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Skills code-review-ai-ai-review
📦
code-review-ai-ai-review
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)
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.
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
Safev4 • 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.
1
Files scanned
451
Lines analyzed
0
Review items
0
False positives ignored
Risk Factors
⚙️ External commands (30)
SKILL.md:367 SKILL.md:370 SKILL.md:25 SKILL.md:54-81 SKILL.md:81-90 SKILL.md:90-114 SKILL.md:114-128 SKILL.md:128-161 SKILL.md:161-169 SKILL.md:169-185 SKILL.md:185-188 SKILL.md:188-195 SKILL.md:195-212 SKILL.md:212-216 SKILL.md:216-232 SKILL.md:232-239 SKILL.md:239-252 SKILL.md:252-257 SKILL.md:257-272 SKILL.md:274-275 SKILL.md:277 SKILL.md:282-286 SKILL.md:286-291 SKILL.md:291-339 SKILL.md:339-343 SKILL.md:343-398 SKILL.md:398-399 SKILL.md:399 SKILL.md:334 SKILL.md:291-339
🌐 Network access (1)
📁 Filesystem access (2)
🔑 Env variables (5)
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.
Copy report link
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<iframe src="https://skillstore.io/embed/skills/sickn33-code-review-ai-ai-review.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>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/4BibTeX 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 55
Architecture
85
Maintainability
87
Content
69
Community
83
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
sickn33License
MIT
Skillstore revision
r1
Version notice
The author did not declare a version.
Repository
https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/code-review-ai-ai-reviewRef
6425ec35f4ac137735cff58cd7877843bba23e3b
Maintenance freshness
7/18/2026
Usage
10 downloads · 109 views
File structure
📄 SKILL.md
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