analyze-future-scenarios

SkillDev tools

Use this analyze claude skill to build and compare future scenarios and test whether a research plan holds up.

Available today. Use it from your connected AI after setup.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the analyze-future-scenarios skill

About this skill

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

What this skill tells your AI

The instructions your AI receives, as published by yogsoth-ai/de-anthropocentric-research-engine in skills/analyze-future-scenarios/SKILL.md and read by ahel’s review.

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.

Signals

GitHub stars
501
Forks
41
Last commit
Sep 2026
Advanced
Catalog kind
skill
Key
analyze-future-scenarios
Source
github.com/yogsoth-ai/de-anthropocentric-research-engine