Server Quality Checklist

Tool Scores

• check_reuseA
  4.2/5.0
  Behavior4/5

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

  With no annotations, the description carries the full burden. It discloses the method (word shingles), scope (local, deterministic), and what it does not do (web search). It lacks details on case sensitivity or language handling but provides sufficient behavioral context.

  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, front-loaded with the core purpose. Every sentence adds value: first explains action, second clarifies scope, third adds deterministic nature. No wasted 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?

  Given no output schema, the description adequately explains return values (overlap share and verbatim passages). It misses details like error behavior or size limits, but is complete enough for a simple check tool.

  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%, so baseline is 3. The description mentions 'using word shingles' but does not add meaning about the parameters themselves, which are self-explanatory from 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 action (compare text against references), method (word shingles), and output (overlap share and verbatim passages). It unequivocally distinguishes from siblings by specifying local check vs web search.

  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 explains when to use it (local check, not web search) and implicitly that it's for comparing against provided documents. However, it does not explicitly state when not to use it or compare with alternatives, though the context is clear given sibling tools.

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

• find_ai_tellsA
  4.2/5.0
  Behavior4/5

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

  No annotations provided, so the description carries full burden. It declares the tool as deterministic and describes the return format (list of spans with start, end, matched text, note). This discloses key behavioral traits.

  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, front-loaded with main action, no wasted words. Every sentence adds value.

  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 simple tool with one parameter, no output schema, and no annotations, the description covers purpose, return structure, and usage hint. It lacks details like indexing but is sufficient.

  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% with parameter description 'The text to analyze.' The description adds context about analyzing text for AI tells but does not add new semantic details 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 verb (locate), resource (character spans that read as AI), and provides specific examples (stock phrasing, long dashes, formulaic sentence openers). It distinguishes from siblings: check_grammar, check_reuse, detect_ai_text, by focusing on exact spans for AI tells.

  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 advises using results to rephrase only flagged parts, indicating when to use (targeted rephrasing). It does not explicitly state when not to use or compare to siblings, but the intent is clear.

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

• check_grammarA
  4.3/5.0
  Behavior4/5

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

  With no annotations, the description discloses key behavioral traits: rule-based (not AI), fully on-device, deterministic. It also specifies return structure. However, it does not mention any limitations (e.g., text length, language support) or performance characteristics.

  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: the first describes the action and output; the second gives usage context. Every sentence is necessary and front-loaded with the core purpose. No wasted words.

  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 explicitly details the return fields (character span, message, flagged text, suggested fixes). It also provides usage context related to AI tells, making the tool's role clear within the sibling toolset. Complete for a single-parameter tool.

  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?

  The single parameter 'text' is fully described in the schema (100% coverage) as 'The text to analyze.' The description adds no additional meaning beyond what the schema already provides, meeting the baseline expectation.

  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 performs a rule-based grammar and style check on text, specifies on-device operation, and details the output format (character span, message, flagged text, suggested fixes). It distinguishes from sibling tools (check_reuse, detect_ai_text, find_ai_tells) by targeting grammar/phrasing issues.

  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 to use it 'to tidy grammar and phrasing, before or after rewriting the flagged AI tells.' This provides context for when to apply the tool, though it does not explicitly state when not to use it or mention alternatives beyond the implied sibling tools.

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

• detect_ai_textA
  4.9/5.0
  Behavior5/5

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

  Discloses on-device processing, per-signal breakdown, confidence band, no yes/no verdict, directional and biased nature. No annotations provided, so description fully handles transparency.

  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, front-loaded with purpose and key traits, second sentence adds bias and recommendation. No fluff, every sentence 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?

  Given one parameter, no output schema, no annotations, description covers purpose, usage, transparency, bias, follow-up tool. Complete for agent decision-making.

  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?

  Only one parameter 'text' with schema description 'The text to analyze.' Description adds context: 'passage', 'AI-written', 'reads as', enhancing meaning beyond schema. Baseline 3 for high coverage, but description provides valuable extra context.

  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 scores likelihood of AI-written text on a 0-100 scale with no yes/no verdict, distinguishes from sibling find_ai_tells by mentioning it provides per-signal breakdown and suggests using find_ai_tells for spans.

  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 to treat as second opinion, not proof, and advises to call find_ai_tells after for rewriting. Also notes bias against non-native English writers, setting appropriate expectations.

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