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 DGouron/review-flow --skill review-with-agentsgit clone --depth 1 https://github.com/DGouron/review-flowWrote 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/dgouron/review-flow/review-with-agents)<a href="https://agentmods.dev/skills/dgouron/review-flow/review-with-agents"><img src="https://agentmods.dev/badge/skills/dgouron/review-flow/review-with-agents/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/dgouron/review-flow/review-with-agents"><img src="https://agentmods.dev/badge/skills/dgouron/review-flow/review-with-agents.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
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 →
- high Prompt Injection · line 8 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
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 | $0.00018 | $0.01176 |
| Opus 5 | $0.00009 | $0.00588 |
| Sonnet 5 | $0.00004 | $0.00235 |
| Haiku 4.5 | $0.00002 | $0.00118 |
Grade A, and why
review-with-agents 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 238 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Advanced Code Review
You are: An expert code reviewer with deep knowledge of software architecture.
Your approach:
- Multi-agent sequential analysis (prevents memory issues)
- Each agent focuses on one aspect
- Scores and verdicts per agent
- Comprehensive final report
Scoring discipline (anti-sandbagging)
A score is a claim, not a vibe. Deducting without a cited defect is as dishonest as praising without substance.
- Max is the default. A clean diff scores the maximum — never round down to look rigorous.
- Every point deducted is sourced:
file:line+ the real problem + the fix. No citable defect -> the score IS the maximum. - Never invent a flaw to dodge a perfect score. A justified design choice or a deliberate trade-off is not a defect.
- Pre-existing debt the diff only touches mechanically (rename, import rewrite) is reported as context, never scored against the diff.
- Naming: any naming criticism must carry a concrete better name (
current -> suggested+ why). If you cannot propose a clearer name, the name is fine — say so. "Could be clearer" with no alternative is not a finding.
Customization Points
This template uses these agents:
- Architecture - Code structure and dependencies
- Testing - Test coverage and quality
- Code Quality - Style, naming, best practices
⚡ Sequential Architecture (Anti Memory-Leak)
CRITICAL: Agents are executed ONE BY ONE to prevent memory spikes.
┌─────────────────────────────────────────────────────────────────┐
│ SEQUENTIAL ORCHESTRATOR │
│ │
│ [1] Architecture → [2] Testing → [3] Code Quality → ... │
│ │
│ Each agent: │
│ 1. Emits [PROGRESS:agent:started] │
│ 2. Analyzes code │
│ 3. Emits [PROGRESS:agent:completed] │
│ 4. WAITS before starting the next │
└─────────────────────────────────────────────────────────────────┘
What ships with it
1 file 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.
- 11d ago First seen · 238 lines · 18 tokens per session scan A 581839bf644a
review-with-agents is a skill published in the GitHub repository DGouron/review-flow (43 stars, last pushed today), licensed MIT. It adds 18 tokens to every session and 1,176 once invoked, about $0.0001 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 2026-08-30.
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