Onefilellm: LLM Context Preparation Tool

Understand the project

Practical overview

Use Onefilellm when an LLM task needs material gathered from several supported source types in a consolidated, structured form.

Developers assembling repository code, issues or pull requests for LLM review.
Researchers collecting papers, PDFs and transcripts into a shared context bundle.
People preparing documentation or local files for language-model prompts.

Combine multiple repositories, URLs or local files into one context bundle.
Prepare a GitHub pull request or issue alongside project documentation for review with an LLM.
Collect academic references, PDF content or YouTube transcripts for later prompting.
Use the Python API to process inputs from a script.

Before you choose

The project is available as a public source-code repository under the MIT license and documents installation through pip or from a cloned repository.

The documented workflow is source collection and formatting; users supply the resulting context to an LLM separately.
The CLI accepts local paths, URLs and aliases, with examples covering repositories, issues, pull requests, documentation, academic references and transcripts.
GitHub API access is recommended; the documentation shows a GITHUB_TOKEN environment variable for it.
The core description specifies XML and clipboard output, while CLI help lists additional output-format options.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Pass a local documentation directory and a GitHub issue to Onefilellm as inputs.

Onefilellm installed and available as the onefilellm command.
A local directory of documents.
A GitHub issue URL; GitHub API access is recommended, with GITHUB_TOKEN documented for that access.

Run onefilellm ./docs/ https://github.com/user/project/issues/123 with the relevant local path and issue URL.
Use the generated consolidated output, which the tool documents as copied to the clipboard, as LLM context.

The selected sources are collected into consolidated content for LLM use.

The example documents input collection, not a successful fetch for every repository or issue.
The core description identifies XML as the structured output; the CLI also exposes output-format options.

Evidence and transparency

Source record details

Source availability: Active
Sources checked: 11 October 2026
Original website title: jimmc414/onefilellm · Official homepage title · retained in its source language