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 0xrafasec/ai-workflow --skill reviewgit clone --depth 1 https://github.com/0xrafasec/ai-workflowWrote 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/0xrafasec/ai-workflow/review)<a href="https://agentmods.dev/skills/0xrafasec/ai-workflow/review"><img src="https://agentmods.dev/badge/skills/0xrafasec/ai-workflow/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/0xrafasec/ai-workflow/review"><img src="https://agentmods.dev/badge/skills/0xrafasec/ai-workflow/review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00077 | $0.00718 |
| Opus 5.5 | $0.00031 | $0.00287 |
| Sonnet 5.5 | $0.00015 | $0.00144 |
| Haiku 4.5 | $0.00008 | $0.00072 |
Grade A, and why
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.
How it starts
The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review the changes on the current branch (or the branch/PR specified in $ARGUMENTS).
Important
You are the reviewer, not the writer. Do NOT rewrite the implementation. Flag issues with specific line references.
Process
-
Determine the target:
- No argument: review current branch changes vs main
- Branch name: review that branch vs main
- PR number: fetch the PR and review its changes
-
Gather context:
git log --oneline main..HEAD git diff main...HEAD -
Check spec compliance - Find the relevant spec in
docs/specs/. Does the implementation match? -
Run stack-aware code review — Prefer Anthropic's official
code-reviewskill (fromclaude-code-plugins) if installed. Otherwise, run/sec-reviewfor security findings and spawn the architecture-reviewer subagent for architecture findings — in parallel. Load the matching language guide fromreviews/(go.md,rust.md,typescript.md,python.md) and pass it to each as stack-specific criteria, so findings cite idiomatic patterns and framework pitfalls. -
Your own review - Focus on what subagents won't catch:
- Business logic correctness - Does it solve the actual problem?
- Design decisions - Are the tradeoffs right?
- What's missing - What didn't the author think of?
- Test layer coverage - Check against
docs/TECHNICAL_DESIGN_DOCUMENT.mdTesting Strategy (if it exists) or infer from codebase patterns:- Are unit tests present for new business logic?
- Are integration tests present for new API endpoints, DB operations, or service boundaries?
- Are e2e tests present for critical user flows (if applicable)?
- Do tests follow the project's conventions (location, naming, framework)?
- Are verification criteria from the spec covered at the right test layer?
- Edge cases - Are failure modes handled?
-
Consolidate findings into a single report:
# Review: [branch/PR] ## Verdict: APPROVE | REQUEST_CHANGES | COMMENT ## Spec Compliance - [Does it match the spec? What's missing?] ## Security (from code review) - [Summary of findings] ## Architecture (from code review) - [Summary of findings] ## Stack-Specific (from code review) - [Language/framework-specific findings] ## Business Logic - [Your findings] ## Test Coverage - **Unit:** [Present/Missing — what's covered, what's not] - **Integration:** [Present/Missing/N/A — what's covered] - **E2E:** [Present/Missing/N/A — what's covered] - **Verdict:** [Adequate / Needs more coverage at X layer] ## Suggestions - [Improvements, not blockers]
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 · 71 lines · 77 tokens per session scan A c553e01b5227
review is a skill published in the GitHub repository 0xrafasec/ai-workflow (9 stars, last pushed 1mo ago), licensed MIT. It adds 77 tokens to every session and 718 once invoked, about $0.0003 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 2026-08-31.
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