Show HN: Tag driven changelog generator (MDX) with optional LLM summaries

I built a tag-driven changelog generator for an OSS project I maintain and used it to backfill our 2025 docs changelog.

It walks git tags, finds merged PRs between releases, buckets them into categories, and renders MDX (Docusaurus in our case) organized by year -> month -> category -> version. There is an optional LLM mode that produces structured JSON via a Pydantic schema for PR entry and monthly summaries.

Example:

python .scripts/changelog/generate.py --year 2025 --github --ai --ai-model gpt-5.2 (or --help)

Gotcha: if you use --github, set GITHUB_TOKEN or you will most likely hit GitHub rate limits.

Repo script: https://github.com/confident-ai/deepeval/blob/main/.scripts/...

Disclosure: I maintain DeepEval. Happy to answer questions and take feedback.

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Show HN: Tag driven changelog generator (MDX) with optional LLM summaries