Server Quality Checklist

Tool Scores

• ai_statusA
  3.8/5.0
  Behavior3/5

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

  With no annotations provided, the description carries full burden. It indicates this is a diagnostic/read-only operation ('check', 'monitoring', 'debugging', 'verifying') which implies non-destructive behavior, but doesn't explicitly state permission requirements, rate limits, or detailed response format. It provides basic behavioral context but lacks comprehensive disclosure.

  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 perfectly concise: two sentences with zero wasted words. The first sentence states purpose with specific components, the second provides usage context. Every element earns its place and information is front-loaded effectively.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness3/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a diagnostic tool with no parameters, no annotations, and no output schema, the description provides adequate purpose and usage context. However, it doesn't describe what the output contains (status indicators, configuration details, test results format) or potential error conditions, leaving gaps in completeness for a tool that presumably returns system information.

  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 description coverage. The description appropriately doesn't discuss parameters since none exist, maintaining focus on the tool's purpose and usage context. This meets the baseline expectation for parameterless tools.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose4/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool's purpose as health monitoring with specific components: checking AI orchestration system status, model configuration, and capability testing results. It distinguishes from siblings by focusing on system diagnostics rather than processing (ai_process) or general information retrieval (get_info), though it doesn't explicitly name those alternatives.

  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 usage: 'Useful for debugging or verifying system readiness.' This gives practical guidance on when to use the tool, though it doesn't explicitly state when not to use it or name specific alternatives among siblings.

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

• get_infoA
  3.8/5.0
  Behavior3/5

  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 describes the tool's function (introspection/discovery) but doesn't mention potential side effects, authentication requirements, rate limits, or what the return format looks like. The description adds value but lacks detailed 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?

  The description is perfectly concise with two sentences that each earn their place: the first states what the tool does, and the second provides usage guidance. There's zero wasted text, and information is front-loaded appropriately.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness3/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool's complexity (introspection with no parameters) and lack of annotations/output schema, the description is adequate but has clear gaps. It explains the purpose and usage context well, but doesn't describe what information is returned or any behavioral constraints, making it incomplete for full agent understanding.

  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 description coverage, so the schema already fully documents the input (none required). The description doesn't need to add parameter information, and it appropriately focuses on the tool's purpose instead. Baseline 4 is appropriate for zero-parameter tools.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose4/5

  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 ('discover available capabilities, connected servers, and tool inventory') and resources ('orchestrator'), making it immediately understandable. It doesn't explicitly differentiate from sibling tools (ai_process, ai_status), but the scope is well-defined.

  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 this tool ('to understand what the orchestrator can do before making complex requests'), which is helpful guidance. However, it doesn't specify when NOT to use it or mention alternatives among the sibling tools, keeping it from a perfect score.

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

• ai_processA
  4.2/5.0
  Behavior3/5

  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 communicates that this is an orchestration tool that automatically selects and coordinates multiple tools, which implies mutation capabilities across various domains. However, it doesn't disclose important behavioral traits like error handling, authentication requirements, rate limits, or what happens when coordination fails. The description adds value by explaining the orchestration behavior but leaves significant gaps.

  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 appropriately sized and front-loaded with the core purpose in the first sentence. The second sentence expands on capabilities, and the third provides clear usage guidance. While efficient, the middle sentence listing domains ('file operations, git management...') could be slightly more concise, but overall it earns its place by clarifying scope.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness3/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a complex orchestration tool with no annotations and no output schema, the description provides good purpose and usage context but lacks important behavioral details. It doesn't explain what the tool returns (success/failure indicators, workflow results), doesn't mention constraints or limitations, and doesn't address error scenarios. Given the tool's complexity and lack of structured metadata, the description should do more to compensate.

  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 schema description coverage is 100%, so the schema already fully documents the single 'request' parameter. The description adds meaningful context by emphasizing this should be a 'natural language description' and providing concrete examples of what types of requests are appropriate. While it doesn't add technical details beyond the schema, it significantly enhances understanding of how to formulate effective requests.

  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 as an 'AI orchestration interface' that 'intelligently processes complex requests by automatically selecting and coordinating multiple tools.' It specifically distinguishes this from sibling tools like ai_status and get_info by emphasizing its multi-tool coordination capability and broad domain coverage (file operations, git management, web search, etc.).

  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 guidance on when to use this tool: 'Describe your goal naturally - the AI will determine the best approach and execute multi-step workflows.' It implicitly suggests this is for complex, multi-step tasks rather than simple status checks (ai_status) or basic information retrieval (get_info), making the context clear without naming alternatives directly.

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