Server Quality Checklist

Tool Scores

• create_specA
  4.3/5.0
  Behavior5/5

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

  With no annotations provided, the description carries the full burden and does so thoroughly. It discloses mandatory user-confirmation pauses, automatic stage detection, dependency validation, idempotent execution, error handling, and the fact that content generation is delegated to the LLM rather than performed by the tool.

  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 well-structured with markdown headings and a front-loaded critical warning, but it is heavily redundant. The user-confirmation protocol appears multiple times, and sections like 'Key Features' and 'User Responsibilities' add length without introducing operationally necessary information for invoking the tool correctly.

  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 is unusually complete for a complex orchestration tool: it covers workflow paths, stage dependencies, recovery, confirmation requirements, idempotence, and error guidance. It still leaves some gaps, such as not explaining the relationship or sequencing with the sibling init_spec_project, and not describing the return value above what the schema hints at.

  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 coverage is already high, but the description adds substantial semantic value beyond the schema. It explains the complexity-analysis rules for next_stage, gives concrete examples for simple vs. complex vs. documentation requirements, and clarifies that requirements_prompt should capture the essence of the user's intent.

  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 opening line clearly identifies the tool as an 'Intelligent workflow manager' that routes work through requirements → design → tasks and delegates content generation to the LLM. It does not explicitly distinguish itself from the sibling tool init_spec_project, but the workflow-scoped description is specific enough to convey what the tool does.

  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 'When to use this tool' section lists concrete scenarios such as starting spec-driven development, continuing interrupted workflows, jumping stages, and regenerating documentation. It also provides complete workflow-path examples. However, it never explicitly says when NOT to use it or how it relates to init_spec_project, so it lacks explicit exclusion guidance.

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

• init_spec_projectA
  4.5/5.0
  Behavior4/5

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

  With no annotations, the description carries the transparency burden and handles it well: it discloses that the tool creates directories, copies templates, is idempotent, and does not generate content. It does not fully specify what happens to existing files on a reset, but the main side effects and safety profile are clear.

  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 organized and front-loaded, but it is longer than necessary for a zero-parameter tool: 'prepares the foundation' and 'prepares workspace' are near-duplicates, and the no-content-generation point is repeated three times. Structure helps, but the prose could be trimmed.

  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?

  The description covers purpose, sequencing relative to create_spec, side effects, idempotency, output, and next-step guidance. For a simple parameterless setup tool with no output schema, nothing essential is missing.

  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?

  There are zero parameters, so the schema leaves no gaps to explain. The description still supplies useful setup context, which is the baseline expectation for a parameterless tool.

  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 opens with a specific verb-object statement: 'Initialize spec-driven project structure and templates.' It explicitly contrasts with content generation and names the sibling workflow by saying it prepares the workspace before create_spec, so an agent can distinguish it from create_spec.

  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?

  A dedicated 'When to use this tool' section lists concrete triggers: new project, user asks about setup, before first create_spec use, or resetting structure. The 'not content generation' and 'LLM Responsibility: None' statements clarify when not to rely on it for content work.

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