Server Quality Checklist

Tool Scores

• suggest_patternA
  4/5.0
  Behavior4/5

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

  With no annotations, the description carries the behavioral disclosure burden. It discloses the response format (up to 3 ranked suggestions with confidence scores), which covers the core behavior. It does not address failure modes, but for a simple suggestion tool 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.

  Conciseness5/5

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

  Two efficient sentences with no redundancy. It front-loads the core purpose and includes usage context. Every word earns its place.

  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?

  The description covers the essential context: input, output, and when to use. Since there is no output schema, it provides necessary return information (ranked suggestions with confidence). Minor gaps like no-suggestion behavior are not critical for this 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 input schema provides 100% coverage of both parameters with clear descriptions. The tool description adds no additional parameter-level semantics beyond the schema, so the baseline of 3 applies.

  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 uses a specific verb ('Map') and clearly identifies the input (problem description) and output (design pattern name(s)), including result limit and confidence scores. It does not explicitly differentiate from the sibling tool get_template, so it misses the top score.

  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?

  Explicitly states when to call this tool ('when you know the problem but not which pattern to apply'), giving clear context. However, it does not mention alternatives or when not to use it, so it doesn't fully earn a 5.

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

• get_templateA
  4.5/5.0
  Behavior4/5

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

  The description discloses that the tool returns compact plain text (~300-500 tokens) optimized for LLM consumption, which goes beyond the basic action. Since no annotations are provided, this adds useful context about output format and size. It does not explicitly state side effects, but the verb 'Get' implies a read-only operation, and no contradicting information exists. A small deduction for not explicitly noting that the operation is read-only.

  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 two sentences long, with the first sentence stating the core purpose and the second providing usage guidance. Every word earns its place; there is no fluff or repetition of schema information. It is efficiently structured and immediately readable.

  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 simple two-parameter tool with full schema coverage, the description provides sufficient context: it tells the agent what the tool does, when to call it, and what the output format looks like. No output schema exists, but the description's mention of plain text token size gives the agent enough to know what to expect. The sibling tool relationship is also addressed via usage guidance.

  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 input schema already provides 100% coverage for both parameters (`pattern` and `language`) with examples and allowed values. The description does not add meaning beyond what the schema gives, such as parameter constraints or relationships. The baseline of 3 is appropriate given full schema coverage.

  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 function: retrieving structural constraints and anti-patterns for a specific design pattern in a specific language. The verb 'Get' and the resource ('structural constraints and anti-patterns') are specific and distinguish this from the sibling `suggest_pattern`, which likely suggests patterns rather than retrieving details for a known one.

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

  Usage Guidelines5/5

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

  The description explicitly says 'Call this when you know which pattern to implement,' which directly tells the agent when to use this tool. It implicitly contrasts with the sibling `suggest_pattern`, implying that if the pattern is unknown, the other tool should be used first. This provides clear usage guidance and exclusions.

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