ablation-planner

Generate targeted ablation plans for machine learning method components.

Updated Jun 10, 2026
One-click install
npx skills add https://github.com/xqinag/ARIS-new --skill ablation-planner-xqinag
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ablation-planner
Source: https://github.com/xqinag/ARIS-new/tree/main/skills/skills-codex/ablation-planner
Command: npx skills add https://github.com/xqinag/ARIS-new --skill ablation-planner-xqinag

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Systematically design ablation studies to answer reviewer questions about a method's components, helping researchers validate claims and strengthen submissions.

Core Features & Use Cases

  • Structured Ablation Design: Generates component-level and hyperparameter ablations aligned with a reviewer perspective.
  • Planning and Feasibility Review: Evaluates feasibility and produces implementation guidance for the local executor.
  • Experiment Tracking Ready: Produces plan artifacts suitable for integration into EXPERIMENT_LOG.md and project notes.

Quick Start

Provide your method description and current results to generate an actionable ablation plan.

Frequently Asked Questions about ablation-planner

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I design ablation studies to address reviewer requests in a machine learning paper?

Designing ablation studies for reviewers requires isolating core machine learning components and hyperparameters. This Skill generates a targeted ablation plan detailing experiment names, expected effects, priority rankings, and compute estimates to validate manuscript claims.

What is the best way to structure component-level ablations for experiment tracking?

Structuring component-level ablations requires explicit experiment names, tested components, expected effects, and coverage metrics. This Skill outputs a structured ablation plan artifact designed for direct integration into EXPERIMENT_LOG.md and project notes.

Can I generate an ablation plan if my manuscript results have not passed a result-to-claim check?

Generating an ablation plan requires manuscript results that pass a result-to-claim check. This Skill operates strictly in contexts where results pass this validation and reviewers explicitly request ablation studies.

How do I estimate compute requirements for hyperparameter ablation experiments?

Estimating compute requirements for hyperparameter ablations requires evaluating feasibility and component contributions. This Skill generates compute estimates and implementation guidance, producing a structured plan ready for local execution.

What do I need to provide to generate a targeted ablation plan?

Generating a targeted ablation plan requires providing your machine learning method description and current results. The Skill identifies core components and outputs a structured ablation plan with priority, coverage, and compute estimates.