abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Decompose a research question into MECE subquestions with coverage and independence arguments.
Claude Code
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill generate-subquestions --agent claude-code
Codex
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill generate-subquestions -a codex -y
Cursor
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill generate-subquestions -a cursor -y
Gemini CLI
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill generate-subquestions -a gemini-cli -y
GitHub Copilot
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill generate-subquestions -a github-copilot -y
OpenCode
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill generate-subquestions -a opencode -y
Windsurf
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill generate-subquestions -a windsurf -y
name: generate-subquestions description: "Decompose a research question into MECE subquestions with coverage and independence arguments."
Decompose a research question into MECE subquestions with coverage and independence arguments.
required: [main_research_question, scope_statement] optional: [evidence_map, dependency_constraints, desired_granularity] constraints: [question must be scoped and complex enough to decompose]
1. Parse the main question into objects, mechanisms, conditions, and outcomes. 2. Generate candidate subquestions and assign coverage domains. 3. Remove overlap, test independence, and map dependencies. 4. Return the MECE set with unresolved gaps.
produces: [subquestion_set, coverage_map, independence_arguments, dependency_notes] delta_fields: [findings, open_questions, uncertainties]
Caller supplies question schema, scope test, MECE policy, granularity, and dependency representation.
Reject decompositions that merely restate the main question or leave domains without a coverage rationale.
A research skill graph for AI-native science. 271 markdown files. No runtime, no dependencies, no build step.
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