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coderlm

Tackle 100-file projects without context window pain

Large codebases with hundreds of files overwhelm AI context windows, causing incomplete analysis and failed refactoring tasks.

Automatically decompose massive codebases into manageable chunks, with intelligent file discovery and recursive sub-agent coordination.

  • Recursive file discovery and strategic peeking
  • Automatic context window overflow protection
  • Divide-and-conquer agent decomposition
  • Built-in bashrlm output truncation
  • Works with any LLM backend

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mfkvault install coderlm

Requires the MFKVault CLI. Prefer MCP?

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🤖 Claude Code💻 Codex
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  • Works with 3 AI agents
  • Lifetime updates included
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Description

--- name: coderlm description: Use when a task involves many files (>10), the total content exceeds comfortable context size, or the task benefits from divide-and-conquer. Runs an agent that discovers files via shell tools, peeks strategically, and recursively decomposes into sub-agents. Bundles bashrlm context guards — output from high-output commands (cat, grep, rg, jq, find, ls, curl, etc.) is automatically truncated so the agent never floods its own context window. --- ## Usage ``` coderlm <agent> --prompt <file> [--max-depth N] [--allowedTools TOOLS] ``` ## Examples ```bash echo "Find all TODO comments in src/" > task.txt coderlm codex --prompt task.txt coderlm "bunx --bun @google/gemini-cli" --prompt task.txt echo "Fix type errors in src/" > task.txt coderlm claude --prompt task.txt --allowedTools "Bash,Edit" ```

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