predict_pr_risk

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

No annotations are provided, so the description carries the behavioral burden. It explains the internal steps (diffing, feature extraction, model inference) and names the model type (GradientBoostingClassifier), which aids transparency. However, it does not disclose side effects (e.g., does it write anything) or failure modes for missing refs.

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 sentences: the first is a concise summary, the second provides helpful internal detail. Each sentence adds value, though the second could be slightly tighter.

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 tool's moderate complexity (2 params, 100% schema coverage, and an output schema exists), the description is largely sufficient. It explains how the tool works internally, which compensates for the lack of annotations, leaving no major gaps for typical use.

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%, so the schema already documents both parameters. The description calls out 'base_ref' implicitly by stating it diffs HEAD against base_ref, but does not add new semantics beyond the schema's default and description for base_ref.

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 diffs the current branch against a base ref and ranks changed files by predicted risk. It uses specific verbs ('diff', 'rank') and resources ('changed files', 'predicted risk'), distinguishing it from siblings like 'analyze_coverage' or 'train_risk_model'.

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 implies the tool is used for assessing risk of changed files in a branch, which differs from siblings like 'detect_flaky_tests' or 'analyze_coverage'. It does not explicitly mention when not to use it or provide alternatives.

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