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 guccig4366/xbsReverseSkill --skill web-reverse-algorithmgit clone --depth 1 https://github.com/guccig4366/xbsReverseSkillWrote 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/guccig4366/xbsreverseskill/web-reverse-algorithm)<a href="https://agentmods.dev/skills/guccig4366/xbsreverseskill/web-reverse-algorithm"><img src="https://agentmods.dev/badge/skills/guccig4366/xbsreverseskill/web-reverse-algorithm/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/guccig4366/xbsreverseskill/web-reverse-algorithm"><img src="https://agentmods.dev/badge/skills/guccig4366/xbsreverseskill/web-reverse-algorithm.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 | $0.00226 | $0.02238 |
| Opus 5.5 | $0.00090 | $0.00895 |
| Sonnet 5.5 | $0.00045 | $0.00448 |
| Haiku 4.5 | $0.00023 | $0.00224 |
Grade A, and why
web-reverse-algorithm 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 1mo 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.
This is a copy
100% identical to web-reverse-algorithm — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 218 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Web 逆向纯算
这项技能不是“给一个固定公式”，而是把资料库里的方法层、题型层、训练层、工程化层压成一套总入口。
先把任务压缩成这条闭环，再决定读哪份 references、走哪条路径、写哪种落地代码：
最终请求 / 最终 cookie / 最终 verify / 最终 WS 帧
-> writer
-> builder
-> entry
-> source
核心原则
- 先找最终写出点，不先读混淆大文件。
- 先存中间值，不先猜算法名。
- 先缩小执行范围，再补环境。
- 先证明输入输出边界，再决定是否整体迁移。
- 先把结果整理成可复用结构，再继续做版本适配。
使用顺序
1. 先判题型
把目标先归到下面之一：
- 标准签名 / 标准摘要题
- 混合加密 / 密钥包装题
- Cookie / Header / 多参数联动题
- JSVMP / VMP / 强混淆纯算题
- Wasm / Protobuf / WebSocket / 二进制协议题
- 验证码 / 风控 / challenge 题
如果还没分清，先读 references/01-decision-tree.md。
2. 再判当前阻塞点
优先判断你卡在下面哪一类：
- 入口没找对
- 原始串或原始 payload 没对齐
- 中间数组 / 中间对象没采到
- 运行时依赖没补齐
- 图像线和参数线没拆开
- 协议边界没证明
遇到这一步拿不准时，优先读 references/04-debug-env-playbook.md。
3. 按题型选路线
标准签名 / 混合加密 / Cookie / Header / 国密
适用信号：
- 输出长度规整
md5/sha1/hmac/aes/rsa/sm3/sm4token&t&appKey&dataparams + encSecKeydocument.cookie或 header 明显可追
优先读取 references/02-algorithm-families.md。
JSVMP / VMP / 小红书 / a_bogus / 多参数复杂纯算
适用信号：
- 大数组、解释器、
for(;;)+switch - 位运算密集、状态数组、寄存器式写法
window._webmsxyw、__TENCENT_CHAOS_VM、byted_acrawler一类入口
优先读取 references/02-algorithm-families.md 和 references/04-debug-env-playbook.md。
Wasm / Protobuf / WebSocket / challenge 协议
适用信号：
WebAssembly.instantiateapplication/x-protobuf- 二进制响应、导出函数、首包/验证包分段
优先读取 references/02-algorithm-families.md 和 references/03-captcha-families.md。
验证码 / 风控 / challenge / verify
永远先拆 5 条线：
- 初始化 / challenge 线
- 图像或题面识别线
- 参数 builder 线
- 环境 / 指纹 / collect 线
- 最终 verify 线
优先读取 references/03-captcha-families.md。
统一工作流
1. 锁定最终写出点
优先从这些位置切：
fetchXMLHttpRequest.sendsetRequestHeaderdocument.cookieJSON.stringify- verify 提交点
- WebSocket 首包或验证包发送点
What ships with it
13 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.
- agents/openai.yaml 302 B
- references/01-decision-tree.md 3.9 KB
- references/02-algorithm-families.md 3.9 KB
- references/03-captcha-families.md 2.8 KB
- references/04-debug-env-playbook.md 2.9 KB
- references/05-training-routes.md 2.4 KB
- references/06-engineering-maintenance.md 2.3 KB
- references/captcha-patterns.md 2.8 KB
- references/debug-env-checkpoints.md 2.5 KB
- references/purecalc-patterns.md 2.6 KB
- references/route-map.md 3.9 KB
- scripts/__pycache__/new_case_scaffold.cpython-312.pyc 12 KB
- scripts/new_case_scaffold.py 11 KB runs code
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.
- 1mo ago First seen · 218 lines · 226 tokens per session scan A 366e236853bc
web-reverse-algorithm is a skill published in the GitHub repository guccig4366/xbsReverseSkill (7 stars, last pushed 5d ago), licensed MIT. It adds 226 tokens to every session and 2,238 once invoked, about $0.0009 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to web-reverse-algorithm, differing in 0 lines, and is treated as a copy.
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