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 MatrixFounder/Agentic-development --skill skill-reverse-engineeringgit clone --depth 1 https://github.com/MatrixFounder/Agentic-developmentWrote 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/matrixfounder/agentic-development/skill-reverse-engineering)<a href="https://agentmods.dev/skills/matrixfounder/agentic-development/skill-reverse-engineering"><img src="https://agentmods.dev/badge/skills/matrixfounder/agentic-development/skill-reverse-engineering/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/matrixfounder/agentic-development/skill-reverse-engineering"><img src="https://agentmods.dev/badge/skills/matrixfounder/agentic-development/skill-reverse-engineering.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00015 | $0.00862 |
| Opus 5.5 | $0.00006 | $0.00345 |
| Sonnet 5.5 | $0.00003 | $0.00172 |
| Haiku 4.5 | $0.00002 | $0.00086 |
Grade A, and why
skill-reverse-engineering 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 13d 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reverse Engineering Skill
Purpose
Recover the mental model of a project from its codebase when documentation is outdated or missing.
When to Use
- Documentation-code mismatch detected
- New team member onboarding
- Post-"quick fix" cleanup
Strategy: Automated Scan + Iterative Analysis
Phase 1: Automated Directory Scan
Tool: scripts/scan_structure.py
Usage:
python3 .agent/skills/skill-reverse-engineering/scripts/scan_structure.py . --depth 2
Goal:
- Get high-level overview of project structure.
- Identify dominant languages and components.
- Avoid context overflow by NOT reading all files.
Phase 2: Local Analysis (Per-Directory)
For each key component identified in Phase 1:
- List files.
- Sample 2-3 representative files (read content).
- Generate Local Summary:
- Purpose
- Key Classes
- Dependencies
Phase 3: Global Synthesis
Combine local summaries to update docs/ARCHITECTURE.md:
- Update Directory Structure
- Update Component Map
- Identify Architecture Drift (Code != Docs)
Output Artifacts
1. ARCHITECTURE.md Update
Generate diffs for:
- Directory Structure
- Component Map
- Data Flow
Figures. Write the text of a section first. Then draw its figure from that text with
mermaid-authoring-guidelines; load the skill before the first figure. Each element of the figure
has a supporting line in that text. A relation found only in the code goes into the text first, or
stays out of the figure. A figure in a section this update leaves unchanged stays as it is.
Why. The skill's fidelity step (Step 6) accepts a line of the document as support. A line of code is not one.
2. KNOWN_ISSUES.md Updates
Identify:
TODO/HACKcomments indicating tech debt.- Discrepancies between implementation and docs.
Filing format (thin index). docs/KNOWN_ISSUES.md is a hand-maintained thin index, not a
flat checklist — do NOT append - [ ] lines to it. The authoritative format contract lives in the
known-issues-format skill (artifact-management, TIER 0, delegates to it) — follow it:
- If
docs/KNOWN_ISSUES.mddoes not exist yet, materialize it fromknown-issues-format'sassets/templates/known_issues_md_template.mdfirst (create-if-absent). - File each finding as its own
docs/issues/<slug>.md(frontmatter + H1 + body) plus one index line under the matching## <category>heading — edit both in lockstep. - If a finding needs a category/prefix the project's ledger doesn't have yet, add a new prefix → category row to that ledger's Rules / Conventions table before filing.
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.
- 13d ago Changed · +9 lines ea77d977f79b
- 1mo ago First seen · 87 lines · 15 tokens per session scan A f7c3d3f72e2b
skill-reverse-engineering is a skill published in the GitHub repository MatrixFounder/Agentic-development (6 stars, last pushed yesterday), licensed Apache-2.0. It adds 15 tokens to every session and 862 once invoked, about $0.0001 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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