code-review_skill

This skill guides post-development code reviews by orchestrating parallel sub-agents to surface findings and enforce fixes.
  • Python

110

GitHub Stars

1

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill sammcj/agentic-coding --skill code-review

  • SKILL.md1.2 KB

Overview

This skill performs a focused, agentic code review after completing multiple complex development tasks to ensure changes are correct and release-ready. It runs parallel sub-agents to self-review, compiles prioritized findings, verifies each issue against the real code, and applies fixes before declaring work complete.

How this skill works

After you finish multiple changes, the skill spawns parallel sub-agents that inspect only the scoped modifications and produce concise, actionable findings. It aggregates those findings into a numbered list with severity labels, verifies each reported issue against the actual code to avoid false positives, and then implements fixes and re-runs lint/test/build pipelines to confirm resolution.

When to use it

  • Before marking a batch of related changes as complete or merging to main.
  • After large refactors touching multiple modules or services.
  • Prior to a release or deploy to catch high-severity regressions early.
  • When multiple features or bugfixes land in the same PR or branch.
  • Before gating changes behind CI checks or code-ownership reviews.

Best practices

  • Scope each sub-agent to only the changed files or logical boundaries to avoid noise.
  • Instruct sub-agents to keep outputs concise and actionable—no broad stylistic nitpicks.
  • Label every finding with severity (critical/medium/low) and a one-line impact summary.
  • Always verify findings against the actual code to eliminate false positives.
  • Implement fixes and re-run the full lint/test/build pipeline before reporting completion.

Example use cases

  • A multi-module refactor where behavior changes might be scattered across packages.
  • Aggregating and validating fixes after a sprint that produced several interdependent PRs.
  • Preparing a release candidate by catching regressions introduced across feature branches.
  • Handling a backlog of bugfixes that touch shared utilities and require coordinated validation.
  • Gatekeeping CI failures by reproducing and resolving issues found by automated checks.

FAQ

Speed depends on change size and test suite; parallel sub-agents speed up inspection but plan for full pipeline time when re-running builds and tests.

Can it auto-fix everything?

The skill auto-applies straightforward fixes (e.g., linting, small API adjustments) but will surface complex or design-impacting issues for human decision and review.

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