result-to-claim

Classify experimental outcomes as yes, partial, or no support for research claims.

Updated Apr 21, 2026
One-click install
npx skills add https://github.com/Shallow-W/llm-wiki --skill result-to-claim-shallow-w
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: result-to-claim
Source: https://github.com/Shallow-W/llm-wiki/tree/main/.claude/skills/result-to-claim
Command: npx skills add https://github.com/Shallow-W/llm-wiki --skill result-to-claim-shallow-w

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Experiments often produce numbers without a clear, evidence-grounded decision about which claims those numbers actually support, which undermines paper writing, reviews, and follow-on work.

Core Features & Use Cases

  • Claim-support judgment via Codex: Routes experiment results through a structured evaluation that determines whether the intended claim is supported, partially supported, or not supported.
  • Verdict-based research workflow: Automatically drives next actions like pivoting, designing supplementary experiments, or marking confirmation-ready outcomes.
  • Optional research-wiki updates: When the wiki exists, records verdicts and updates claim/idea status and edges to keep the knowledge graph consistent.

Quick Start

Use the result-to-claim gate after experiments finish by providing the experiment description or the relevant W&B run identifier so the skill can compile results, ask Codex for a verdict, and route to the next research step.

Frequently Asked Questions about result-to-claim

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

FAQPage Schema
How do I verify if my experiment results support my research claims?

To verify experiment results against research claims, the skill collects data from sources like W&B runs and uses Codex to classify support as yes, partial, or no. This structured evaluation normalizes evidence to determine if your findings are defensible before paper writing.

How do I evaluate W&B runs to decide between pivoting or running ablations planning?

Evaluating W&B runs for ablation planning requires a post-experiment gating process that issues a verdict on claim support. Based on this Codex judgment, the workflow automatically routes next actions toward ablation design, supplementary experiments, or confirmation.

What is the best way to automate claim verification in a research workflow?

Automating claim verification in a research workflow requires a post-experiment gate that applies evidence-collection rules and experiment-integrity checks. It uses Codex routing to classify outcomes and optionally updates a research-wiki knowledge graph with verdicts.

Can I use Codex judgment to gate experimental outcomes before writing papers?

Yes, you can use Codex judgment to gate experimental outcomes before writing papers. The process enforces verdict parsing rules and evidence-collection requirements to ensure only supported claims advance to the publication stage.

Does claim verification work with experiment logs to update a research-wiki knowledge graph?

Claim verification works with experiment logs by collecting results and issuing a Codex verdict. When a research-wiki exists, the workflow records the verdict and updates claim or idea status and edges to keep the knowledge graph consistent.

When should I apply post-experiment gating to normalize key evidence?

You should apply post-experiment gating to normalize key evidence immediately after experiments finish and before writing papers or running ablations. This ensures your intended research claims are evaluated for support before proceeding with downstream research cycles.