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CLI ToolsMay 12, 2026·2 min de lectura

code2prompt — Turn Repos into LLM-Ready Prompts

code2prompt ingests a codebase and outputs structured, token-aware prompts, helping you move from ad-hoc copy/paste to repeatable context engineering.

Introducción

code2prompt ingests a codebase and outputs structured, token-aware prompts, helping you move from ad-hoc copy/paste to repeatable context engineering.

  • Best for: developers building agent workflows who need consistent, sharable repo context
  • Works with: any Git repo; outputs text you can paste into ChatGPT/Claude/Cursor/Codex
  • Setup time: 5–15 minutes

Practical Notes

  • Quant: run on 2 repos and compare output size (chars/tokens) before/after adding ignore rules.
  • Quant: keep a baseline prompt snapshot and diff it weekly to spot context drift.

Pattern: context as an artifact

Treat the generated prompt like a build artifact:

  • Check it into a scratch folder (or attach to PRs) when you need reproducibility.
  • Add ignore rules aggressively to keep noise down.
  • Prefer smaller, task-scoped prompts over one giant dump.

Agent workflow tip

Use code2prompt as a pre-step before:

  • running an agent to refactor,
  • generating docs,
  • or doing security review of changes.

If you record the prompt file, you can replay the same context across models and compare results.

FAQ

Q: Is this only a CLI? A: No. The repo describes a wider ecosystem, but the CLI alone is already useful for most workflows.

Q: How do I reduce prompt size? A: Add ignores and scope to a subdirectory; prioritize only the files needed for the task.

Q: Can I use it for reviews? A: Yes—generate a snapshot prompt and attach it to a PR so reviewers/agents share the same context.

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Fuente y agradecimientos

Source: https://github.com/mufeedvh/code2prompt > License: MIT > GitHub stars: 7,342 · forks: 422

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