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review_pr

Run an AI code review on a GitHub pull request. Fetches the diff, reviews each changed file in parallel, and returns a synthesized markdown report.

Instructions

Run a full AI code review on a pull request: fetches the diff, reviews every changed file in parallel, and returns a synthesized markdown review.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoYes
ownerYes
pull_numberYes
Behavior4/5

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

With no annotations, the description discloses key behaviors: fetches diff, parallel file review, returns markdown. It does not disclose potential side effects (e.g., does it post a comment?) but the sibling tools suggest it only returns. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single, well-structured sentence that conveys the core action and process. Front-loaded with the main purpose, no unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the essential workflow and output (synthesized markdown review). Lacks details on prerequisites or error handling, but for a three-parameter tool without an output schema, it is sufficiently complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has three parameters (owner, repo, pull_number) with zero descriptions. The tool description adds no additional meaning beyond the parameter names, which are self-explanatory. Given 0% schema description coverage, more elaboration would be beneficial.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool performs a full AI code review on a pull request, including fetching the diff, reviewing every changed file in parallel, and returning a synthesized markdown review. This distinguishes it from siblings like get_pr_diff (just diff), review_file (single file), and post_review_comment (posting a comment).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives. The description does not mention conditions or provide context for selecting this over review_file or get_pr_diff for partial reviews.

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

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