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-relay-coercion-chaingit 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-relay-coercion-chain)<a href="https://agentmods.dev/skills/zhaoxuya520/reverse-skill/competition-relay-coercion-chain"><img src="https://agentmods.dev/badge/skills/zhaoxuya520/reverse-skill/competition-relay-coercion-chain/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-relay-coercion-chain"><img src="https://agentmods.dev/badge/skills/zhaoxuya520/reverse-skill/competition-relay-coercion-chain.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 | $0.00119 | $0.00633 |
| Opus 5 | $0.00060 | $0.00316 |
| Sonnet 5 | $0.00024 | $0.00127 |
| Haiku 4.5 | $0.00012 | $0.00063 |
Grade A, and why
competition-relay-coercion-chain 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.
Copies of this mod
4 near-identical copies found in the catalogue:
- competition-relay-coercion-chain — 100% identical, 0 lines differ
- competition-relay-coercion-chain — 100% identical, 0 lines differ
- competition-relay-coercion-chain — 100% identical, 0 lines differ
- competition-relay-coercion-chain — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competition Relay Coercion Chain
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 hard part is proving the full chain from forced authentication to a service that actually accepts the relayed identity.
Reply in Simplified Chinese unless the user explicitly requests English.
Quick Start
- Split the chain into coercion source, captured auth, relay target, acceptance point, and resulting effect.
- Record transport, protocol, and service identity at each hop.
- Separate forced-auth generation from relay success and from downstream privilege.
- Keep coercion trigger, relay transcript, and accepting service in one evidence chain.
- Reproduce the smallest coercion-to-acceptance path that proves the decisive edge.
Workflow
1. Map The Coercion Source
- Identify the service, RPC, file path, printer path, WebDAV edge, or protocol trigger that forces authentication.
- Record source host, coerced principal, transport, and any environmental preconditions.
- Keep one compact note of exactly what causes the auth to leave the source.
2. Trace The Relay Target
- Record where the authentication lands, how it is forwarded, and which protocol or service consumes it.
- Distinguish capture-only, replay-only, and actual relay acceptance.
- Keep service name, target host, protocol, relay transcript, and acceptance response tied together.
3. Reduce To The Decisive Relay Chain
- Compress the result to the smallest sequence: coercion trigger -> relayed auth -> accepted service -> resulting privilege or artifact.
- State clearly whether the decisive weakness lives in the coercion source, the relay target, signing settings, or the accepted downstream service.
- If the path ultimately becomes a certificate-enrollment issue or a pure Kerberos delegation edge, hand off to the tighter specialized 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.
- 13d ago First seen · 51 lines · 119 tokens per session scan A 0902a70e320e
competition-relay-coercion-chain is a skill published in the GitHub repository zhaoxuya520/reverse-skill (35,595 stars, last pushed 9d ago), licensed MIT. It adds 119 tokens to every session and 633 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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