to expect and how to use the tool safely.

  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 coverage is 100%, so the baseline is 3. The description adds meaning through concrete examples for repo and skillName (e.g., 'existential-birds/beagle', 'python-code-review') and clarifies the enableScan default and uv requirement in the args section. While the schema already documents parameter formats, the examples provide additional concrete usage patterns that help an agent construct valid invocations.

  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 begins with a specific verb ('Read') and a clear resource ('a skill's content directly from a GitHub repository'), distinguishes itself from sibling search tools by emphasizing direct content retrieval, and includes an explicit 'IMPORTANT' usage note. This leaves no ambiguity about the tool's primary function.

  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 statement ('Use this to quickly load skill instructions and verify safety without manual steps') and includes examples. However, it does not explicitly mention alternatives or when not to use this tool, which would fully satisfy the rubric for a 5.

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