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-review-qualitygit 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-quality)<a href="https://agentmods.dev/skills/aaaaqwq/agi-super-team/code-review-quality"><img src="https://agentmods.dev/badge/skills/aaaaqwq/agi-super-team/code-review-quality/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-quality"><img src="https://agentmods.dev/badge/skills/aaaaqwq/agi-super-team/code-review-quality.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 Excessive Agency · line 163 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 | $0.00033 | $0.01598 |
| Opus 5 | $0.00016 | $0.00799 |
| Sonnet 5 | $0.00007 | $0.00320 |
| Haiku 4.5 | $0.00003 | $0.00160 |
Grade A, and why
code-review-quality 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 3d 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-quality — 92% identical, 9 lines differ
How it starts
The opening of the file, as written. The whole thing — 233 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Review Quality
<default_to_action> When reviewing code or establishing review practices:
- PRIORITIZE feedback: 🔴 Blocker (must fix) → 🟡 Major → 🟢 Minor → 💡 Suggestion
- FOCUS on: Bugs, security, testability, maintainability (not style preferences)
- ASK questions over commands: "Have you considered...?" > "Change this to..."
- PROVIDE context: Why this matters, not just what to change
- LIMIT scope: Review < 400 lines at a time for effectiveness
Quick Review Checklist:
- Logic: Does it work correctly? Edge cases handled?
- Security: Input validation? Auth checks? Injection risks?
- Testability: Can this be tested? Is it tested?
- Maintainability: Clear naming? Single responsibility? DRY?
- Performance: O(n²) loops? N+1 queries? Memory leaks?
Critical Success Factors:
- Review the code, not the person
- Catching bugs > nitpicking style
- Fast feedback (< 24h) > thorough feedback </default_to_action>
Quick Reference Card
When to Use
- PR code reviews
- Pair programming feedback
- Establishing team review standards
- Mentoring developers
Feedback Priority Levels
| Level | Icon | Meaning | Action |
|---|---|---|---|
| Blocker | 🔴 | Bug/security/crash | Must fix before merge |
| Major | 🟡 | Logic issue/test gap | Should fix before merge |
| Minor | 🟢 | Style/naming | Nice to fix |
| Suggestion | 💡 | Alternative approach | Consider for future |
Review Scope Limits
| Lines Changed | Recommendation |
|---|---|
| < 200 | Single review session |
| 200-400 | Review in chunks |
| > 400 | Request PR split |
What to Focus On
| ✅ Review | ❌ Skip |
|---|---|
| Logic correctness | Formatting (use linter) |
| Security risks | Naming preferences |
| Test coverage | Architecture debates |
| Performance issues | Style opinions |
| Error handling | Trivial changes |
Feedback Templates
Blocker (Must Fix)
🔴 **BLOCKER: SQL Injection Risk**
This query is vulnerable to SQL injection:
```javascript
db.query(`SELECT * FROM users WHERE id = ${userId}`)
Fix: Use parameterized queries:
db.query('SELECT * FROM users WHERE id = ?', [userId])
Why: User input directly in SQL allows attackers to execute arbitrary queries.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 233 lines · 33 tokens per session scan A 7dca0660a1e6
code-review-quality is a skill published in the GitHub repository aAAaqwq/AGI-Super-Team (91 stars, last pushed yesterday), licensed MIT. It adds 33 tokens to every session and 1,598 once invoked, about $0.0002 per session on Opus 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
code-review-quality
Conduct context-driven code reviews focusing on quality, testability, and maintainability. Use when reviewing code, providing feedback, or establishing review practices.
dos-verify-done-claims
Before accepting an agent's 'done / shipped / fixed' claim, verify it against ground truth (git ancestry + the commit's own diff) using the DOS kernel's dos verify and dos commit-audit — never the agent's own narration.
code-review
Use to judge a concrete diff, branch, or GitHub PR on its own merits with no rsc-SDD spec/plan chain to key off — the spec-less giving pass behind /code-review: only findings you can defend, one verdict, read-only unless --comment or --fix. NOT the SDD gate keyed to 02-DOCS/wiki/sdd/ that also processes incoming…
structured-code-review
Performs a structured five-stage code review covering requirements compliance, correctness, code quality, testing, and security/performance. Each stage uses targeted checklists and categorized feedback (Blocker/Major/Minor/Nit) with actionable suggestions and rationale. Use when the user asks for code review, PR…
code-review
The depth half of a review - the dimensions a diff is read against (correctness, boundaries, concurrency, failure paths, secrets, data access, structure, test quality) and the rule that a finding is refuted before it is reported. The verdict stays with the reviewer agent. Use when reviewing a diff or a pull request…
deslop
The optimization pass, defined - delete before you add, one smell class per pass, behaviour pinned by a test that ran BEFORE the edit. Lints a SKILL.md and prose by the same instinct. Use for the per-story optimization pass or when code has grown noisy without growing capable.