result-to-claim

Interpret experimental results against intended claims and route next actions.

Updated Apr 1, 2026
One-click install
npx skills add https://github.com/Wenwen555/ARIS-LVLM --skill result-to-claim-wenwen555
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: result-to-claim
Source: https://github.com/Wenwen555/ARIS-LVLM/tree/main/skills/result-to-claim
Command: npx skills add https://github.com/Wenwen555/ARIS-LVLM --skill result-to-claim-wenwen555

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Use after experiments complete to judge what claims the results support, what they don't, and what evidence is still missing. Codex MCP evaluates results against intended claims and routes to next action (pivot, supplement, or confirm). Use after experiments finish — before writing the paper or running ablations.

Core Features & Use Cases

  • Codex-driven evaluation of results against intended claims.
  • Automatic routing to next actions based on verdict (pivot, supplement, or confirm).
  • Applicable post-experiment checks before paper writing or ablations.

Quick Start

Run the result-to-claim evaluation on your latest experiment outputs to decide the next steps.

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 my experiment results support intended research claims?

Evaluating experiment results against research claims requires aggregating outputs from wandb histories and EXPERIMENT_LOG.md, then querying Codex to parse verdicts and route next actions like pivot, supplement, or confirm.

When should I run a claims evaluation on my experiment analysis workflow?

Run claims evaluation post-experiment but pre-paper writing or ablations. This workflow queries Codex to parse verdicts against research contracts, routing to pivot, supplement, or confirm actions with explicit evidence gaps identified.

Can I use wandb logs and EXPERIMENT_TRACKER.md for automated claims evaluation?

Yes, claims evaluation aggregates wandb histories, EXPERIMENT_TRACKER.md, EXPERIMENT_LOG.md, and log files to interpret results against research contracts. Codex MCP parses this evidence to route next actions with explicit gaps.

What is the best way to decide whether to pivot or confirm after experiment analysis?

Use Codex MCP to evaluate experiment results against research contracts. It parses verdicts to objectively route next actions—pivot, supplement, or confirm—based on identified evidence gaps and recommendations.

Does this experiment analysis workflow require any specific dependencies or components?

No dependencies or components are required. The workflow queries Codex MCP to evaluate aggregated results from wandb histories and experiment trackers against research contracts, routing next actions without external dependencies.