Skills code-review-ai-ai-review

📦

code-review-ai-ai-review

Name: code-review-ai-ai-review
Author: sickn33

Content revision r1 Safe ⚙️ External commands🌐 Network access📁 Filesystem access🔑 Env variables

Review Pull Requests with AI

Code reviews can miss security, performance, and maintainability issues when changes move quickly. This skill provides structured AI review workflows, scanner guidance, and comment formats for pull requests.

Supports: Claude Codex Code(CC)

🥉 78 Bronze

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request

Review the Skillstore skill "code-review-ai-ai-review" from https://skillstore.io/skills/sickn33-code-review-ai-ai-review.md and its manifest at https://skillstore.io/api/skills/sickn33-code-review-ai-ai-review/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

Your Agent should still show its plan and request any confirmation required by the security policy.

Agent-readable resources

Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.

Markdown detail GET /skills/sickn33-code-review-ai-ai-review.md Signed manifest GET /api/skills/sickn33-code-review-ai-ai-review/manifest Signed lockfile GET /api/skills/sickn33-code-review-ai-ai-review/lockfile

Test it

Using "code-review-ai-ai-review". Review a 120-line login pull request with changed session handling.

Expected outcome:

The skill returns prioritized findings, including missing session invalidation, weak test coverage, and exact review comments for the affected lines.

Using "code-review-ai-ai-review". Plan CI review automation for a TypeScript API.

Expected outcome:

A scanner matrix covering CodeQL, Semgrep, SonarQube, and dependency checks.
A pull request comment workflow with severity labels and quality gate rules.
A list of required secrets and permissions to configure outside the skill.

Using "code-review-ai-ai-review". Evaluate a large refactor touching service boundaries.

Expected outcome:

The skill separates automated checks from human review areas, then flags compatibility, ownership, testing, and architecture risks.

Security Audit

Safe

v4 • 7/5/2026 Open versioned report

The audit found no evidence of malicious prompt injection, credential exfiltration, or hidden execution. The static alerts are caused by Markdown code examples, CI snippets, tool names, secret placeholder references, and a CWE link. The CI examples still require normal approval, least-privilege credentials, and human validation before use.

Files scanned

451

Lines analyzed

Review items

False positives ignored

Risk Factors

⚙️ External commands (30)

🌐 Network access (1)

SKILL.md:283

📁 Filesystem access (2)

SKILL.md:322 SKILL.md:322

🔑 Env variables (5)

SKILL.md:359 SKILL.md:360 SKILL.md:359 SKILL.md:311 SKILL.md:360

No confirmed security findings were detected by the latest completed static and semantic audit. This does not prove the skill has no side effects.

Audited by: codex View Audit History →

Share & cite this report

Share the versioned assessment report, neutral badge, embed card, and citations. Skillstore reports evidence without deciding whether this Skill is safe.

Open versioned report

Copy report link

https://skillstore.io/skills/sickn33-code-review-ai-ai-review/audits/4?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report

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Academic citations (APA · BibTeX · CFF)

APA citation

sickn33. (2026). code-review-ai-ai-review security audit report (audit version 4) [Author version unspecified]. Skillstore. https://skillstore.io/skills/sickn33-code-review-ai-ai-review/audits/4

BibTeX citation

@techreport{sickn33-sickn33-code-review-ai-ai-review-2026,
  author = {sickn33},
  title = {code-review-ai-ai-review security audit report (audit version 4)},
  institution = {Skillstore},
  year = {2026},
  number = {4},
  url = {https://skillstore.io/skills/sickn33-code-review-ai-ai-review/audits/4},
  note = {Author version unspecified}
}

CITATION.cff

cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "code-review-ai-ai-review security audit report (audit version 4)"
version: "unspecified"
type: report
authors:
  - name: "sickn33"
date-released: "2026-07-05"
url: "https://skillstore.io/skills/sickn33-code-review-ai-ai-review/audits/4"
identifiers:
  - type: other
    value: "skillstore:sickn33-code-review-ai-ai-review:audit:4"
    description: "Skillstore immutable audit report identifier"

Skillstore Score

Why this score Evidence Confidence: High

Architecture

Maintainability

Content

Community

Spec Compliance

What You Can Build

Audit Sensitive Pull Requests

Review authentication, authorization, input handling, and dependency changes before merge.

Standardize Review Criteria

Create repeatable severity rules, comment formats, and quality gates for engineering teams.

Design CI Review Pipelines

Plan workflows that combine scanners, AI review, pull request comments, and release gates.

Try These Prompts

Review a Small Pull Request

Use this skill to review the attached diff for bugs, tests, and maintainability. Return concise findings with file, line, severity, reason, and suggested fix.

Check Security Risks

Analyze this authentication or data access change for OWASP risks, secret exposure, missing authorization, and unsafe input handling. Prioritize exploitable issues.

Design a CI Review Workflow

Create a CI plan that runs CodeQL, Semgrep, SonarQube, dependency checks, and AI review for this repo. Include triggers, permissions, outputs, and quality gates.

Tune Enterprise Review Policy

Given our repository standards, risk tolerance, and past false positives, design a review routing policy for automatic comments, human escalation, and release-blocking findings.

Best Practices

Run deterministic static analyzers before AI review so prompts include concrete evidence.
Require human review for security-sensitive, large, or architecture-changing pull requests.
Store API keys in CI secret managers and restrict repository token permissions.

Avoid

Asking the model to approve a pull request without line-level evidence.
Letting AI-generated comments block releases without human confirmation.
Running scanners with broad credentials or on untrusted forks without permission checks.

Frequently Asked Questions

Does this skill run CodeQL or Semgrep automatically?

No. It describes workflows and prompts. Users must install and run tools in their own environment.

Can it replace human reviewers?

No. It helps with triage, repeatable checks, and suggested comments. Humans should decide architecture and release risk.

Which AI tools are supported?

The report lists Claude, Codex, and Claude Code compatibility. The examples also discuss other model providers.

Does it require API keys?

Only if you implement the CI examples. Keep keys in secret managers and use least privilege.

What review areas does it cover?

It covers security, performance, architecture, maintainability, testing, and AI or ML-specific concerns.

Is the referenced playbook included?

No. The current package contains SKILL.md only, so use the main instructions as the available source.

Developer Details

Author

sickn33

License

MIT

Skillstore revision

Version notice

The author did not declare a version.

Repository

https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/code-review-ai-ai-review

Ref

6425ec35f4ac137735cff58cd7877843bba23e3b

Maintenance freshness

7/18/2026

Usage

10 downloads · 109 views

File structure

📄 SKILL.md