Server Quality Checklist

Tool Scores

• compare_brand_namesA
  4.1/5.0
  Behavior4/5

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

  Annotations already declare readOnly, non-destructive. The description adds valuable context: call-count behavior (one call for up to five names), five verification axes, top-line recommendation, and a legal disclaimer. No behavioral surprises are omitted, so this goes beyond the annotation baseline.

  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?

  Well-structured with trigger phrases, examples, and disclaimer. Slight redundancy between the opening and the 'Returns side-by-side comparison' sentence, but every section earns its place and key info is front-loaded.

  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 no output schema, the description explains return shape (ranked verdicts, recommendation, comparison across axes), usage triggers, examples, and a caveat. It could mention single-name alternatives or failure conditions, but the overall context is enough for an agent to invoke correctly.

  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?

  Schema covers both parameters at 100%, so the baseline is 3. The description's examples illustrate names but add no extra semantics for the optional vertical parameter, and no parameter syntax details beyond what schema already provides.

  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 states a specific action ('Compares 2-5 brand name candidates side-by-side and returns a ranked verdict for each, plus a recommendation') with a clear result. The examples and trigger phrases distinguish it from sibling tools like verify_brand_name, which likely handles single names.

  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?

  Explicit 'Use this tool whenever a user' triggers and two concrete examples make the intended usage clear. It doesn't explicitly name alternatives or state when NOT to use it (e.g., single-name checks), but the 2-5 range and finalist framing imply the boundary.

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

• verify_brand_nameA
  4.4/5.0
  Behavior5/5

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

  The description goes far beyond the annotations by disclosing response time (2-3 seconds), free tier limits, signup prompt behavior, default class handling (software/SaaS), and the presence of _citation field. It also mentions the public verification URL and disclaimer. No contradiction with readOnlyHint=true or destructiveHint=false exists.

  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 long but well-structured with clear sections, examples, and a disclaimer. Every sentence serves a purpose, though the mention of non-existent parameters and the lengthy pricing details could be trimmed. Overall, it is efficient for the complexity it covers.

  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 all essential aspects: purpose, verdict semantics, use cases, alternatives, pricing, default behavior, methodology, verification, and examples. Since there is no output schema, it properly explains the returned fields and how to interpret them, making it complete for an agent to invoke and act on the tool.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The schema already describes both parameters (name and vertical) with 100% coverage, so the baseline is 3. However, the description erroneously introduces non-existent parameters `business_description` and `nice_classes`, which could mislead the agent into setting invalid fields. This adds confusion rather than clarity, lowering the score.

  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's function: verifying brand names and returning a signed clearance verdict (PROCEED / PROCEED_STRATEGIC / ABANDON). It also distinguishes itself from sibling tools by naming compare_brand_names, unblock_name, and get_naming_methodology, making its unique role explicit.

  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?

  Provides explicit trigger conditions ('Use this tool whenever a user...') with specific examples. It also gives clear alternatives: use compare_brand_names for similarity checks, unblock_name for abandoned names, and get_naming_methodology for methodology questions. This fully addresses when and when not to use the tool.

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

• get_naming_methodologyA
  4.6/5.0
  Behavior5/5

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

  Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds meaningful context: operation is free, no quota, publicly accessible, and includes a legal disclaimer. All disclosed behaviors align 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.

  Conciseness4/5

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

  The description is well-structured with a clear 'Use this tool when' list and additional operational details. It is longer than strictly necessary but every sentence adds value, covering purpose, usage, access, and disclaimer.

  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 read-only tool with one optional parameter and no output schema, the description covers purpose, usage, access constraints, and legal caveats. It fully satisfies contextual needs without requiring explanation of return values.

  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?

  Schema coverage is 100%: the only parameter (section) has an enum and description. The description reinforces that section is optional and references the five axes, but it doesn't provide new parameter semantics beyond what the schema already defines. Baseline 3 is appropriate.

  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 the public Etymolt verification methodology, specifying that it covers five axes. It distinguishes itself from sibling tools like verify_brand_name and compare_brand_names by focusing on methodology rather than name-level operations.

  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 lists multiple user scenarios ('Asks how does this verification work?', 'Wants to cite Etymolt's analysis') and an inline-quote use case. It adds operational context (free, no quota) and refers to the public URL for direct linking, though it doesn't name alternative tools explicitly.

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

• unblock_nameA
  4.7/5.0
  Behavior4/5

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

  No annotations are provided, so the description carries the full burden. It discloses key behaviors: returns pre-verified variants, sorted descending by score, and warns that missing class scope leads to ambiguously-scoped variants. It also mentions the return structure. However, it doesn't explicitly state the operation is read-only or note any side effects, though the tool seems non-destructive by nature.

  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: main action, use-when bullets, don't-use exclusion, input notes, and returns. Every sentence adds essential information without redundancy. It is front-loaded with the core purpose and remains focused.

  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 there is no output schema and no annotations, the description provides a thorough picture: it explains when to use, how it relates to verify_brand_name, what inputs are needed and why, and what the output looks like. It leaves no major gaps for an agent to misuse the 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?

  Schema coverage is 100%, so the baseline is 3. The description adds value beyond the schema by linking parameters to the verify_brand_name context ('the same business_description or nice_classes you used') and highlighting the consequence of omitting them ('Without the class scope, this returns ambiguously-scoped variants'). This enriches parameter understanding.

  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 and resource: 'Generates close variants of the original name that are clear in the same goods/class.' It clearly distinguishes from siblings by stating 'Don't use for unrelated name generation' and pointing to verify_brand_name as the prerequisite. This is a precise purpose statement.

  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?

  It explicitly states when to use (after verify_brand_name returns ABANDON) and when not to use ('Don't use for unrelated name generation... call verify_brand_name on each candidate instead'). The 'Use when' bullets give concrete triggers. This is exemplary usage guidance with alternatives.

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