abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Construct a scenario across key uncertainties with explicit assumptions and plausibility. Modes include baseline/narrative, counterfactual, and extreme-but-plausible worst-case with breaking point, failure cascade, recovery assumptions, and distinguishing observables.
Claude Code
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill construct-scenario --agent claude-code
Codex
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill construct-scenario -a codex -y
Cursor
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill construct-scenario -a cursor -y
Gemini CLI
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill construct-scenario -a gemini-cli -y
GitHub Copilot
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill construct-scenario -a github-copilot -y
OpenCode
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill construct-scenario -a opencode -y
Windsurf
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill construct-scenario -a windsurf -y
name: construct-scenario description: "Construct a scenario across key uncertainties with explicit assumptions and plausibility. Modes include baseline/narrative, counterfactual, and extreme-but-plausible worst-case with breaking point, failure cascade, recovery assumptions, and distinguishing observables."
Construct scenarios across key uncertainties with explicit assumptions and plausibility, including baseline, counterfactual, and extreme-but-plausible modes.
required: [context, uncertainty_set, scenario_mode] optional: [drivers, dependency_model, probability_method, recovery_assumptions] constraints: [scenario assumptions and distinguishing observables must be explicit]
1. Select uncertainty axes and record their state space. 2. Generate distinct combinations appropriate to the mode. 3. Propagate interactions, breaking points, failure cascades, and recovery assumptions where applicable. 4. Attach plausibility rationale, distinguishing observables, and outcome implications.
produces: [scenario_set, assumptions, plausibility_rationales, observables, outcome_implications] delta_fields: [findings, hypothesis_updates, uncertainties, open_questions]
Caller supplies context schema, uncertainty axes, mode, distinctness rule, plausibility/probability method, and worst-case fields.
Reject decorative narratives that do not vary an uncertainty or expose a testable implication.
| source | criterion | |---|---| | scenario-construction | Output contains at least 3 distinct scenarios spanning different combinations of key uncertainties. | | scenario-construction | Each scenario includes a narrative, key assumptions, and probability estimate. | | worst-case-construction | Extreme-but-plausible mode includes breaking points, failure cascades, and recovery assessment. |
A research skill graph for AI-native science. 271 markdown files. No runtime, no dependencies, no build step.
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