Agent skill · AI & Agents

checkpoint-promotion

Gate fine-tuned checkpoints with drift budgets, paired comparison, and forgetting checks before promotion. Use after a training run produces a checkpoint, when deciding whether a tuned model ships, or when a promoted model needs re-gating against updated goldens.

Seth Hobson38,331★ · +219/wk · 1 repos on radarProfile →
claude-codecodexcopilotcursorMIT
Install
npx skills add wshobson/agents --skill checkpoint-promotion --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 8 KB
Bundled scripts: none
Path: plugins/llm-finetuning/skills/checkpoint-promotion/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 38,479 · +148 this week
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Checkpoint Promotion The Phase 5 gate for the whole plugin: a checkpoint that trains cleanly and beats its task metric still doesn't ship without clearing all four stages below. `eval-harness-first` built the suite re-run here — this skill is where that suite's baseline decides something. **Input:** a trained checkpoint, `eval/baseline-<model>.json` from `eval-harness-first`, and the frozen `eval/drift-suite.yaml`. **Output format:** `promotion-report.md` — the four-stage evidence plus a terminal `PROMOTE` or `REJECT` verdict that `/finetune` Phase 5 and `/promote-checkpoint` consume directly. ## The Four-Stage Gate Each stage gates the next — a failure at stage 2 means stage 3 doesn't run. Stages 2 and 3 share one expensive inference pass, so running them concurrently and applying gate order at verdict time is licensed on a **deterministic** arena (nothing saved by serializing); a judge-based arena should still wait for stage 2 first — that's where the real savings are. 1. **Data-quality gate.** Before any eval touches the checkpoint: dedup the training set, check for eval-goldens leakage (the exact failure `trace-to-training-data`'s Hygiene section exists to prevent), and scan

What's inside
Steps it walks through
  1. The Four-Stage Gate
  2. Drift Budget
  3. Catastrophic Forgetting
  4. The Verdict
  5. Related Skills
Ships with 1 file
  • references/gate-templates.md
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About this skill
What does the checkpoint-promotion skill do?

Gate fine-tuned checkpoints with drift budgets, paired comparison, and forgetting checks before promotion. Use after a training run produces a checkpoint, when deciding whether a tuned model ships, or when a promoted model needs re-gating against updated goldens.

How do I install it?

Run `npx skills add wshobson/agents --skill checkpoint-promotion --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From wshobson/agents, a repository with 38,479 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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