abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
@yogsoth-aiInstall SkillAutomation
Skill
/generate-competing-hypotheses
Generate mechanism-distinct explanations rather than superficial paraphrases.
Claude Code
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill generate-competing-hypotheses --agent claude-code
Codex
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill generate-competing-hypotheses -a codex -y
Cursor
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill generate-competing-hypotheses -a cursor -y
Gemini CLI
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill generate-competing-hypotheses -a gemini-cli -y
GitHub Copilot
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill generate-competing-hypotheses -a github-copilot -y
OpenCode
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill generate-competing-hypotheses -a opencode -y
Windsurf
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill generate-competing-hypotheses -a windsurf -y
SKILL.md
generate-competing-hypotheses.SKILL.mdname: 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`
Read more
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`
Ships withde-anthropocentric-research-engine
A research skill graph for AI-native science. 271 markdown files. No runtime, no dependencies, no build step.
512200 skills
Stars on GitHub
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Questions about generate-competing-hypotheses.
- Which coding agents can use generate-competing-hypotheses?
- generate-competing-hypotheses 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.