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-pcap-protocolgit 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-pcap-protocol)<a href="https://agentmods.dev/skills/zhaoxuya520/reverse-skill/competition-pcap-protocol"><img src="https://agentmods.dev/badge/skills/zhaoxuya520/reverse-skill/competition-pcap-protocol/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-pcap-protocol"><img src="https://agentmods.dev/badge/skills/zhaoxuya520/reverse-skill/competition-pcap-protocol.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 | $0.00117 | $0.00689 |
| Opus 5 | $0.00059 | $0.00345 |
| Sonnet 5 | $0.00023 | $0.00138 |
| Haiku 4.5 | $0.00012 | $0.00069 |
Grade A, and why
competition-pcap-protocol 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-pcap-protocol — 100% identical, 0 lines differ
- competition-pcap-protocol — 100% identical, 0 lines differ
- competition-pcap-protocol — 100% identical, 0 lines differ
- competition-pcap-protocol — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competition PCAP Protocol
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 evidence sits inside packet order, protocol framing, or stream reconstruction rather than a single IOC or host log.
Reply in Simplified Chinese unless the user explicitly requests English.
Quick Start
- Establish the capture boundaries first: hosts, time span, interfaces, missing packets, retransmits, and stream count.
- Group traffic into sessions before decoding payload semantics.
- Record protocol framing, sequence, timing, and transferred artifacts together instead of as isolated packets.
- Correlate packet evidence with host, malware, or app behavior only after the session is reconstructed.
- Reproduce the smallest decoded stream or transferred artifact that proves the challenge path.
Workflow
1. Build The Session Map
- Identify endpoints, protocols, ports, TLS handshakes, DNS lookups, websocket upgrades, and long-lived streams.
- Note missing capture coverage, asymmetric routing, packet loss, or reassembly issues before drawing conclusions.
- Separate control channels, bulk transfers, keepalives, and noise.
2. Decode The Protocol Boundary
- Reassemble TCP streams or UDP conversations before interpreting fields.
- Recover framing, message order, custom headers, binary fields, compression, encryption boundaries, and object transfers.
- Keep payload direction, timing, and session state aligned with each decoded message.
3. Tie Packets To Behavior
- Show which packet sequence maps to which host event, malware branch, login flow, upload, exfiltration step, or command channel.
- Distinguish protocol recognition from artifact recovery: naming HTTP, DNS, or a custom C2 is not enough without decoded content or proven downstream effect.
- If the task becomes mostly a host timeline problem after decode, switch to the tighter forensic timeline 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 · 53 lines · 117 tokens per session scan A 18285bb445a8
competition-pcap-protocol is a skill published in the GitHub repository zhaoxuya520/reverse-skill (35,183 stars, last pushed 6d ago), licensed MIT. It adds 117 tokens to every session and 689 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.
Other skills, from other repositories
debug-optimize-lcp
Guides debugging and optimizing Largest Contentful Paint (LCP) using Chrome DevTools MCP tools. Use this skill whenever the user asks about LCP performance, slow page loads, Core Web Vitals optimization, or wants to understand why their page's main content takes too long to appear. Also use when the user mentions…
systematic-debugging
Use when debugging a failing test, build error, or runtime issue that isn't immediately obvious. Guides a 4-phase root cause analysis instead of random fix attempts.
diagnose
Trace from a reproduced symptom to the source code that causes it. Pin the specific file and approximate line, rate confidence in the cause and clarity of the fix independently, and always propose a concrete fix.
repro-admin
Reproduce an EmDash admin UI bug. Attach a container, start the demo dev server, drive the admin with agent-browser using the dev-bypass session, and capture the reproduction as screenshots plus a replayable transcript.
log-error-digest
Analyze log files to troubleshoot errors, identify peak error periods, and produce error clustering, frequency statistics, and time distribution reports. Supports JSON, syslog, and Nginx formats with automatic detection. Use when a user uploads a .log file and asks to analyze errors, find patterns, debug issues, or…
byted-util-volcengine-detect-retry
An orchestration workflow for Volcengine Cloud Detect, a service that checks websites or network endpoints from test locations.