ContextForge Drafts AI Agent Instruction Files by Parsing Your Repo Directly

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Developers adopting AI coding agents like Cursor, Claude Code, or Codex often find the tools misread project conventions within the first two weeks of use, producing code that does not match the existing repo structure. Most AI agents can read dedicated instruction files such as CLAUDE.md or AGENTS.md, but writing accurate ones manually takes 30 to 90 minutes per repository and tends to go stale. ContextForge addresses this by parsing a repo's file tree and package.json to extract verifiable facts — including the package manager, framework, test runner, and CI system — before any AI model is involved. Each extracted fact is tagged as detected, inferred, or unknown, and uncertain details are surfaced as open questions rather than fabricated conventions. The tool also returns a Context Score out of 100 reflecting how much it could reliably determine, and stores no repository data, requiring only a pasted file tree to operate.

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