albertan017/LLM4Decompile
Reverse Engineering: Decompiling Binary Code with Large Language Models
The missing cognitive primitive for AI agents. Decompose any text into classified semantic units — authority, risk, attention, entities. No LLM. Deterministic.
Appears on
Quick read
Latest capture 2026-09-13 03:08
Archive status reflects the last catalog sync, not a maintenance assessment. Check recent releases, issue responses, and fit for your project with the repository shortlisting checklist.
1 path
Agent instructions and tool configuration found in this repository.
Claude Code
9 observed captures since 2026-05-22. Observed captures are shown by default.
Stars from first capture +1
Observed captures only
All tracked data
Observed snapshots
Observed snapshots
Nearest indexed repositories by embedding similarity.
Reverse Engineering: Decompiling Binary Code with Large Language Models
The open document intelligence platform for builders and hackers - DMS for the agentic world
ExtractThinker is a Document Intelligence library for LLMs, offering ORM-style interaction for flexible and powerful document workflows.
Code research platform for AI agents; find, understand, and prove context across your code and all of GitHub, in a fraction of the tokens. One toolset, MCP or CLI
Polyglot document intelligence with a Rust core: extract text, metadata, images, tables, and structured data from 106 formats across 140 file extensions, plus code intelligence for 371 languages. Fifteen bindings, with CLI, REST API, and MCP server.
Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 60-95% fewer tokens, same answers. Library, proxy, MCP server.