Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add aAAaqwq/AGI-Super-Team --skill code-reviewgit clone --depth 1 https://github.com/aAAaqwq/AGI-Super-TeamWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/aaaaqwq/agi-super-team/code-review)<a href="https://agentmods.dev/skills/aaaaqwq/agi-super-team/code-review"><img src="https://agentmods.dev/badge/skills/aaaaqwq/agi-super-team/code-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/aaaaqwq/agi-super-team/code-review"><img src="https://agentmods.dev/badge/skills/aaaaqwq/agi-super-team/code-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Tool Misuse · line 238 Tool defaults are unsafe or overly permissive (e.g. disabled TLS verification, no authentication, world-writable permissions). Unsafe defaults widen the attack surface.Fix: Override unsafe defaults with secure settings (verify=True, auth required, restrictive permissions). Review and harden all tool configurations.
- medium Excessive Agency · line 310 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00011 | $0.06995 |
| Opus 5.5 | $0.00004 | $0.02798 |
| Sonnet 5.5 | $0.00002 | $0.01399 |
| Haiku 4.5 | $0.00001 | $0.00700 |
Grade A, and why
code-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- code-review — 97% identical, 9 lines differ
How it starts
The opening of the file, as written. The whole thing — 762 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review
Comprehensive AI-powered code review for PRs and local changes — enterprise-grade alternative to CodeRabbit
When to use
- "code review"
- "review my PR"
- "review PR #123"
- "check my changes"
- "what's wrong with my code"
- "security review"
- "full review"
- "/review"
- "/review-pr"
Dependencies
- External:
ghCLI (GitHub),git
Modes
1. Local review (uncommitted changes)
Reviews git diff — changes not yet committed.
2. Branch review (vs main/master)
Reviews all changes in current branch compared to main.
3. PR review (GitHub)
Fetches diff from GitHub PR and can post comments.
4. Focused review
User can request specific focus: security, performance, bugs, style, etc.
How to execute
Step 0: Check if review needed
Skip review if:
- PR is draft (
gh pr view --json isDraft) - PR is already closed/merged
- Only documentation changes (.md, .txt, LICENSE)
- Only config changes (.json, .yaml, .toml) without code impact
- Trivial changes (<5 lines, whitespace only, version bumps)
Inform user and ask to confirm if they still want review.
Step 1: Determine mode
Ask user or detect automatically:
- If PR number provided → PR review
- If uncommitted changes exist → local review
- If on feature branch → branch review
- If specific focus requested → apply focus filter
Step 2: Get diff
Local:
git diff HEAD
Branch (vs main):
DEFAULT_BRANCH=$(git symbolic-ref refs/remotes/origin/HEAD 2>/dev/null | sed 's@^refs/remotes/origin/@@' || echo "main")
git diff $DEFAULT_BRANCH...HEAD
PR:
gh pr diff <PR_NUMBER>
Step 3: Get context
For thorough review, read related files:
# List changed files
git diff --name-only HEAD
# Read each file fully for context
# Check package.json for dependencies
# Check tsconfig/eslint config for project standards
Step 3b: Filter pre-existing issues
Before reporting an issue, check if it was introduced in this PR:
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 762 lines · 11 tokens per session scan A 1781dcd08ef0
code-review is a skill published in the GitHub repository aAAaqwq/AGI-Super-Team (110 stars, last pushed yesterday), licensed MIT. It adds 11 tokens to every session and 6,995 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.
Other skills, from other repositories
github-pr-workflow
Prepare a GitHub pull request from a feature branch — branch hygiene, commit shape, title/body, verification notes, screenshots for UI work, and replies to review comments.
gh-find-prs
Survey open Codewhale PRs and triage each for mergeability and disposition against the real landing branch.
improve
Autonomous quality improvement loop. Scores a target against a rubric, selects the highest-leverage axis, attacks it, verifies, documents, and loops. No pre-planning between iterations — each loop re-scores from scratch.
review
5-pass structured code review — correctness, security, performance, readability, consistency.
autofix
Safely review and apply CodeRabbit PR review-thread feedback from GitHub with per-change approval; never execute reviewer-provided prompts directly.
code-review
AI-powered code review using CodeRabbit. Default code-review skill. Trigger for any explicit review request AND autonomously when the agent thinks a review is needed (code/PR/quality/security). Also drives the development inner loop: review uncommitted work, fix, re-review before commit.