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PthahnixPthahnix/De-Anthropocentric-Research-Engine/skills/analyze-future-scenarios/SKILL.md

analyze-future-scenarios

Skill504 starsChanged 50 days agoApache-2.0View on GitHub

Construct and compare plausible future/competitive/temporal/stress scenarios and test whether the research path remains robust across them.

1 other project uses a version of this.

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The file

We split this skill into the rules it gives an agent

2 rules. About 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Do not perform called SOP operations inline.

    line 22
  2. Distinctive:

    Stop synthesis when a required object is absent, a precondition is violated, or a counterexample invalidates the proposed conclusion.

    line 50

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

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Files
SKILL.md

analyze-future-scenarios

Purpose

Construct and compare plausible future/competitive/temporal/stress scenarios and test whether the research path remains robust across them.

Input contract

required: [research_path, scenario_axes, uncertainty_drivers]
optional: [assumptions, prior_findings, evidence_updates]
constraints: [consume named scientific objects; preserve provenance; keep unresolved uncertainty visible]

Execution protocol

Do not perform called SOP operations inline; each loaded SOP owns its contract and thresholds.

  1. You MUST load skill identify-scenario-drivers to rank the horizon's high-impact uncertainties.
  2. You MUST load skill enumerate-dimension-values to enumerate representative, boundary, and adversarial driver values.
  3. You MUST load skill evaluate-compatibility to prune incompatible combinations while retaining near-boundary cases.
  4. You MUST load skill construct-scenario to assemble distinct baseline, counterfactual, and extreme-but-plausible worlds.
  5. You MUST load skill evaluate-scenario-impact to score the research path inside each fixed world and record failure triggers.
  6. You MUST load skill evaluate-scenario-robustness to aggregate per-world results and expose fragile assumptions.
  7. You MUST load skill predict-competitive-move to forecast credible competitor moves and preemption risk.
  8. You MUST load skill analyze-temporal-trajectory to order outcomes through time and reveal regime changes.

Deviation: reorder only when a dependency is already satisfied or unavailable; record the reason and confidence effect.

Output contract

produces: [scenario_set, impact_comparison, robustness_assessment]
delta_fields: [findings, decisions]

Thresholds and quality gates

  • Each output is traceable to an input object, operation, and evidence reference.
  • Scope, assumptions, and unresolved alternatives remain explicit.
  • Retain $\alpha$ 0.05 and power 0.8 wherever the predeclared statistical design requires them.

Failure and counterexamples

Stop synthesis when a required object is absent, a precondition is violated, or a counterexample invalidates the proposed conclusion; return the partial delta with the failure recorded.

Provenance map

  • intermediate: experiment-execution/scenario-planning [campaign]
  • resolved: morphological-scenario
  • resolved: narrative-scenario
  • resolved: stress-scenario
  • resolved: competitive-scenario
  • resolved: temporal-scenario
  • resolved: parameter-space-construction
  • resolved: cross-consistency-filtering
  • resolved: strategy-robustness-testing

Preserved source criteria ledger

sourcecriteriontreatment
resolved v3 entries abovenode-specific criteriaretained and specialized to the v4 object contract
experiment-execution/statistical-testing$\alpha$ = 0.05fixed value retained where applicable
experiment-execution/sample-size-estimationpower = 0.8fixed value retained where applicable

Context checkpoint / Delta notes

Return the node-specific research-state delta and preserve findings, evidence updates, uncertainties, decisions, open questions, and recommended jumps as applicable.

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