analyze_file_changes

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool analyzes file changes but does not reveal whether it performs a read-only GitHub API call, any side effects, limitations, or what the output contains. This is a significant gap for a tool with no annotation support.

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?

A single, focused sentence with no filler. It is front-loaded with the action and presents the purpose efficiently.

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?

There is no output schema or annotations, so the description must explain what the tool returns or any relevant behavior. It fails to clarify the output format (e.g., a list of change types, a summary, a classification) or any edge cases like large PRs or rate limits. The description is minimal for a tool that likely produces a meaningful analysis.

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 100%, with each parameter (owner, repo, pull_number) already described in the schema. The description adds no supplementary parameter semantics, so the baseline 3 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?

The description uses a specific verb ('Analyzes') and identifies the resource ('file changes in a GitHub PR') and the outcome ('determine the type of changes made'). It clearly distinguishes from sibling tools like analyze_ci_results, which focuses on CI results.

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 this tool—when analyzing file changes in a GitHub PR. However, it does not mention when not to use it or suggest alternatives, so it lacks explicit exclusionary guidance.

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