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

Annotations only cover read-only and idempotent behavior, but the description adds substantial context beyond that: the scoring model (start at 100, subtract size/lines/files/complexity/focus/title-description/cross-area penalties), a bounded AI adjustment of at most ±20, and explicit exclusions (no CI results, no linter). It also constrains reporting to the returned `factors`, preventing fabricated explanations.

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?

Front-loaded with purpose and a concrete example use case, then a second paragraph on methodology and caveats. Every sentence carries information, though the methodology paragraph is slightly dense and could be trimmed without losing meaning.

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?

Output schema exists, so return values need no explanation, yet the description still clarifies the shape of the response and the scoring rationale. The exclusions (CI, linter) and the instruction to report only returned factors close the remaining ambiguity for an explain-style tool.

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 is 100% and both parameters are documented in the schema with format examples ('owner/name', PR number 1186). The description adds no additional parameter-level detail, so the baseline of 3 for a fully-documented schema is appropriate.

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?

States a specific verb and resource: explain why one specific PR received its score and label. The description also enumerates exactly what it returns (score, label, size counts, penalties with point cost, AI adjustment, breakdown), which clearly separates it from sibling metrics tools like get-pull-request-metrics-tool.

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?

Gives explicit trigger scenarios such as someone asking 'why is #1186 marked poor' or wanting to understand a low score on their own PR, and it defines the scope as one specific pull request. It does not, however, name an alternative sibling (e.g. get-pull-request-metrics-tool) for aggregate or cross-PR comparisons.

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