Competition Bundle Sourcemap Recovery logo

Competition Bundle Sourcemap Recovery

CommunityPopular
zhaoxuya520
competition-bundle-sourcemap-recovery

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for source maps, build manifests, chunk registries, emitted bundles, obfuscated loader flow, and frontend runtime recovery. Use when the user asks to reconstruct served JavaScript structure, inspect source maps or chunk maps, trace bundle loading, recover hidden routes or APIs from emitted assets, or explain runtime behavior from built frontend artifacts. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

Overview

Publisherzhaoxuya520
Repositoryreverse-skill
Skill namecompetition-bundle-sourcemap-recovery
Stars
36.3K
Forks
5K
Bundled files
2
LicenseMIT
Links
Skill sourceRepository
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by zhaoxuya520 on GitHub. Read the source before you install it.

Installation

Install the Competition Bundle Sourcemap Recovery AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/zhaoxuya520/reverse-skill.git /tmp/reverse-skill
mkdir -p .claude/skills
cp -r /tmp/reverse-skill/CTF-Sandbox-Orchestrator/competition-bundle-sourcemap-recovery .claude/skills/competition-bundle-sourcemap-recovery
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Competition Bundle Sourcemap Recovery in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Competition Bundle Sourcemap Recovery on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Competition Bundle Sourcemap Recovery is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Competition Bundle Sourcemap Recovery

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 runtime truth lives in built assets, source maps, chunk tables, or obfuscated loader flow rather than in checked-in source alone.

Reply in Simplified Chinese unless the user explicitly requests English.

Quick Start

  1. Start from the served artifact set: entry HTML, build manifest, bootstrap bundle, chunk map, and source maps.
  2. Record chunk ids, route chunks, loader functions, endpoint strings, and config keys before broad manual deobfuscation.
  3. Reconstruct the smallest runtime graph that explains which asset executes now.
  4. Keep served artifact truth separate from repository source unless parity is proven.
  5. Reproduce the smallest asset-to-runtime boundary that proves the decisive behavior.

Workflow

1. Map The Served Artifact Set

  • Record entry HTML, script tags, preload hints, manifest files, asset map, chunk registry, and source map URLs.
  • Note framework-specific artifacts such as route manifests, client reference manifests, or lazy-loader tables when present.
  • Keep emitted filenames, hash suffixes, and route ownership tied together.

2. Reconstruct Runtime Structure

  • Follow bootstrap code, chunk loaders, module registry, string decoders, and lazy import boundaries.
  • Use source maps, manifest files, and stable symbol clusters to recover route names, API calls, feature flags, and hidden panels.
  • Distinguish build-time intent from the bundle that is actively served now.

3. Reduce To The Decisive Bundle Path

  • Compress the result to the smallest sequence: served asset -> loader path -> module or symbol -> runtime effect.
  • State clearly whether the decisive weakness lives in manifest drift, chunk loading, hidden route code, string decoding, or stale source assumptions.
  • If the task shifts from built assets to SSR or template enforcement, hand back to the tighter template-render skill.

Read This Reference

  • Load references/bundle-sourcemap-recovery.md for the artifact checklist, deobfuscation checklist, and evidence packaging.

What To Preserve

  • Served filenames, chunk ids, manifest entries, source map paths, recovered symbols, and endpoint strings
  • The exact executing bundle or module that proves the runtime branch
  • One minimal asset-to-runtime sequence that reaches the decisive effect

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Competition Bundle Sourcemap Recovery AI skill do?

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for source maps, build manifests, chunk registries, emitted bundles, obfuscated loader flow, and frontend runtime recovery. Use when the user asks to reconstruct served JavaScript structure, inspect source maps or chunk maps, trace bundle loading, recover hidden routes or APIs from emitted assets, or explain runtime behavior from built frontend artifacts. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

Why use Competition Bundle Sourcemap Recovery on TypingMind?

Because you install it once and use it with any model. Competition Bundle Sourcemap Recovery is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Competition Bundle Sourcemap Recovery in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zhaoxuya520/reverse-skill/tree/main/CTF-Sandbox-Orchestrator/competition-bundle-sourcemap-recovery. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Competition Bundle Sourcemap Recovery?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Competition Bundle Sourcemap Recovery?

As many as you like. As long as a model supports skills, you can use Competition Bundle Sourcemap Recovery with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Competition Bundle Sourcemap Recovery AI skill free?

Yes. It is published on GitHub by zhaoxuya520 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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