abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Generate a deliberate pattern-breaking perturbation: PO, reversal, negation, random stimulus, exaggeration, or distortion.
Claude Code
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill generate-provocation --agent claude-code
Codex
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill generate-provocation -a codex -y
Cursor
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill generate-provocation -a cursor -y
Gemini CLI
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill generate-provocation -a gemini-cli -y
GitHub Copilot
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill generate-provocation -a github-copilot -y
OpenCode
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill generate-provocation -a opencode -y
Windsurf
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill generate-provocation -a windsurf -y
name: generate-provocation description: "Generate a deliberate pattern-breaking perturbation: PO, reversal, negation, random stimulus, exaggeration, or distortion."
Generate a deliberate pattern-breaking perturbation that opens alternative reasoning paths.
required: [target_pattern, provocation_mode, boundary_conditions] optional: [random_stimulus_pool, intensity, safety_constraints] constraints: [provocation must be traceable to the target pattern]
1. Describe the dominant pattern and its protected assumptions. 2. Apply the selected mode: PO, reversal, negation, random stimulus, exaggeration, or distortion. 3. Record the altered elements and generated questions. 4. Return candidate directions without premature selection.
produces: [provocations, altered_assumptions, generated_questions, candidate_directions] delta_fields: [findings, hypothesis_updates, open_questions]
Caller supplies target schema, provocation modes, intensity scale, stimulus pool, and boundary constraints.
Reject random outputs with no relation to the target or ideas presented as validated conclusions.
A research skill graph for AI-native science. 271 markdown files. No runtime, no dependencies, no build step.
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