Server Quality Checklist

Tool Scores

• audit_textA
  4.7/5.0
  Behavior5/5

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

  Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, and the description adds valuable behavior beyond that: the audit runs locally, is deterministic, returns up to 100 flagged patterns and 100 highlighted sentence regions, and includes truncation counts. It also disclaims that the result is heuristic rather than proof, which is essential context for the agent's interpretation.

  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 sentences, each earning its place: one identifies the action and method, one lists the return bounds and truncation behavior, and one sets expectations and routes to the sibling. The most decision-relevant facts are 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?

  Given the output schema exists, the annotations cover safety, and the description covers local processing, deterministic behavior, response bounds, truncation counts, and the heuristic caveat, an agent has everything it needs to select and invoke the tool correctly. The only thing left to the schema is the context enum, which is appropriately delegated.

  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 description coverage is 100%, so the text and context parameters are already documented. The description adds no extra parameter semantics, but it doesn't need to because the schema carries that weight. 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 states a specific action ('Audit text'), names the concrete detector ('the deterministic Avoid AI Writing detector'), and distinguishes this tool from its sibling score_text by describing the richer audit output. An agent can tell exactly what this tool does and how it differs from the sibling without opening the schema.

  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 gives clear usage context: it is a local, deterministic, heuristic writing audit and not proof of authorship. It explicitly says to use score_text when a compact result is needed, naming the alternative and the condition that selects it.

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

• score_textA
  4.7/5.0
  Behavior5/5

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

  Annotations already cover read-only, idempotent, and non-destructive hints. The description adds critical behavioral traits: the detector is deterministic, it is a heuristic signal not proof of authorship, and it operates locally. These go beyond the annotations and help calibrate trust in the output.

  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 sentences with no filler. The action and scope are front-loaded, the caveat is stated compactly, and the alternative is offered in the same breath. Every word earns its place.

  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 tool has a rich output schema, complete parameter documentation, and strong annotations. The description covers the operation's purpose, the caveat about heuristic results, and the routing to audit_text. Nothing an agent needs to call it correctly is missing.

  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 description coverage is 100% – both parameters have clear descriptions (text is local, context has default and behavior). The description itself does not add parameter-specific semantics beyond the schema, so the baseline of 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 states a specific verb ('Score'), a resource ('text'), and the exact detector ('Avoid AI Writing'). It also names the sibling tool 'audit_text' and differentiates by saying when audit_text is needed, so it clearly distinguishes from the alternative.

  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 to 'use audit_text when individual findings are needed', implying this tool is for a compact score. It also notes the operation is local and deterministic, giving clear context for when to choose this tool.

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