Server Quality Checklist

Tool Scores

• usage_deltaA
  3.8/5.0
  Behavior3/5

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

  With no annotations, description carries burden. It explains the two actions but doesn't disclose persistence of baseline, side effects (e.g., overwrite), or rate limits. Some transparency but incomplete.

  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, no fluff. Efficiently conveys action and purpose.

  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 the tool's simplicity (2 params, no output schema, no annotations), the description covers the main behavior. Missing output format and error cases, but adequate for a basic 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% with descriptions for both action and label. Description adds no new meaning beyond the schema, so baseline 3 applies.

  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 it tracks real cost of a single task, with specific actions 'mark' and 'measure', and distinguishes itself from theoretical estimates. This is specific and helpful.

  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?

  No explicit guidance on when to use this tool vs siblings like usage_forecast or usage_status. The mention of replacing theoretical costs implies use case but lacks clear context or exclusions.

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

• cache_statsA
  3.9/5.0
  Behavior4/5

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

  With no annotations provided, the description carries full burden. It discloses that it reads the latest session log and interprets the hit rate, which is sufficient for a compute-only tool. It does not mention side effects or error conditions, but none are expected.

  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 action, and no extraneous words. Every sentence adds value.

  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 explains the purpose and signal interpretation, but does not specify the output format (e.g., percentage, numeric value) or how 'latest' is determined. With no output schema, this leaves a gap for an agent to know what to expect.

  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 adds no additional meaning beyond what the schema already provides for the two parameters. Description does not elaborate on project_dir or last_n.

  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 computes Anthropic prompt cache hit rate from Claude Code session logs, with a specific verb and resource. It distinguishes from sibling tools which focus on other usage metrics (proceed, delta, forecast, status).

  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 gives context on when low hit rate indicates wasted tokens, implying use for efficiency analysis. However, it does not explicitly state when to use this tool versus alternatives, or provide exclusions or prerequisites.

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

• should_proceedA
  4/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries full responsibility. It discloses that the tool returns 'proceed/downgrade/abort', but does not explain the criteria for each outcome (e.g., based on current usage thresholds). This is adequate but could be more explicit about the decision logic.

  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 purpose and return values, followed by usage timing. Every sentence earns its place with zero 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?

  For a simple tool with two parameters, no output schema, and no annotations, the description covers the essentials: purpose, return values, and when to use. It could include a brief note about the decision mechanism or an example, but it is largely complete for its complexity.

  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%, with the schema already thoroughly documenting both parameters (task_size enum values with token estimates, description as free-text). The main description adds no additional parameter meaning beyond 'Call BEFORE...', which is usage, not parameter semantics. 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 clearly states the tool's purpose: 'Decide whether to proceed with a task given current usage. Returns proceed/downgrade/abort.' It identifies the specific verb 'decide' and the resource 'proceed/downgrade/abort', making it distinct from sibling tools which are informational (cache_stats, usage_delta, etc.).

  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 explicitly lists when to use the tool: 'Call BEFORE producing large responses, doing huge file reads, or starting expensive operations.' This provides clear context and implies when not to use (small tasks), though it does not explicitly exclude or name alternative tools.

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

• usage_forecastA
  4/5.0
  Behavior3/5

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

  No annotations are provided, so the description must carry the burden. It explains what the tool does but does not mention whether it is read-only, what data it reads, or any side effects. For a zero-parameter tool, this is acceptable but not thorough.

  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 key information. Every word adds value, no redundancy or fluff.

  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 description is fairly complete for a simple tool with no parameters and no output schema. It explains the core function and the decision it enables, though it could be more specific about terms like 'burn rate' or time horizon.

  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?

  There are no parameters, so the schema is empty. The description adds meaning by explaining the computation and output without needing parameters, which is a baseline of 4 because the schema provides no additional info.

  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 uses specific verbs ('compute', 'tells you') and clearly identifies the resource ('usage history', 'limit'). It distinguishes from sibling tools like usage_status and usage_delta by focusing on forecasting.

  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?

  No explicit guidance on when to use this tool vs alternatives like usage_status or usage_delta. However, the purpose implies it is for future projections, so usage is implied but not clarified.

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

• usage_statusA
  4/5.0
  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 discloses auth behavior (reads OAuth token), logging behavior (auto-logs to history), and data source (same endpoint as IDE bar), but does not mention read-only nature, rate limits, or potential side effects beyond logging.

  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 very concise at two sentences, each adding essential information: purpose with specific data types, and technical details (auth source, logging). No redundant or vague phrases.

  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 and low complexity, the description adequately explains return values (session, weekly usage, reset times, extra credits) and covers auth and logging. It lacks mention of error conditions or prerequisites beyond the token file, but is otherwise complete for a simple read tool.

  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 zero parameters and 100% schema description coverage, so baseline is 4. The description adds context by detailing the returned data types and auth mechanism, going beyond the bare 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 fetches real-time Claude.ai subscription usage, specifies the data types (5h session, 7d weekly utilization, reset times, extra credits), and distinguishes itself from sibling tools like usage_delta and usage_forecast by referencing the same endpoint as Claude Code's IDE bar.

  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 mentions reading OAuth token and auto-logging to history, providing some context on setup and side effects, but does not explicitly compare with sibling tools or state when to use vs alternatives.

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