Skip to content
Automation
Skill

/identify-scenario-drivers

Identify high-impact/high-uncertainty drivers and rank them for scenario construction.

From plugin
de-anthropocentric-research-engine
512200 skills

Claude Code

$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill identify-scenario-drivers --agent claude-code

SKILL.md

identify-scenario-drivers.SKILL.md
name: identify-scenario-drivers
description: "Identify high-impact/high-uncertainty drivers and rank them for scenario construction."

identify-scenario-drivers

Purpose

Identify high-impact/high-uncertainty drivers and rank them for scenario construction.

Input contract

required: [candidate_drivers, impact_assessments, uncertainty_assessments]
optional: [evidence, assumptions, prior_results]
constraints: [use named scientific objects; retain provenance and missingness; $\alpha$ = 0.05 and power = 0.8 where applicable]

Procedure

1. Validate the typed inputs and state the decision this operation must support. 2. Apply the declared operation to the named object; record intermediate values that affect interpretation. 3. Check boundary conditions and counterexamples, then emit the result with uncertainty and source links.

Output contract

produces: [identify_scenario_drivers_result, evidence_trace, uncertainties]
delta_fields: [evidence_updates, uncertainties]

Quality gates

  • Inputs are named scientific objects with compatible schemas.
  • Every material result has a derivation or source reference.
  • Fixed statistical criteria remain exact where applicable: $\alpha$ 0.05 and power 0.8.

Failure and counterexamples

Return a failed operation with the violated precondition when inputs are incomplete, assumptions are unsupported, or a counterexample defeats the result.

Provenance map

  • intermediate: experiment-execution/scenario-driver-identification
Read more
@yogsoth-ai
Ships withde-anthropocentric-research-engine

A research skill graph for AI-native science. 271 markdown files. No runtime, no dependencies, no build step.

Stars on GitHub

Momentum

stars in total
512
Star history of yogsoth-ai/de-anthropocentric-research-engine on GitHub, a chart by star-history.com

More skills from other plugins.

agent-builder

agent-builder

Load immediately after an Agent intent, before the first agent_builder_* call. Governs how you create, configure, test, and…

n8n2w209k
@n8n-io@n8n-ioInstall Skill
browser-use

browser-use

Direct browser control via CDP for web interaction: automation, scraping, testing, screenshots, and site/app work. Also covers…

@browser-use@browser-useInstall Skill
add-anydoc

add-anydoc

Add local office-document-to-Markdown conversion to NanoClaw agent containers with the pinned Firecrawl AnyDoc CLI. Use when…

@nanocoai@nanocoaiInstall Skill

Questions about identify-scenario-drivers.

Which coding agents can use identify-scenario-drivers?
identify-scenario-drivers installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.