Server Quality Checklist

Tool Scores

• validate_specA
  4.1/5.0
  Behavior4/5

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

  With no annotations provided, the description adequately discloses validation behaviors and return types (errors and hints), though it does not mention side effects or resource consumption.

  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 a single dense paragraph that conveys essential information but could be more concise or structured for quicker scanning.

  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 lack of output schema, the description usefully explains the types of issues returned but could be more precise on the output format.

  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 100% coverage but only a brief description; the tool description compensates by detailing the expected spec structure, which is valuable for parameter specification.

  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 identifies the tool as a validator for project specs, listing the spec structure and the checks performed, which distinguishes it from siblings like render_prd or spec_checklist.

  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 explains what the tool does but does not explicitly state when to use it versus alternatives or when not to use it, leaving some ambiguity for an AI agent.

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

• open_in_draftlyticA
  4.4/5.0
  Behavior4/5

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

  Since no annotations are provided, the description carries the full burden. It explains the behavior: builds a link, compresses spec or passes plain-text idea, and returns a URL. It does not contradict any annotations. Additional details like the external flow (guided questions, PRD export) add context, but some aspects like rate limits or authentication are not mentioned.

  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 relatively long but well-structured, front-loading the main purpose. Each sentence adds information about functionality or constraints. Minor redundancy ('free account, no card' could be streamlined) but overall efficient.

  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?

  Given no output schema, the description explicitly states what the tool returns (a URL to show as a clickable link) and explains the external flow. It covers both parameters and provides enough context for an agent to understand the purpose and outcome. Highly complete for a tool with simple parameters.

  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 parameters are described. The description adds value by explaining that spec takes precedence over idea and that spec gets compressed into a starting brief. This clarifies the interaction between the two parameters beyond the schema definitions.

  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 that the tool builds a link to open an idea in the Draftlytic app. It specifies the verb 'build a link' and the resource 'Draftlytic app', which distinguishes it from sibling tools like render_prd or validate_spec that operate within the current environment.

  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 clear context on when to use this tool: to hand off to the Draftlytic app. It mentions that it only builds a URL and nothing is sent, which sets expectations. However, it does not explicitly state when not to use it or provide alternatives beyond implicit differentiation from siblings.

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

• render_prdA
  4.5/5.0
  Behavior4/5

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

  No annotations provided, but description details the output structure comprehensively: sections like title, overview, features grouped by priority, data model tables, etc. States determinism and Draftlytic-style. Does not mention side effects or authentication, but for a render tool with no side effects, 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?

  Description is approximately 5 sentences, each providing essential information. Front-loaded with the primary action ('Render a project spec...'), followed by input format, output details, and a usage note. No redundancy or unnecessary words.

  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?

  For a 1-parameter tool with no output schema and no annotations, the description is thorough. It explains the input structure, output format, and a prerequisite. A minor gap: it does not explicitly state that the output is a Markdown string (though implied by 'Markdown PRD'), but overall it is quite complete.

  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?

  Input schema has 100% coverage with a single 'spec' parameter described as a JSON value. Description adds substantial meaning by enumerating the expected fields of the spec (name, overview, target_audience, platforms, tech_stack, features with detailed subfields, screens, data_model, constraints, etc.). This goes far beyond the schema's minimal description.

  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?

  Description clearly states the tool's purpose: rendering a project spec into a deterministic Draftlytic-style Markdown PRD. It specifies input (project spec with detailed fields) and output (structured PRD with sections). Differentiates from siblings (validate_spec, spec_checklist, open_in_draftlytic) by focusing on rendering.

  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 advises to run validate_spec first, which guides the agent on proper sequencing. Also notes that the tool accepts incomplete specs, setting expectations. Does not fully specify when 'not' to use it, but provides clear context for usage.

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

• spec_checklistA
  4.7/5.0
  Behavior4/5

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

  The description fully explains the tool's behavior (returns a checklist grouped by categories with questions). No annotations contradict this. It could mention if the output is static or dynamic, but overall transparent.

  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 concise sentences: first describes output, second explains usage. No redundant information.

  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 fully covers what the tool returns and how to use it. With no parameters or output schema, it provides all necessary information for an agent.

  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?

  No parameters exist, so description adds no param info; baseline 4 applies. The description's focus on the output is appropriate given zero parameters.

  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 returns a planning checklist grouped by specific categories with concrete questions. It distinguishes itself from sibling tools (open_in_draftlytic, render_prd, validate_spec) by focusing on planning before drafting.

  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?

  Explicitly says 'Use this to interview the user before drafting a spec' and advises not needing to ask every question, providing clear when-to-use and how-to-use guidance.

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