ablation-planner
Use when main results pass result-to-claim (`claim_supported = yes` or `partial`) and ablation studies are needed for paper submission. A secondary Codex agent designs ablations from a reviewer's perspective; the local executor reviews feasibility and implements.
npx skills add majiayu000/claude-skill-registry --skill ablation-planner --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Ablation Planner Systematically design ablation studies that answer the questions reviewers will ask. The reviewer agent leads the design; the local executor reviews feasibility and implements. ## Context: $ARGUMENTS ## When to Use - Main results pass `/result-to-claim` with `claim_supported = yes` or `partial` - The user explicitly requests ablation planning - `/auto-review-loop` identifies missing ablations ## Workflow ### Step 1: Prepare Context Read available project files to build the full picture: - Method description and components (from `docs/research_contract.md`, project notes, or method docs) - Current experiment results (from `EXPERIMENT_LOG.md`, `EXPERIMENT_TRACKER.md`, or W&B) - Confirmed and intended claims (from `/result-to-claim` output or project notes) - Available compute resources (from server notes, run configs, or user-provided budget) ### Step 2: Codex Designs Ablations ```text spawn_agent: model: gpt-5.5 reasoning_effort: xhigh message: | You are a rigorous ML reviewer planning ablation studies. Given this method and results, design ablations that: 1. Isolate the contribution of each novel component 2. Answer questions reviewers will definitely ask 3. Test
- Context: $ARGUMENTS
- When to Use
- Workflow
- Step 1: Prepare Context
- Step 2: Codex Designs Ablations
- Step 3: Parse Ablation Plan
- Step 4: CC Reviews Feasibility
- Step 5: Implement and Run
- Rules
What does the ablation-planner skill do?
Use when main results pass result-to-claim (`claim_supported = yes` or `partial`) and ablation studies are needed for paper submission. A secondary Codex agent designs ablations from a reviewer's perspective; the local executor reviews feasibility and implements.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill ablation-planner --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 majiayu000/claude-skill-registry, a repository with 534 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.