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Skill

/generate-competing-hypotheses

Generate mechanism-distinct explanations rather than superficial paraphrases.

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de-anthropocentric-research-engine
499200 skills
Install
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill generate-competing-hypotheses --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/generate-competing-hypotheses

Context preview

The summary Claude sees to decide when to auto-load this skill.

Generate mechanism-distinct explanations rather than superficial paraphrases.

SKILL.md

generate-competing-hypotheses.SKILL.md
name: generate-competing-hypotheses
description: "Generate mechanism-distinct explanations rather than superficial paraphrases."

generate-competing-hypotheses

Purpose

Generate distinct, testable hypotheses that explain a target observation or research problem.

Input contract

required: [problem_statement, observations, scope_constraints]
optional: [existing_theories, analogies, anomaly_records]
constraints: [each hypothesis must imply a differentiating prediction or assumption]

Procedure

1. Extract the target phenomenon and unresolved explanatory gap. 2. Generate mechanismally distinct explanations, including a null or status-quo hypothesis. 3. Translate each explanation into predictions, assumptions, and disconfirming observations. 4. Deduplicate equivalent explanations and retain the comparison set.

If competing hypotheses have explicit predictions and evidence links, consider `score-object` as the next tactic.

Output contract

produces: [hypothesis_set, mechanism_descriptions, prediction_set, assumption_register]
delta_fields: [hypothesis_updates, uncertainties, open_questions, recommended_jumps]

Quality gates

  • Hypotheses differ in mechanism or prediction, not wording only.
  • A null or baseline explanation is considered where applicable.

Failure and counterexamples

Do not generate unfalsifiable narratives or discard inconvenient hypotheses before comparison.

Provenance map

  • `resolved: generate-competing-hypotheses`
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Ships withde-anthropocentric-research-engine

The complete research orchestration system for AI-native science. What It Does Design Philosophy Architecture (v3.2.2) Quick Start Configuration Roadmap License DARE is not a tool that helps you do research. It is the researcher.

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Python
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Apache-2.0
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Repo: yogsoth-ai/de-anthropocentric-research-engine