PR Babysitter
openinterpreter/openinterpreter
Watches an open GitHub pull request until it merges, handling review comments, diagnosing CI failures and retrying flaky checks along the way.
Perform thorough code reviews on files or pull requests, checking for bugs, security vulnerabilities, performance issues, and style violations.
$ npx skills add seb1n/awesome-ai-agent-skills --skill code-review -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills code-review --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/code-and-development/code-review .claude/skills/code-review && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "code-review" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/code-and-development/code-review into .claude/skills/code-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "code-review", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/seb1n/awesome-ai-agent-skills/tree/main/code-and-development/code-reviewType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add seb1n/awesome-ai-agent-skills --skill code-review -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills code-review --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/code-and-development/code-review .agents/skills/code-review && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "code-review" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/code-and-development/code-review into .agents/skills/code-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "code-review", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add seb1n/awesome-ai-agent-skills --skill code-review -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills code-review --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/code-and-development/code-review .cursor/skills/code-review && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "code-review" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/code-and-development/code-review into .cursor/skills/code-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "code-review", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/seb1n/awesome-ai-agent-skills.git --path code-and-development/code-review--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add seb1n/awesome-ai-agent-skills --skill code-review -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills code-review --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/code-and-development/code-review .gemini/skills/code-review && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "code-review" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/code-and-development/code-review into .gemini/skills/code-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "code-review", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install seb1n/awesome-ai-agent-skills code-reviewInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add seb1n/awesome-ai-agent-skills --skill code-review -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/code-and-development/code-review .github/skills/code-review && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "code-review" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/code-and-development/code-review into .github/skills/code-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "code-review", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add seb1n/awesome-ai-agent-skills --skill code-review -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install seb1n/awesome-ai-agent-skills code-review --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/code-and-development/code-review .opencode/skills/code-review && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "code-review" agent skill from https://github.com/seb1n/awesome-ai-agent-skills/tree/main/code-and-development/code-review into .opencode/skills/code-review/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "code-review", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
code-reviewPerform thorough code reviews on files or pull requests, checking for bugs, security vulnerabilities, performance issues, and style violations.
Code Review is an agent skill from seb1n/awesome-ai-agent-skills. Perform thorough code reviews on files or pull requests, checking for bugs, security vulnerabilities, performance issues, and style violations. Use when the user requests code review or provides relevant inputs for this workflow.
Its SKILL.md is about 2.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Development, covering Code review and Pull requests. The repository describes itself as: 103 ready-to-use AI agent skills for Claude Code, OpenAI Codex, Gemini CLI, Cursor, GitHub Copilot, Windsurf, and other Agent Skills-compatible tools. Complete SKILL.md… The licence is MIT.
6 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 75865a5. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are python and diff).
From the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
github.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Code Review loads about 2.5k tokens when it runs. Until then it costs about 60 tokens; SKILL.md has 859 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from seb1n/awesome-ai-agent-skills at commit 75865a5, republished under its MIT licence (© seb1n). 859 words, ~2,540 tokens.
.claude/skills/code-review/SKILL.md (or your agent's skills folder).This skill enables an AI agent to conduct a structured, comprehensive code review on a source file, a set of changes, or a pull request. The agent examines the code across multiple quality dimensions — correctness, security, performance, readability, and maintainability — and produces a detailed review report with actionable feedback tied to specific lines of code.
Parse the input and establish context. Determine whether the input is a single file, a directory, or a pull request diff. If it is a pull request, fetch the diff and identify the base branch so that only the changed lines are reviewed. Read any related configuration files (linter configs, style guides, type definitions) to calibrate the review against the project's standards.
Understand the intent of the change. Read commit messages, PR descriptions, and surrounding code to understand what the author intended. This prevents false positives — a reviewer must know the goal before judging whether the code achieves it. Summarize the change in one sentence before proceeding.
Check for correctness and bugs. Walk through every changed function and trace the data flow. Look for null or undefined dereferences, off-by-one errors, incorrect boolean logic, unhandled error paths, race conditions in concurrent code, and resource leaks (open files, database connections, unreleased locks). Verify that edge cases — empty inputs, maximum values, unexpected types — are handled.
Evaluate security. Scan for common vulnerability patterns: unsanitized user input (SQL injection, XSS), hardcoded secrets or credentials, insecure cryptographic usage, overly permissive file or network access, and missing authentication or authorization checks. Flag any dependency additions and check for known CVEs.
Assess performance and scalability. Identify algorithmic complexity issues (nested loops over large collections, repeated database queries inside loops, unbounded memory growth). Check for unnecessary allocations, missing caching opportunities, and blocking calls in async contexts. Consider the expected data volume and whether the code will scale.
Review readability and maintainability. Evaluate naming clarity, function length, code duplication (DRY violations), and adherence to the project's style guide. Check that public functions have docstrings or type annotations. Verify that magic numbers are replaced with named constants and that complex logic has explanatory comments.
The agent evaluates every change against these categories:
| Category | What to look for |
|---|---|
| Bugs | Null derefs, off-by-one, logic errors, unhandled exceptions |
| Security | Injection, XSS, hardcoded secrets, missing auth, insecure dependencies |
| Performance | O(n²) loops, N+1 queries, unnecessary allocations, blocking I/O |
| Readability | Unclear names, long functions, missing docs, inconsistent formatting |
| DRY | Copy-pasted blocks, duplicated logic that should be extracted |
| Error handling | Swallowed exceptions, missing retries, unclear error messages |
| Testing | Missing tests for new logic, broken existing tests, untested edge cases |
Provide one or more of the following inputs:
https://github.com/user/repo/pull/42. The agent fetches the diff and reviews only the changed lines in context.Given this file src/auth.py:
import hashlib
def authenticate(username, password, db):
query = f"SELECT password_hash FROM users WHERE username = '{username}'"
row = db.execute(query).fetchone()
if row is None:
return False
stored_hash = row[0]
input_hash = hashlib.md5(password.encode()).hexdigest()
return input_hash == stored_hashThe agent produces the following review:
## Review: src/auth.py — authenticate()
### Critical — SQL Injection (line 4)
The query uses f-string interpolation with `username` directly in the SQL
string. An attacker can pass `' OR '1'='1` as the username to bypass
authentication entirely.
**Fix:** Use parameterized queries.
- row = db.execute(query).fetchone()
+ row = db.execute(
+ "SELECT password_hash FROM users WHERE username = ?", (username,)
+ ).fetchone()
### Critical — Weak Hashing Algorithm (line 9)
MD5 is cryptographically broken and unsuitable for password hashing. It is
vulnerable to rainbow table attacks and can be brute-forced in seconds on
modern hardware.
**Fix:** Use bcrypt or argon2 with a per-user salt.
- input_hash = hashlib.md5(password.encode()).hexdigest()
+ import bcrypt
+ return bcrypt.checkpw(password.encode(), stored_hash.encode())
### Warning — Timing Attack (line 10)
Direct string comparison of hashes with `==` leaks information through
timing differences. Use a constant-time comparison function.
**Fix:**
- return input_hash == stored_hash
+ import hmac
+ return hmac.compare_digest(input_hash, stored_hash)
### Info — Missing Type Annotations
Adding type hints improves readability and enables static analysis:
def authenticate(username: str, password: str, db: Connection) -> bool:
**Summary:** 2 critical, 1 warning, 1 info. This function must not be
deployed until the SQL injection and hashing issues are resolved.Given a PR diff for src/api/orders.js:
@@ -12,6 +12,20 @@ const express = require("express");
const router = express.Router();
+router.get("/orders", async (req, res) => {
+ const userId = req.query.userId;
+ const orders = await db.query("SELECT * FROM orders WHERE user_id = $1", [userId]);
+ const enriched = [];
+ for (const order of orders.rows) {
+ const items = await db.query("SELECT * FROM order_items WHERE order_id = $1", [order.id]);
+ order.items = items.rows;
+ enriched.push(order);
+ }
+ res.json(enriched);
+});The agent produces:
## Review: src/api/orders.js — GET /orders
### Warning — N+1 Query (lines 18-21)
Each order triggers a separate SELECT for its items. For a user with 200
orders this executes 201 database queries. This will degrade significantly
under load.
**Fix:** Use a single JOIN or a batched IN query:
const items = await db.query(
"SELECT * FROM order_items WHERE order_id = ANY($1)",
[orders.rows.map(o => o.id)]
);
// Then group items by order_id in application code.
### Warning — Missing Authorization Check (line 14)
The endpoint reads `userId` from the query string without verifying that
the authenticated user is allowed to view that user's orders. Any user
can read any other user's order history by changing the query parameter.
**Fix:** Validate that `req.user.id === userId` or that the requester
has an admin role before executing the query.
### Info — SELECT * Usage (lines 16, 19)
Selecting all columns returns data the client may not need (e.g.,
internal timestamps, soft-delete flags). Specify only the required columns
to reduce payload size and avoid leaking internal fields.
**Summary:** 0 critical, 2 warning, 1 info.© seb1n, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in code-and-development/code-review of seb1n/awesome-ai-agent-skills.
Open the folder on GitHubat commit 75865a5
Code Review next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Code Review this skillseb1n/awesome-ai-agent-skills | 206 | — | ~2.5k | Automated safety check: Pass | MIT | |
| PR Babysitteropeninterpreter/openinterpreter | 69k | 3 repos | ~4.2k | Automated safety check: Pass | Apache-2.0 | |
| Understand Diff AnalysisEgonex-AI/Understand-Anything | 85k | 1 repos | ~1.4k | Automated safety check: Pass | MIT | |
| WooCommerce Code Reviewwoocommerce/woocommerce | 11k | 3 repos | ~1.1k | Automated safety check: Pass | Custom licence | |
| Open Code Review CLIalibaba/open-code-review | 44k | — | ~3.1k | Automated safety check: Pass | Apache-2.0 | |
| GitHub Review Iterationprisma/orm | 48k | — | ~2.2k | Automated safety check: Pass | Apache-2.0 |
openinterpreter/openinterpreter
Watches an open GitHub pull request until it merges, handling review comments, diagnosing CI failures and retrying flaky checks along the way.
Egonex-AI/Understand-Anything
Reads your git changes or a pull request against a prebuilt knowledge graph of the project to explain what changed, which components are affected and what is risky.
woocommerce/woocommerce
Reviews WooCommerce code changes against the project's standards, flagging backend PHP architecture, naming, documentation, data integrity and testing violations.
alibaba/open-code-review
Runs the ocr command-line tool to review Git changes, a commit or a branch comparison with an AI model, returning line-level comments and optionally applying fixes.
prisma/orm
Runs a loop on a GitHub pull request: fetch review state, triage comments into actions, implement them and resolve threads, repeating until nothing actionable is left.
microsoft/garnet
Checks that a pull request's title and description match its implementation and reviews the code for Garnet best practices, reporting findings without posting them.
seb1n/awesome-ai-agent-skills
Plan, execute, document, and retest authorized security assessments of AI agents and multi-agent workflows using safe adversarial cases, synthetic identities, canaries, and evidence-based findings.
seb1n/awesome-ai-agent-skills
Build a preliminary, evidence-based EU AI Act readiness assessment across AI-system inventory, territorial scope, operator roles, prohibited-practice screening, risk classification, transparency…
seb1n/awesome-ai-agent-skills
Design and verify auditable human oversight, approval gates, escalation paths, and safe state transitions for AI agent workflows.
seb1n/awesome-ai-agent-skills
Design, implement, harden, and verify Model Context Protocol (MCP) servers with precise tool contracts, least-privilege authorization, safe transports, structured errors, and interoperability tests.
seb1n/awesome-ai-agent-skills
Inspect, extract, OCR, create, merge, split, reorder, rotate, annotate, fill, redact, compress, secure, and verify PDF documents while preserving source files and visual fidelity.
seb1n/awesome-ai-agent-skills
Audit agent skills, plugins, prompts, manifests, scripts, dependencies, and bundled assets for provenance, prompt-injection, permission, execution, exfiltration, persistence, and update risk.
Categories
Perform thorough code reviews on files or pull requests, checking for bugs, security vulnerabilities, performance issues, and style violations. Code Review is an agent skill from seb1n/awesome-ai-agent-skills. Perform thorough code reviews on files or pull requests, checking for bugs, security vulnerabilities, performance issues, and style violations.
Code Review fits situations like: the user requests code review; provides relevant inputs for this workflow.
Run `npx skills add seb1n/awesome-ai-agent-skills --skill code-review -a claude-code`. Or copy the skill folder (code-and-development/code-review in seb1n/awesome-ai-agent-skills) into .claude/skills/code-review in your project. Claude Code loads it when a task matches its description.
Run `npx skills add seb1n/awesome-ai-agent-skills --skill code-review -a codex`. Or copy the skill folder (code-and-development/code-review in seb1n/awesome-ai-agent-skills) into .agents/skills/code-review in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add seb1n/awesome-ai-agent-skills --skill code-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/code-review, .gemini/skills/code-review, .github/skills/code-review and .opencode/skills/code-review in your project.
SKILL.md names no scripts, command-line tools or credentials: Code Review is instructions for the agent only. Our summary lists: Python 3.
SKILL.md names 1 domain. In commands or code: github.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Code Review is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.5k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Code Review: PR Babysitter (openinterpreter/openinterpreter, 69k stars), Understand Diff Analysis (Egonex-AI/Understand-Anything, 85k stars), WooCommerce Code Review (woocommerce/woocommerce, 11k stars) and Open Code Review CLI (alibaba/open-code-review, 44k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
seb1n (a GitHub user) maintains it in seb1n/awesome-ai-agent-skills, which has 206 GitHub stars. The repository holds 92 skills in this directory. The repository was last updated on August 9, 2026.
Source: seb1n/awesome-ai-agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.