Quantum Score

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

Annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds meaningful behavioral context: it states the result is reproducible ('same codebase always gives same score') and mentions confidence weighting, which implies a confidence output. These details go beyond the annotations and help an agent anticipate behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two short sentences with no fluff. It front-loads the core purpose (scoring), then states the grading scale and reproducibility. Every sentence earns its place, and the structure is clear and efficient.

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

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

Given the simple input (one well-documented path) and strong annotations, the description covers the essential invocation details. It explains the output scale and reproducibility. It could be more complete by listing the 10 dimensions or how confidence weighting is reported, but for an agent deciding to call it, the current description is sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage for the single 'path' parameter is 100%, so the baseline is 3. The description does not enrich the parameter meaning beyond saying it gives a score; the schema already explains 'path' as an absolute path to the repo root. No additional parameter-specific detail is provided, so it stays at baseline.

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

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

The description clearly states the tool computes a '10-dimension weighted codebase score' and assigns a grade on an S/A/B/C/D/F scale, which specifies the verb, resource, and output format. It is distinct from generic 'analyze' tools, but it does not explicitly differentiate from similar scoring siblings like code_quality or complexity, so it misses the top mark.

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

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

The description gives no guidance on when to use this tool versus alternatives. It does not mention prerequisites, exclusions, or contrast with any sibling tools (e.g., verify_all, code_quality). An agent has to infer from the name and output that it is for overall scoring, but no explicit usage context is provided.

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