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repo2post

Turn a git diff, tag range, or pull request into a release blog post, changelog, or launch thread — with one AI call.

You shipped the release. Now you have to write it up — again. repo2post reads what actually changed (commits + diff stats between two refs, or a GitHub PR) and drafts the write-up in the format you need: a blog post, a Keep-a-Changelog entry, GitHub release notes, a launch thread, or a technical breakdown. It is grounded — the prompt forbids inventing features that aren't in the diff — and model-agnostic: pass any provider/model string and it routes through the Vercel AI Gateway.

$ repo2post --from v1.0.0 --to v1.1.0 --style changelog --project envjoy
repo2post changelog from v1.0.0..v1.1.0 (12 commits) via anthropic/claude-sonnet-4.5…

## v1.1.0

### Added
- `--generate` now accepts `--force` to overwrite an existing example (a1b2c3d)

### Fixed
- Inline `#` comments are stripped the way dotenv does (e4f5a6b)
- Duplicate keys now fail `--check` instead of being silently ignored (c7d8e9f)

Quick start

export AI_GATEWAY_API_KEY=...    # or a provider key, e.g. ANTHROPIC_API_KEY

# Default: previous tag → HEAD, as a blog post
npx @vtx-labs/repo2post

# A specific range as a changelog, written to a file
npx @vtx-labs/repo2post --from v1.0.0 --to v1.1.0 -s changelog -o CHANGELOG-1.1.0.md

# A launch thread from a GitHub pull request
npx @vtx-labs/repo2post --pr VTX-Labs/repo2post#1 -s thread

Or add it to a project: pnpm add -D @vtx-labs/repo2post

Styles

| Style | Output | | :-------------- | :--------------------------------------------------------------------- | | blog | Narrative release post — headline, intro, themed sections (default) | | changelog | Keep a Changelog entry — Added / Changed / Fixed / Removed | | release-notes | GitHub release notes — highlights + what's changed | | thread | X/Twitter launch thread — numbered, punchy, no hashtag spam | | technical | Engineer-facing breakdown — what changed, why, migration notes |

CLI

repo2post [options]

Source
  --from <ref>           Start ref, exclusive (default: previous tag, else root)
  --to <ref>             End ref, inclusive   (default: HEAD)
  --pr <owner/repo#n>    Use a GitHub pull request instead of a local range
  -C, --cwd <dir>        Repository directory (default: current directory)
  --max-commits <n>      Cap commits read from the range (default: 200)

Output
  -s, --style <style>    blog | changelog | release-notes | thread | technical
  -m, --model <id>       provider/model id (default: anthropic/claude-sonnet-4.5)
  --project <name>       Project name to anchor the writing
  --guidance <text>      Extra instructions to weave into the prompt
  --temperature <n>      Sampling temperature 0–2 (default: 0.4)
  -o, --out <file>       Write to a file instead of stdout

Other
  --list-models          Print the curated model ids and exit
  -h, --help             Show help
  -v, --version          Show version

| Exit code | Meaning | | :-------- | :------------------------------------------------------- | | 0 | Generated successfully | | 1 | No commits in the range — nothing to write | | 2 | Usage error, not a git repo, or a bad ref | | 3 | Generation failed (model / API error) | | 4 | No AI credentials found in the environment |

The generated content goes to stdout; progress and token usage go to stderr, so you can pipe the result straight into a file or gh:

repo2post -s release-notes | gh release create v1.1.0 --notes-file -

Models & credentials

Models are plain provider/model strings. In AI SDK 6 such a string routes through the Vercel AI Gateway automatically, so a single AI_GATEWAY_API_KEY unlocks every major provider. A direct provider key (ANTHROPIC_API_KEY, OPENAI_API_KEY, GOOGLE_GENERATIVE_AI_API_KEY, XAI_API_KEY, …) works too. Run repo2post --list-models for a curated set — but any gateway model id is accepted.

Programmatic API

import { collectChanges, generatePost } from "@vtx-labs/repo2post";

const changes = await collectChanges({ from: "v1.0.0", to: "v1.1.0" });
const post = await generatePost(
  { changes, style: "changelog", project: "my-lib" },
  { model: "anthropic/claude-sonnet-4.5" },
);
console.log(post.content);

| Export | Description | | :-------------------------------- | :----------------------------------------------------------------- | | collectChanges(options?) | Read a git range (read-only) → ChangeSet | | collectPullRequest(ref, token?) | Read a GitHub PR via the REST API → ChangeSet | | parsePrRef(input) | Parse owner/repo#123 or a PR URL | | buildPrompt(input) | Build the grounded system + user prompt for a change set + style | | generatePost(input, options?) | Run the AI generation → { content, model, usage, … } | | allStyles() / MODELS | The available styles and curated models |

generatePost accepts an injected generateText (matching the AI SDK shape), so you can unit-test the whole pipeline with no network and no API key.

How it works

1. Acquire — read commits + git diff --numstat between two refs (read-only), or fetch a pull request from the GitHub API. A PR becomes the same ChangeSet.
2. Build a grounded prompt — serialize the commits and largest file changes, truncate to a budget, and pin the rules: write only what the diff supports, prefer user-facing impact, never invent versions or numbers.
3. Generate — one generateText call to the chosen model, via the AI Gateway.
4. Emit — content to stdout (or a file); usage + progress to stderr.

repo2post never writes to your repository and never sends your source code — only commit messages and diff statistics are included in the prompt.

License

MIT © VTX Labs