Server Quality Checklist

Tool Scores

• simulate_tool_choiceA
  3.6/5.0
  Behavior2/5

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

  No annotations are present, so the description must disclose behavioral traits. It only states what the tool does, not whether it is read-only, deterministic, or how predictions are generated. Missing important behavioral context for a simulation tool.

  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 fluff. The first sentence states the core function, the second gives a use case. Efficient and appropriately sized.

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

  Completeness2/5

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

  The description omits expected output format or any caveats about the prediction (e.g., confidence score, top-n tools). With no output schema, this is a significant gap for a prediction tool, making it incomplete for practical use.

  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 the baseline is 3. The description mentions 'user prompt' and 'list of available tools' but adds no extra detail beyond the schema's own parameter descriptions.

  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?

  Clearly states it predicts which tool an agent is most likely to pick given a prompt and tool list. The verb 'predict' and resource 'tool choice' are specific, and this distinguishes it from siblings that score descriptions or generate tests.

  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?

  Provides a clear use context: 'testing tool selection before production.' However, it does not explicitly mention alternatives or when not to use the tool, so it falls short of a full 'when/when-not' guide.

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

• estimate_token_costA
  3.7/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the burden of behavioral disclosure. It notes the estimate is 'rough,' setting expectations about accuracy, but does not disclose return format, potential side effects, or how the estimate is computed. For a non-destructive estimation tool, this is minimal but not misleading.

  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 two sentences that are front-loaded and free of redundancy. The first sentence states the core function, the second adds the decision context. No filler or unnecessary detail.

  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?

  The tool has a simple input schema and no output schema. The description covers purpose and use case but does not specify the return format (e.g., numeric value, range, aggregate) or whether the estimate is per-tool or total. This is a moderate gap, though acceptable for an estimation 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 input schema already provides 100% coverage for the single 'tools' parameter, including nested object structure and descriptions. The tool description adds context about tool definitions and token consumption, but does not add significant detail beyond what the schema already specifies.

  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 action and resource: 'estimate how many tokens a list of tool definitions will consume in the agent context window.' It also provides context for its use case, distinguishing it from sibling tools like score_tool_description or reliability_report.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies usage when deciding on progressive loading ('Helps decide whether to enable progressive loading'), but it does not explicitly state when not to use it or mention alternative tools. Guidance is implied rather than explicit.

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

• generate_agent_testsA
  3.7/5.0
  Behavior3/5

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

  No annotations are provided, so the description must bear the burden. It discloses that the tool generates 3 prompts and the intended use, but does not detail any side effects, permissions, or output format. For a simple generation tool, this is minimal but acceptable.

  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 a single, clear sentence with no superfluous words. Front-loaded with the action.

  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?

  The description covers the core function and purpose, but lacks guidance on usage context, output structure, and any behavioral caveats. Given the tool's simplicity, this is adequate but leaves some gaps.

  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 input schema already provides descriptions for both parameters (tool_name and description), with 100% coverage. The tool description adds no additional parameter information 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 tool's function: 'Generate 3 simple test prompts' with the purpose of verifying an agent's tool selection and usage. This distinguishes it from sibling tools like score_tool_description or simulate_tool_choice.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies the use case (generating test prompts for tool verification) but does not explicitly state when to use it vs alternatives, nor does it mention any exclusions or prerequisites.

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

• reliability_reportA
  3.8/5.0
  Behavior3/5

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

  With no annotations, the description carries full transparency burden. It discloses that the tool creates a short actionable report and combines description scores and token estimates, which hints at internal computation. However, it does not mention whether the operation is read-only, whether it internally invokes other tools, or how the estimates are derived, leaving some behavioral ambiguity.

  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 a single sentence that front-loads the primary action ('Create a short reliability report') and then states the value proposition. There is no filler or repetition of schema details, making it extremely efficient.

  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?

  The tool has one parameter and no output schema, but the description adequately conveys purpose and composition. It explains that the report merges description scores and token estimates, and sibling tool names provide additional context. A minor gap is that the output format is unspecified, which would improve completeness, but it is still sufficient for an agent to understand how to invoke the 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 schema already provides a description for the only parameter 'tools' ('List of tools to evaluate'), so schema coverage is 100%. The description's phrase 'set of tools' adds no new semantic detail beyond what the schema conveys, so a baseline score 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 clearly states the verb 'Create' and the resource 'a short reliability report for a set of tools.' It specifies that the tool combines description scores and token estimates, which differentiates it from siblings like score_tool_description (which scores individual descriptions) and estimate_token_cost (which estimates token costs).

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  Usage is implied rather than explicit. The description indicates that the tool aggregates scores and token estimates into a summary, suggesting it is used when an overall reliability snapshot is needed, but it does not explicitly state when to use this tool versus the sibling functions or provide any exclusions or alternative guidance.

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

• score_tool_descriptionA
  3.8/5.0
  Behavior2/5

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

  No annotations are provided, so the description must carry the full burden. It states the scoring criteria (clarity, specificity, LLM-friendliness) but does not disclose behavior such as whether the tool is read-only, what output format to expect, or any limitations. For an apparently safe utility, this lack of explicit safety disclosure is a notable gap.

  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 two sentences, front-loaded with the primary purpose, and every word contributes value. There is no redundancy or filler.

  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 two parameters and no output schema, the description adequately explains the core function and a primary use case. Missing return-value details are acceptable given the tool's simplicity, but a bit more context on how to interpret the 0-100 score would have made it fully complete.

  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 baseline is 3. The description text adds no additional parameter-level meaning beyond what the schema already provides for 'name' and 'description'. It does not compensate further, but it doesn't need to at this coverage level.

  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: scoring how clear, specific, and LLM-friendly a tool description is on a 0-100 scale. It uses a specific verb (score) and resource (tool description), distinguishing it from sibling tools like estimate_token_cost or simulate_tool_choice.

  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 a clear when-to-use instruction: 'Use this before adding a new tool to an agent to reduce wrong tool calls.' It doesn't explicitly mention alternatives or exclusions, but the context is specific enough to guide the agent.

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