Reading the repo
Opening the box…
Reading the repo
Opening the box…
Assembly instructions
Agent Skill for fine-tuning an agentic model on your own Claude Code sessions with Tinker. Works in Claude Code, Codex and OpenCode.
GitHub didn't answer, so this is the saved copy from 17 h ago
Will it work on macOS?
Heads-upIt also needs 2 settings in .env (2 secret).
Then run bash setup.sh. It stops at the first error and is safe to run again. Servers and tests aren't started; it lists them at the end. Read it first.
Needs Git: xcode-select --install
git clone https://github.com/drost-ai/tinker-ai-skill.git cd tinker-ai-skill
Python 3.x (no version pinned)
brew install python
Fill in secrets: TINKER_API_KEY, WANDB_API_KEY
cp .env.example .env
python -m venv .venv source .venv/bin/activate pip install -r requirements.txt
git clone https://github.com/drost-ai/tinker-ai-skill.git ~/.claude/skills/tinker-ai-skill
cd ~/.claude/skills/tinker-ai-skill
uv venv && source .venv/bin/activate && uv pip install -r requirements.txt
python scripts/make_sample_transcript.py --out ./demo-claude-projects --turns 14 --long-results
python scripts/collect_sessions.py --claude-dir ./demo-claude-projects --data-dir ./demo-data --min-bytes 1000
python scripts/normalize_sessions.py --data-dir ./demo-data
python scripts/anonymize_sessions.py --data-dir ./demo-data --name "Taylor Quintrell"
python scripts/build_dataset.py --data-dir ./demo-data --model Qwen/Qwen3.6-35B-A3B --max-len 8192 \
--system-prompt-file assets/system-prompt.md
python scripts/train_tinker.py --data-dir ./demo-data --name qwen3.6-35b-a3b-8k # offline smoke test
The last command prints a decoded training row, the token count and the resolved
configuration. Add --train to launch a real run; afterwards
export_checkpoint.py and make_gguf.sh take it to a GGUF you can run.
No reports for macOS yet.
GitManual AI Agent reads the 3 key files and writes a step-by-step guide for macOS. Once written, it's saved for everyone.