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Angr Symbolic Adapter

Community
Sahil-SS9
angr-symbolic-adapter

Use angr for symbolic analysis when evidence needs justify it: constraint solving on parsers, decoders and guarded paths, with coverage honesty.

Overview

PublisherSahil-SS9
Repositoryagent-personas
Skill nameangr-symbolic-adapter
Stars
67
Forks
4
Bundled files
1
LicenseBSD-2-Clause
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 Sahil-SS9 on GitHub. Read the source before you install it.

Installation

Install the Angr Symbolic Adapter 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/Sahil-SS9/agent-personas/tree/main/skills/angr-symbolic-adapter
  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/Sahil-SS9/agent-personas.git /tmp/agent-personas
mkdir -p .claude/skills
cp -r /tmp/agent-personas/skills/angr-symbolic-adapter .claude/skills/angr-symbolic-adapter
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Angr Symbolic Adapter 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 Angr Symbolic Adapter 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 Angr Symbolic Adapter 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.

angr symbolic adapter

angr turns guarded code paths into constraint problems: recover decoders, enumerate reachable states, find inputs that reach a target. A scalpel, not a default ritual. (Adapter structure original; angr is third-party tooling referenced, not embedded.)

When to use

When a written question justifies it — e.g. what input reaches a forbidden branch, or what a transformation routine decodes — and static reading alone stalls. Requires: angr available, artefact arch supported, explicit budget agreed.

Procedure

  1. Frame the symbolic question before scripting: the target (address/state), the constraints that matter, the budget (time/steps). Record both; a solver run without them is noise.
  2. Prepare the state deliberately: correct base address, initialised registers/memory, avoided paths (e.g. anti-analysis or abort branches) chosen from static reading — the avoidance choices are assumptions and are recorded.
  3. Read results as evidence with limits: solver "not found" is not coverage proof; timeout is not safety; a found input is a witness to be verified by execution/emulation, not a conclusion.
  4. Prefer symbolic execution of small, well-understood routines (decoders, checksums, guards) over whole-program exploration; whole-program runs get explicit timeboxes and coverage accounting.
  5. Feed findings back to the static loop: recovered transformations become retypeable data or callable signatures.

Decision rules

  • Solver completion time or status never substitutes for coverage measurement; report both.
  • Found inputs are verified before becoming findings (the verification member owns that step).

Pitfalls

  • Fighting path explosion in loops/parsers with bigger budgets instead of better boundaries.
  • Presenting "no input found" as "input cannot exist".

Done

A scripted run with recorded question/budget/assumptions, witnesses or bounded negative results, and coverage notes.

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 Angr Symbolic Adapter AI skill do?

Use angr for symbolic analysis when evidence needs justify it: constraint solving on parsers, decoders and guarded paths, with coverage honesty.

Why use Angr Symbolic Adapter on TypingMind?

Because you install it once and use it with any model. Angr Symbolic Adapter 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 Angr Symbolic Adapter in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Sahil-SS9/agent-personas/tree/main/skills/angr-symbolic-adapter. 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 Angr Symbolic Adapter?

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 Angr Symbolic Adapter?

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

Is the Angr Symbolic Adapter AI skill free?

Yes. It is published on GitHub by Sahil-SS9 under the BSD-2-Clause 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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