appreciative-discovery

$npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/appreciative-discovery

Identify positive deviants and extract transferable success principles

  • Solves the problem of finding rare successful cases in a domain
  • Relies on subagent-spawning and domain-specific data sources
  • Uses Appreciative Inquiry to analyze enabling conditions and patterns
  • Returns principles and examples to inform reframing and strategy

SKILL.md

.github/skills/appreciative-discoveryView on GitHub ↗
---
name: appreciative-discovery
description: Search for positive deviants and extract transferable principles using Appreciative Inquiry.
execution: subagent
prompt: ./prompt.md
input: problem_domain
used-by: appreciative-reframing
---

## Execution

Subagent — spawned via subagent-spawning/spawn-agent.

## Budget

One unit = one complete appreciative discovery (positive deviants + enabling conditions + principles).

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