predict_regression

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

No annotations are provided, so the description carries the full burden. It discloses what the tool uses (past bugs, test failures, constraint violations) but does not state whether it has side effects, permissions requirements, or what the output looks like. The methodology hint adds some behavioral context, but safety and operational traits remain undisclosed.

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 a single, front-loaded sentence with no wasted words. It efficiently conveys the tool's purpose and key inputs.

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?

For a tool with two simple parameters and no output schema, the description is adequate for tool selection but does not fully prepare the agent for invocation. It lacks details on input semantics and return value format, though the simplicity and sibling context make it acceptable but not thorough.

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 description coverage is 0%, so the description must compensate. It mentions 'proposed change to a file' which loosely maps to file_path and change_description, but it does not clarify parameter formats, required fields, or examples. The description adds minimal meaning beyond what the property names already imply.

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 uses a specific verb ('Score') and resource ('regression risk') with the basis ('past bugs, test failures, and constraint violations'). It clearly distinguishes from siblings like predict_test_failures (which targets test failures specifically) and simulate_change (which simulates changes).

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 usage for assessing regression risk of a proposed change to a file, but it does not explicitly state when to prefer this tool over alternatives or provide exclusions. Sibling tools like predict_test_failures or validate_change could overlap, and no guidance is given on choosing among them.

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