Server Quality Checklist

Tool Scores

• briefkit_generate_design_systemA
  4/5.0
  Behavior3/5

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

  Annotations already indicate readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds minor context about the output format (markdown) and paste targets (Lovable, Claude Code, Cursor), but does not significantly elaborate on behavioral traits beyond what annotations provide.

  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 clear headings (Args, Returns, Examples) and is appropriately sized for the tool's complexity. Every sentence contributes useful information without redundancy, though it could be slightly more concise.

  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 no output schema, the description thoroughly explains the return value (complete DESIGN.md with CSS custom properties, type scale, etc.) and provides examples. Given full schema coverage and annotations, the description is complete enough for an AI agent to use correctly.

  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 baseline is 3. The description lists all parameters with defaults and enums similar to the schema, but adds value by providing concrete examples that map natural language to parameter values (e.g., 'trust blue colors' → palette='trust-blue'). This aids understanding 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 the tool generates a complete DESIGN.md specification for a SaaS product, covering specific elements like colors, typography, and components. It distinguishes itself from sibling tools (database schema, RLS policies) by focusing on design systems.

  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 implies usage through examples (e.g., 'Generate a design system for my CRM called PipeFlow') but does not explicitly specify when to use this tool versus alternatives like briefkit_generate_database_schema or briefkit_generate_rls_policies. There are no when-not or exclusion statements.

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

• briefkit_generate_database_schemaA
  4.2/5.0
  Behavior4/5

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

  Annotations (readOnlyHint=true, destructiveHint=false, idempotentHint=true) indicate safe, non-modifying behavior. Description adds value by explaining the output is a complete SQL schema ready to run, and clarifies what is included (indexes, security baseline). No contradiction with annotations.

  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 concise: a single introductory sentence, followed by a structured list of arguments with examples. Every sentence adds value, and the front-loading of the purpose is effective. No redundant or vague statements.

  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 complexity (3 parameters, no output schema), the description adequately explains the return format (SQL statements) and includes examples. It covers the essential behavioral context for an agent to decide on invocation.

  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?

  Input schema has 100% description coverage for all three parameters. Description reinforces parameter meaning via examples (e.g., showing saas_type values and custom_tables usage). This adds contextual value beyond the schema descriptions, especially for custom_tables.

  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 it generates a specific resource (Supabase/PostgreSQL database schema) listing included elements (tables, columns, foreign keys, indexes, security baseline). It effectively distinguishes from sibling tools which focus on design systems, RLS policies, and info, making the tool's unique purpose unambiguous.

  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?

  Description provides examples that imply typical use cases (e.g., generating schema for 'StockFlow' or 'invoice generator'), but it does not explicitly state when to use this tool vs. alternatives or when not to use it. The sibling tools are different enough that context is implied, but explicit guidance is lacking.

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

• briefkit_generate_rls_policiesA
  4.2/5.0
  Behavior3/5

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

  Annotations already indicate readOnly=true, destructive=false, idempotent=true, so the safety profile is clear. The description adds output details but no new behavioral traits like auth needs or side effects, which is acceptable given 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 well-structured with separate sections for args, returns, and examples. It is informative without being verbose, though minor repetition exists.

  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 the tool's simplicity (2 required params, no output schema, annotations present), the description fully explains purpose, parameters, output, and special cases. No critical gaps.

  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% with descriptions for both parameters. The description adds value by noting automatic handling of server-only tables and providing examples, which aids understanding 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 it generates RLS policies for Supabase with specific SQL operations (SELECT, INSERT, UPDATE, DELETE). The name, title, and sibling tools (database schema, design system) distinguish it well.

  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 for when to use the tool (generating RLS policies) and includes examples. It does not explicitly exclude alternatives or state when not to use, but the context is sufficient.

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

• briefkit_get_infoA
  4.5/5.0
  Behavior4/5

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

  Annotations already indicate safe/read-only. Description adds return value details (contents, pricing, prompt reduction stats) which is useful context beyond annotations.

  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?

  Three succinct sentences: purpose, usage trigger, return summary. No wasted words, front-loaded.

  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?

  No output schema but description enumerates exactly what is returned (pack contents, pricing, results). Rich annotations complement perfectly. Complete for a simple info tool.

  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; schema coverage is trivially 100%. Baseline for 0 params is 4. Description does not need to add parameter info.

  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?

  Clearly states 'Get information about BriefKit' with detailed specifics (what's in the pack, pricing, integration with AI tools). Distinguishes from siblings that generate specific outputs.

  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 says 'Use this when someone asks about BriefKit, SaaS specification tools, or how to reduce AI build tool iterations.' Could add when to avoid (e.g., for generating specific files).

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