onefilellm

name	onefilellm
description	Use when aggregating local files, directories, GitHub repositories/issues/PRs, documentation pages, PDFs, arXiv/DOI/PMID sources, YouTube transcripts, stdin, or clipboard text into a single LLM-ready XML context file using the locally installed jimmc414/onefilellm CLI. Use for context packaging, source bundling, repo-to-text conversion, and multi-source research ingestion.
license	MIT

OneFileLLM

Use this skill to collect multiple sources into one XML-style context payload for LLM analysis.

Source

• Upstream repository: https://github.com/jimmc414/onefilellm
• Integrated source commit: 99c51a2cbe8cc01c0db037a9f800ca31fae9c2cd
• Local checkout: %USERPROFILE%\.onefilellm\onefilellm
• Isolated venv CLI: %USERPROFILE%\.onefilellm\venv\Scripts\onefilellm.exe
• Windows shim: %USERPROFILE%\.onefilellm\bin\onefilellm.cmd

README-Grounded Usage

The upstream README defines OneFileLLM as a command-line tool and Python API for aggregating local files, GitHub repos, web pages, PDFs, YouTube transcripts, arXiv/DOI/PMID sources, stdin, and clipboard content into a single structured XML output.

Run:

python scripts/run_onefilellm.py ./docs README.md
python scripts/run_onefilellm.py https://github.com/user/project
python scripts/run_onefilellm.py https://docs.python.org/3/tutorial/
python scripts/run_onefilellm.py --help-topic examples

Equivalent direct commands:

& "$env:USERPROFILE\.onefilellm\venv\Scripts\onefilellm.exe" --help
& "$env:USERPROFILE\.onefilellm\bin\onefilellm.cmd" --help-topic crawling

References

• references/source-readme.md contains the full upstream README.
• references/architecture.md contains upstream architecture notes.
• references/requirements.txt and references/requirements-lock.txt document installed dependencies.
• references/source-metadata.json records the integrated commit and local paths.

Safety And Quality Rules

• Prefer local files/directories when possible.
• Treat network sources as active fetches. Only run against trusted URLs or explicit user-provided URLs.
• Do not pass secrets, private tokens, or sensitive local directories unless the user explicitly asks and the scope is clear.
• Use GITHUB_TOKEN only when private GitHub access or higher rate limits are required.
• Use OFFLINE_MODE=1 for local-only dry runs or when network fetches should be blocked.
• For YouTube-only transcript work, prefer the youtube-transcript-english skill because it enforces English output more strictly than OneFileLLM's built-in transcript fallback.