correlate_code_changes

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

With no annotations, the description must disclose behavioral traits but only states the operation and return type. It does not mention side effects, limitations, or how the optional affectedTests parameter influences behavior, leaving the agent with limited insight into the tool's runtime characteristics.

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 with the core action front-loaded. Every phrase is informative, and there is no redundancy, making it highly efficient and easy to parse.

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?

The absence of an output schema shifts the burden to the description to explain the return value, but 'correlation mapping' is vague and lacks structural details. Edge cases and the behavior of the optional parameter are unaddressed, leaving the agent under-informed for a 3-parameter 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?

The input schema provides 100% description coverage for all parameters, so the baseline is 3. The description adds no extra parameter semantics beyond what is already in the schema, such as formatting rules or parameter interdependencies.

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's function with a specific verb ('Match') and delineates the exact inputs (changed files, failing tests) and objective (determine which failures are directly caused by changes). It distinguishes itself from siblings like detect_temporal_failure_patterns by focusing on code-change causation.

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 provides clear context for when to use the tool: when analyzing a commit's changes against its failing tests. However, it does not explicitly mention alternatives or exclusion criteria, so it misses the full 'when/when-not' guidance needed for a 5.

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