Reverse Skill is a routing package for AI coding agents that selects appropriate reverse-engineering, penetration-testing, and security-research methods and tools for a given target. It is used for tasks involving APKs, binaries, frontend JavaScript, packet captures, CTF challenges, and authorized penetration testing. Its catalogue add-ons provide the skills and instructions that guide these workflows.
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 zhaoxuya520/reverse-skill --skill competition-runtime-routinggit clone --depth 1 https://github.com/zhaoxuya520/reverse-skillWrote 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/zhaoxuya520/reverse-skill/competition-runtime-routing)<a href="https://agentmods.dev/skills/zhaoxuya520/reverse-skill/competition-runtime-routing"><img src="https://agentmods.dev/badge/skills/zhaoxuya520/reverse-skill/competition-runtime-routing/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/zhaoxuya520/reverse-skill/competition-runtime-routing"><img src="https://agentmods.dev/badge/skills/zhaoxuya520/reverse-skill/competition-runtime-routing.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 | $0.00120 | $0.00682 |
| Opus 5 | $0.00060 | $0.00341 |
| Sonnet 5 | $0.00024 | $0.00136 |
| Haiku 4.5 | $0.00012 | $0.00068 |
Grade A, and why
competition-runtime-routing 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 9d 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
4 near-identical copies found in the catalogue:
- competition-runtime-routing — 100% identical, 0 lines differ
- competition-runtime-routing — 100% identical, 0 lines differ
- competition-runtime-routing — 100% identical, 0 lines differ
- competition-runtime-routing — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competition Runtime Routing
Use this skill only as a downstream specialization after $ctf-sandbox-orchestrator is already active and has established sandbox assumptions, node ownership, and evidence priorities. If that has not happened yet, return to $ctf-sandbox-orchestrator first.
Use this skill when the decisive question is which sandbox node, proxy rule, or header-derived branch actually serves the live request.
Reply in Simplified Chinese unless the user explicitly requests English.
Quick Start
- Assume every presented hostname, domain, and node belongs to the sandbox unless the challenge path disproves it.
- Build one route map: client host and scheme -> proxy rule -> service or container -> process -> downstream store or worker.
- Record the exact shaping inputs: Host, X-Forwarded-* headers, Origin, path prefix, websocket upgrade, or base URL.
- Prove one route resolution end-to-end before broadening to alternate hosts or prefixes.
- Re-run the same request with one routing input changed at a time.
Workflow
1. Map Route Inputs
- Inspect vhost rules, reverse proxies, forwarded headers, path-prefix rewrites, upstream pools, and websocket or SSE upgrades.
- Note which parts of the request influence routing or app behavior: host, scheme, port, path, prefix, cookie scope, or origin.
- Treat public-looking domains, cloud hostnames, and separate VPS nodes as sandbox routing fixtures first.
2. Trace Route To Live Consumer
- Map hostname to proxy rule to container or process to port to downstream service.
- Compare checked-in proxy intent against live listeners, mounted configs, runtime env, and observed traffic.
- Keep headers, proxy config, and live request traces tied together in one evidence chain.
3. Prove The Decisive Deviation
- Reduce the result to the smallest request shape that flips host-based routing, tenant selection, cookie scope, or upstream target.
- Distinguish route resolution from application auth logic; prove where each decision really happens.
- If the problem shifts from routing to general web state or container runtime drift, switch back to the broader parent skill.
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.
- 9d ago First seen · 52 lines · 120 tokens per session scan A 2d49d8e943f3
competition-runtime-routing is a skill published in the GitHub repository zhaoxuya520/reverse-skill (35,183 stars, last pushed 5d ago), licensed MIT. It adds 120 tokens to every session and 682 once invoked, about $0.0006 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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