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Agent Prompt Tuning Lab

Local toolkit to harvest Cursor agent transcripts, normalize turns, split for eval/pool, and distill rules and skills for other repos. No bundled dataset — you run the pipeline on your machine.

Quick start

git clone <your-fork-url> agent-prompt-tuning-lab && cd agent-prompt-tuning-lab
chmod +x scripts/*.sh scripts/*.mjs

pnpm harvest:all && pnpm seed-manifest && pnpm normalize && pnpm split
pnpm insights                                    # see repo_hint names in output
pnpm suggest-artifacts -- --list                 # bundles from your splits
pnpm suggest-artifacts -- --bundle <repo> --llm prompt   # see docs/PROMPT_MODE.md

cp data/bundle-targets.example.json data/bundle-targets.json   # map repos → local paths
pnpm install-artifacts -- --bundle <repo> --include-personal

Documentation

Doc Contents
Overview Purpose, repo layout, roadmap
Pipeline Harvest → normalize → split → suggest-artifacts
Workflow Weekly cadence, porting lessons to other repos
Extraction Rule vs skill, insights, artifact loop
Prompt mode --llm prompt + ingest workflow
Bundle targets Map repos to local project paths
Artifacts Per-project rules and skills
Schema Manifest and turn fields
Gold sessions Tagged exemplar session ids
Contributing PR guidelines

Do not commit raw transcripts, processed turns, or data/manifest.jsonl.

About

Privacy-first toolkit to harvest, normalize, and split Cursor agent transcripts into prompt-tuning datasets, skills, rules & gold exemplars for LLM agents.

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