stat-result-validator

name	stat-result-validator
description	Validate statistical research outputs for formulation quality, method-to- problem alignment, theory presence, experimental evidence, fair comparison, artifact completeness, and final-claim consistency.
metadata	{"category":"domain","trigger-keywords":"validation,audit,formulation,theory,comparison,claims,statistical sanity,quality gate","applicable-stages":"10,11,12,13,14,15,16,17,20","priority":"1"}

Stat Result Validator

Overview

Use this skill after formulation, method proposal, theory, experimental evaluation, comparison, and result synthesis. It checks whether the final result is supported by a coherent statistical research chain.

Artifact Checks

Required for all topics:

progress/<TOPIC_ID>/step0_problem_formulation.md
progress/<TOPIC_ID>/step1_method_proposal.md
progress/<TOPIC_ID>/step2_theory_analysis.md
progress/<TOPIC_ID>/step3_experimental_evaluation.md
progress/<TOPIC_ID>/step4_comparison.md
progress/<TOPIC_ID>/step5_result_synthesis.md
progress/<TOPIC_ID>/step6_quality_audit.md
experiments/<TOPIC_ID>/config.yaml
experiments/<TOPIC_ID>/results/metrics.json
experiments/<TOPIC_ID>/results/run_manifest.json
experiments/<TOPIC_ID>/results/comparison_summary.md
experiments/<TOPIC_ID>/results/claim_verdicts.json
experiments/<TOPIC_ID>/report/paper.md
experiments/<TOPIC_ID>/README.md

Analysis-specific source files and raw outputs are determined by the experiment plan and should live under experiments/<TOPIC_ID>/src/ and experiments/<TOPIC_ID>/results/.

Formulation Checks

The formulation must define:

• Observed data and sampling regime
• Data model or data source
• Target parameter, decision, prediction, or risk
• Assumptions
• Claims or hypotheses
• Evaluation criteria
• Theory targets

Blocking failures:

• No target or estimand.
• Claims cannot be measured.
• Assumptions are absent or incompatible with the proposed method.
• Evaluation criteria do not answer the research question.

Method Checks

Verify that:

• The proposed method addresses the formulated target.
• Baselines are meaningful.
• Ablations isolate important design choices.
• Diagnostics are specified for likely failure modes.
• Method outputs match the metrics and theory targets.

Theory Checks

Theory may be rigorous or partial, but it must be explicit.

Check for:

• Definitions and assumptions.
• Proposition, theorem, derivation, counterexample, or clearly labeled heuristic analysis.
• Predicted empirical patterns.
• Limitations and regimes not covered.

Blocking failures:

• No theory section at all.
• Theory analyzes a different target than the formulation.
• Final claims are stronger than the theory supports.

Experimental Evidence Checks

Check that:

• Experiments test the formulated claims.
• Conditions are aligned with assumptions and stress tests.
• Proposed method, baselines, and ablations are run on comparable conditions.
• Failure counts are recorded.
• Runtime reductions are recorded in run_manifest.json.
• Metrics are grouped at the right level.

Comparison Checks

Verify that:

• Comparisons include proposed method vs baseline.
• Ablations are interpreted.
• Experimental patterns are compared with theoretical predictions.
• Disagreements between theory and experiments are discussed.
• Claim verdicts cite both theoretical and empirical support when available.

Final Claim Checks

Every final claim must be traceable to:

formulation -> method -> theory -> experiment -> comparison

Use:

• PASS: formulation, theory, experiments, and comparisons support the claims.
• WARN: usable but has limitations that must be disclosed.
• FAIL: missing formulation, theory, evidence, or fair comparison prevents a valid conclusion.