result-to-claim

Evaluate experimental results against intended research claims and output structured verdicts.

Updated May 20, 2026
One-click install
npx skills add https://github.com/lightrain-a/medtrace-aris --skill result-to-claim-lightrain-a
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: result-to-claim
Source: https://github.com/lightrain-a/medtrace-aris/tree/main/.vendor/aris/skills/result-to-claim
Command: npx skills add https://github.com/lightrain-a/medtrace-aris --skill result-to-claim-lightrain-a

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Experiments often produce numbers, but teams struggle to know which claims those numbers actually support and what evidence is still missing.

Core Features & Use Cases

  • Codex-based claim adjudication: Evaluates whether results support the intended claim and outputs a structured verdict (yes/partial/no).
  • Evidence collection and normalization: Pulls key metrics and context from W&B, experiment logs/trackers, files, and research contracts.
  • Automated routing for next actions: Directs the workflow to confirm, supplement, or pivot based on the verdict, optionally updating the research wiki when available.

Quick Start

Use the result-to-claim gate after your experiments finish by providing the experiment description or the relevant W&B run identifier, so Codex can judge support for your intended claim and route the project to the next 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 evaluate if experiment results support intended research claims?

To evaluate if experiment results support intended research claims, use a Codex-based claim adjudication process that pulls metrics from W&B runs and outputs a structured verdict of yes, partial, or no. This normalizes evidence and identifies missing data before paper drafting.

What is the best way to automate routing experiments to confirm, supplement, or pivot?

Automated routing for experiment outcomes directs your workflow to confirm, supplement, or pivot based on a structured Codex verdict parsing of collected metrics and baselines. It optionally updates your research wiki to reflect the next action after experiments finish.

Can I use experiment logs and W&B runs to check research integrity before ablation decisions?

Yes, you can use experiment logs and W&B runs to optionally check research integrity before ablation decisions. The process collects and normalizes key metrics from these trackers to determine which intended claims are supported by completed results.

When do I need evidence synthesis from completed experimental results?

You need evidence synthesis from completed experimental results when you must determine which intended research claims are supported and identify missing evidence. This applies after experiments finish and before paper drafting or ablation decisions across your research scenarios.

Does claim evaluation work without a research contract or specific file formats?

Claim evaluation works by pulling key metrics and context from W&B, experiment logs, trackers, files, and research contracts. While it relies on these inputs to collect evidence and apply Codex for structured verdict parsing, it operates across scenarios using available run identifiers.

Why does my experiment report automation show a partial claim verdict?

Experiment report automation shows a partial claim verdict when collected metrics and baselines provide incomplete support for your intended research claim. The Codex-based adjudication identifies this gap, routing the workflow to supplement missing evidence before proceeding.