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/analyze-experiment-results

Interpret completed experimental outputs after host/runtime execution using pre-declared statistical tests, effect/uncertainty estimates, reproducibility checks, and calibrated synthesis.

From plugin
de-anthropocentric-research-engine
507200 skills

Claude Code

$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill analyze-experiment-results --agent claude-code

SKILL.md

analyze-experiment-results.SKILL.md
name: analyze-experiment-results
description: "Interpret completed experimental outputs after host/runtime execution using pre-declared statistical tests, effect/uncertainty estimates, reproducibility checks, and calibrated synthesis."

analyze-experiment-results

Purpose

Interpret completed experimental outputs after host/runtime execution using pre-declared statistical tests, effect/uncertainty estimates, reproducibility checks, and calibrated synthesis.

Input contract

required: [experiment_results, predeclared_analysis_plan, reproducibility_target]
optional: [assumptions, prior_findings, evidence_updates]
constraints: [consume named scientific objects; preserve provenance; keep unresolved uncertainty visible]

Execution protocol

Do not perform called SOP operations inline; each loaded SOP owns its contract and thresholds.

1. You MUST load skill `statistical-testing` to run the preregistered statistical tests and retain effect uncertainty. 2. You MUST load skill `verify-reproducibility` to verify the declared reproduction level. If the results must be assembled into claims, evidence, and counterclaims, consider `construct-argument-map`. If several interventions or methods require comparative selection, consider `rank-candidates`.

Deviation: reorder only when a dependency is already satisfied or unavailable; record the reason and confidence effect.

Output contract

produces: [effect_estimates, uncertainty_summary, reproducibility_assessment, interpretation]
delta_fields: [uncertainties]

Thresholds and quality gates

  • Each output is traceable to an input object, operation, and evidence reference.
  • Scope, assumptions, and unresolved alternatives remain explicit.
  • Retain $\alpha$ 0.05 and power 0.8 wherever the predeclared statistical design requires them.

Failure and counterexamples

Stop synthesis when a required object is absent, a precondition is violated, or a counterexample invalidates the proposed conclusion; return the partial delta with the failure recorded.

Provenance map

  • intermediate: experiment-execution/result-analysis [strategy]
  • resolved: result-validation-loop
  • resolved: statistical-testing
  • resolved: reproducibility-verification
  • resolved: execution-synthesis
  • resolved: result-collection

Preserved source criteria ledger

| source | criterion | treatment | |---|---|---| | resolved v3 entries above | node-specific criteria | retained and specialized to the v4 object contract | | experiment-execution/statistical-testing | $\alpha$ = 0.05 | fixed value retained where applicable | | experiment-execution/sample-size-estimation | power = 0.8 | fixed value retained where applicable |

Context checkpoint / Delta notes

Return the node-specific research-state delta and preserve findings, evidence updates, uncertainties, decisions, open questions, and recommended jumps as applicable.

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@yogsoth-ai
Ships withde-anthropocentric-research-engine

A research skill graph for AI-native science. 271 markdown files. No runtime, no dependencies, no build step.

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Questions about analyze-experiment-results.

Which coding agents can use analyze-experiment-results?
analyze-experiment-results installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.