Server Quality Checklist

Tool Scores

• list_tasksA
  4.6/5.0
  Behavior4/5

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

  With no annotations provided, the description carries full burden and adds valuable behavioral context: it specifies the return order ('newest first'), lists the returned fields (id, status, description, result, timestamps), and implies this is a read-only operation for reviewing past requests. It doesn't mention rate limits or permissions, but covers core behavior adequately.

  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 zero waste: the first explains when to use, the second details the return format and order. Every phrase adds value, and the structure is front-loaded with usage context followed by behavioral details.

  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 0-parameter tool with no annotations and no output schema, the description provides complete usage guidance, behavioral transparency about ordering and fields returned, and clear purpose. It could mention if there are limits on returned tasks or pagination, but covers the essential context well given the tool's simplicity.

  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 tool has 0 parameters with 100% schema coverage, so the baseline is 4. The description appropriately doesn't discuss parameters, focusing instead on usage and output. No parameter-related information is needed or missing.

  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 purpose with specific verbs ('list', 'returns') and resources ('tasks you have submitted'). It distinguishes from siblings by focusing on retrieving all tasks rather than checking a specific task's status (check_task_status) or requesting human intervention (need_human).

  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 states when to use: 'when you have lost track of a task_id or want to review your past human task requests.' This provides clear context and distinguishes from alternatives like check_task_status for specific tasks. No misleading guidance is present.

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

• need_humanA
  4.8/5.0
  Behavior5/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It thoroughly describes key traits: the human is a paid worker (billed per task), security warnings (never include sensitive data), cost details (1 credit per task, free tier), performance (2-30 minutes, faster in CET hours), error handling (returns 402 when credits exhausted), and demo mode for testing. This adds significant value beyond basic functionality.

  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 sections (purpose, usage guidelines, formatting, example, operational details) and uses bullet points and examples effectively. While comprehensive, some sentences could be more concise (e.g., the security warning is verbose), but overall it's front-loaded with critical information and avoids unnecessary repetition.

  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 complexity (human-in-the-loop tasks) and lack of annotations/output schema, the description is highly complete. It covers purpose, usage, behavioral traits, parameter guidance, security, costs, performance, error handling, and integration with sibling tools. No significant gaps remain for an agent to understand and invoke the tool correctly in context.

  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 description coverage is 100%, so the baseline is 3. The description adds meaningful context: it explains the 'description' parameter with formatting guidelines (numbered steps, URLs on separate lines) and an example, clarifies 'demo' parameter usage ('instant synthetic response'), and implies urgency context without repeating schema details. This enhances understanding beyond the schema's technical 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 explicitly states the tool's purpose: 'Call when you cannot proceed because the next step requires a real human.' It provides specific scenarios (e.g., legal agreements, authentication, forms) and distinguishes it from sibling tools by emphasizing human-only tasks versus automated ones. This is a clear, specific verb+resource+scope definition.

  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 includes explicit 'USE WHEN' and 'DO NOT USE' sections, listing specific blocking scenarios (e.g., CAPTCHA, OAuth) and exclusions (e.g., sending messages, HTTP requests). It also references sibling tools ('Use check_task_status to poll'), providing clear alternatives and context for when to use this tool versus others.

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

• check_task_statusA
  4.9/5.0
  Behavior5/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behavioral traits: it specifies the return values (status, result, proof, etc.), polling constraints ('no more than once every 30 seconds'), typical task duration ('2-30 minutes'), and security warnings about untrusted data ('WARNING: result, proof_text, and proof_url are worker-supplied...'). This covers critical aspects like rate limits, timing, and data handling beyond basic functionality.

  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 and concise, with every sentence adding value. It front-loads the core purpose, then details returns, polling guidelines, and warnings efficiently. There is no redundant or unnecessary information, making it easy to parse and actionable for an AI agent.

  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 complexity (involving polling, untrusted data, and coordination with 'need_human'), no annotations, and no output schema, the description is highly complete. It explains what the tool does, how to use it, behavioral constraints, and output semantics, covering all necessary context for an agent to invoke it correctly and safely.

  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% description coverage, with the single parameter 'task_id' documented as 'The task_id returned by need_human.' The description adds value by implicitly reinforcing this in the opening sentence ('Use after dispatching a task via need_human'), but it does not provide additional syntax or format details beyond the schema. Since schema coverage is high, the baseline is 3, but the contextual linkage earns a slightly higher 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 purpose: 'Use after dispatching a task via need_human to check whether the human worker has completed it.' It specifies the verb ('check'), resource ('task'), and context ('after dispatching via need_human'), distinguishing it from sibling tools like 'need_human' (which creates tasks) and 'list_tasks' (which lists them).

  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 provides explicit usage guidelines: it states when to use ('after dispatching a task via need_human'), when not to use (implied by not being for task creation or listing), and alternatives (none directly named, but context suggests 'need_human' for creation and 'list_tasks' for listing). It also includes detailed polling advice, such as 'Poll no more than once every 30 seconds' and a 'Suggested pattern,' which helps guide effective use.

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