Skill389 estrellas del repoactualizado 20d ago

appreciative-discovery

Appreciative-discovery identifies and analyzes positive deviants, organizations or systems performing exceptionally well, to extract transferable best practices and enabling conditions. Use this Claude Code skill when researching what makes high-performing outliers successful, seeking actionable principles applicable to improving similar contexts, or conducting organizational benchmarking focused on learning from excellence rather than failure analysis.

Ver fuente Repositorio: de-anthropocentric-research-engine

Instalar en Claude Code

Copiar

git clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engine /tmp/appreciative-discovery && cp -r /tmp/appreciative-discovery/skills/appreciative-discovery ~/.claude/skills/appreciative-discovery

Después abre una sesión nueva de Claude Code; el skill carga automáticamente.

Definición

SKILL.md

## Execution

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

## Budget

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

<!-- BEGIN available-tables (generated) -->

## Available SOPs

Optional, no fixed order; the final leaf is always a sop.

| SOP | When to use |
| --- | --- |
| spawn-agent | Spawn a customized CC subagent with full MCP tool access. Used by SOPs that declare execution: subagent. |

<!-- END available-tables (generated) -->

Del mismo repositorio

formated-resultSkill

Experiment-specific - summarize the DARE executor's research design into a clean research_result report, forced to write back into the spec file produced by formated-specs.

formated-specsSkill

Experiment-specific - replaces writing-specs, emits DARE's 4-layer call plan as a clean research_graph schema. Last step forces load formated-result.

injection-fidelitySkill

loss-1 judge - read a sample's full dialogue and decide whether the user simulator semantically enacted its Policy Card. check-blind.

ladder-quality-orderSkill

loss-2 judge - pairwise quality comparison across the n rungs within one topic; decide monotonicity and endpoint separation. check-blind, D1-D5 only.

abductive-hypothesis-generationSkill

Strategy: Inference to the best explanation in the face of anomalies

ablation-brainstormSkill

Remove components one by one, observe system changes to reveal hidden

ablation-component-mappingSkill

Map system architecture to ablatable units for ablation studies

ablation-designSkill

Design ablation studies to isolate component contributions in ML systems