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 agentmods add skills/shinpr/claude-code-workflows/recipe-reverse-engineernpx skills add shinpr/claude-code-workflows --skill recipe-reverse-engineergit clone --depth 1 https://github.com/shinpr/claude-code-workflowsWrote 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/shinpr/claude-code-workflows/recipe-reverse-engineer)<a href="https://agentmods.dev/skills/shinpr/claude-code-workflows/recipe-reverse-engineer"><img src="https://agentmods.dev/badge/skills/shinpr/claude-code-workflows/recipe-reverse-engineer.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00026 | $0.03712 |
| Opus 5 | $0.00013 | $0.01856 |
| Sonnet 5 | $0.00005 | $0.00742 |
| Haiku 4.5 | $0.00003 | $0.00371 |
Grade A, and why
recipe-reverse-engineer 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 4d 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 — 400 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Explicit User Instruction: The user explicitly instructs and authorizes every subagent call named in this recipe. Execute each applicable call when its prerequisites are met.
Execute Skill: llm-friendly-context before writing Agent prompts, handoffs, or generated artifacts. Execute Skill: subagents-orchestration-guide before making workflow decisions, invoking agents, or resolving findings.
Context: Reverse engineering workflow to create documentation from existing code
Target: $ARGUMENTS
Orchestrator Definition
Core Identity: "I am an orchestrator."
Local authority gate: Make this recipe's workflow decisions and validate each returned result directly; delegate semantic deliverable production to the named specialist.
Review Resolution Gate [MANDATORY]: Resolve every actionable deliverable-review finding through subagents-orchestration-guide Review Resolution before correction or progression.
Before the first finding disposition, read references/review-resolution.md from the loaded subagents-orchestration-guide skill.
Execution Protocol:
- Invoke named specialists for deliverable production — pass deliverable paths between them and validate their results (see subagents-orchestration-guide "Orchestrator Execution Boundary")
- Process one step at a time: Execute steps sequentially within each unit (2 → 3 → 4 → 5). Each step's output is the required input for the next step. Complete all steps for one unit before starting the next
- Preserve evidence while bridging outputs — copy the fields required by the next specialist in their declared form; apply Review Resolution before routing any correction
At each Agent invocation below, build the prompt as a mechanical extraction: copy the named source values into the exact fields, apply only the declared serialization, then invoke immediately.
Execution Gate: Complete Phase 1 before Phase 2. Within each phase, complete one unit's generation, verification, review, and required revision to convergence before starting the next unit. Advance only when the current step's stated output and quality gate are satisfied. At each loop boundary, select the first unit in the current phase's declared order whose Unit Completion conditions are unsatisfied and that is not logged as a generation failure. A document path proves generation only.
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.
- 4d ago First seen · 400 lines · 26 tokens per session scan A b8ad3db00fca
recipe-reverse-engineer is a skill published in the GitHub repository shinpr/claude-code-workflows (675 stars, last pushed 6d ago), licensed MIT. It adds 26 tokens to every session and 3,712 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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