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Hidden Rx Memory Reconstruction

Community
manyuegong33
hidden-rx-memory-reconstruction

Beginner-friendly workflow for Executable anonymous mappings, memfd, JIT pages, decrypted code, and runtime reconstruction. Extracts general methods and evidence practices without depending on any author, private repository, personal path, secret, or branded prompt. Use when a reverse-engineering task needs reliable observation, loader analysis, runtime evidence, dump validation, crash attribution, tool setup, or reproducible reporting.

Overview

Publishermanyuegong33
Repositoryr0crawl_skills
Skill namehidden-rx-memory-reconstruction
Stars
340
Forks
120
Bundled files
1
Links
  • 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.

  • 1 bundled files

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

  • Open source

    Published by manyuegong33 on GitHub. Read the source before you install it.

Installation

Install the Hidden Rx Memory Reconstruction 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.
    https://github.com/manyuegong33/r0crawl_skills/tree/main/skills/hidden-rx-memory-reconstruction
  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/manyuegong33/r0crawl_skills.git /tmp/r0crawl_skills
mkdir -p .claude/skills
cp -r /tmp/r0crawl_skills/skills/hidden-rx-memory-reconstruction .claude/skills/hidden-rx-memory-reconstruction
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hidden Rx Memory Reconstruction 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 Hidden Rx Memory Reconstruction 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 Hidden Rx Memory Reconstruction 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.

Executable anonymous mappings, memfd, JIT pages, decrypted code, and runtime reconstruction

Beginner mode

Explain the object, the observation question, the required evidence, the first tool, and the success criterion before using advanced terminology.

Workflow

  1. Record sample hash, version, architecture, environment, entry action, and objective.
  2. Preserve raw artifacts before modifying, decoding, dumping, or patching anything.
  3. Perform the smallest observation that can distinguish competing hypotheses.
  4. Correlate static references with runtime stacks, registers, mappings, files, traffic, and outputs.
  5. Record commands, tool versions, paths, offsets, timestamps, and first-difference locations.
  6. Validate the result with a clean baseline, repeat run, edge case, and consumer tool or independent observation.

Quality gates

  • A string or one log line is not a call chain.
  • A dump is not valid until its structure, mappings, imports/relocations, and consumer-tool behavior agree.
  • A patch or observation hook is not stable until cold start, warm start, repeated calls, and clean baseline are compared.
  • If a prerequisite is missing, report the smallest next artifact instead of changing the environment blindly.

Deliverables

  • Beginner summary.
  • Evidence table and confidence level.
  • Technical chain and unresolved hypotheses.
  • Reproducible command, script, fixture, dump validation, or report.
  • Limitations, rollback notes, and next action.

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 Hidden Rx Memory Reconstruction AI skill do?

Beginner-friendly workflow for Executable anonymous mappings, memfd, JIT pages, decrypted code, and runtime reconstruction. Extracts general methods and evidence practices without depending on any author, private repository, personal path, secret, or branded prompt. Use when a reverse-engineering task needs reliable observation, loader analysis, runtime evidence, dump validation, crash attribution, tool setup, or reproducible reporting.

Why use Hidden Rx Memory Reconstruction on TypingMind?

Because you install it once and use it with any model. Hidden Rx Memory Reconstruction 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 Hidden Rx Memory Reconstruction in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/manyuegong33/r0crawl_skills/tree/main/skills/hidden-rx-memory-reconstruction. 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 Hidden Rx Memory Reconstruction?

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 Hidden Rx Memory Reconstruction?

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

Is the Hidden Rx Memory Reconstruction AI skill free?

It is published on GitHub by manyuegong33. Check the repository for licensing terms. 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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