pi-tinker

Diagnose training issues with Tinker in Pi or another coding-agent shell — slow steps, hanging sessions, output mismatches, error messages, renderer problems, and deployment issues. Use this skill whenever a user reports that training is slow, steps take too long, sessions are hanging, model outputs differ between Tinker and external engines (vLLM, SGLang), they get a confusing error message, training quality is poor (high KL, bad outputs), or they suspect something is wrong. Also trigger when users ask "is this a Tinker issue or my issue?", "is Tinker down?", report unexpected wait times, see output quality regressions, get opaque errors, or want to profile/debug their training or deployment pipeline. This skill walks through systematic triage to determine root cause.

Conduct post-training research for LLMs using the Tinker API in Pi or another coding-agent shell — replicate paper results, explore new training ideas, run and monitor experiments, and document findings. Use this skill whenever the user wants to do research, replicate experiments from a paper or repo, investigate training hypotheses, run experiment sweeps, explore post-training techniques (SFT, RL, DPO, distillation, etc.), set up training, write training code, choose a model, tune hyperparameters, manage checkpoints, export weights, or analyze training logs — even if they just say "try this idea" or "let's see what happens if...".