MCP HubMCP Hub
Volver a habilidades

adaptic

pjt222
Actualizado 2 days ago
6 vistas
17
2
17
Ver en GitHub
Metaaidesign

Acerca de

Adpatic es una habilidad maestra que orquesta un ciclo sinóptico de 5 pasos —incluyendo meditación, observación e integración— para producir una síntesis panorámica unificada en tres o más dominios. Úsala cuando las interacciones entre dominios sean más críticas que la profundidad individual, el análisis secuencial resulte inadecuado, o antes de tomar decisiones arquitectónicas importantes que afecten a múltiples partes interesadas. Genera una comprensión coherente y holística, en lugar de un compromiso secuencial.

Instalación rápida

Claude Code

Recomendado
Principal
npx skills add pjt222/agent-almanac -a claude-code
Comando PluginAlternativo
/plugin add https://github.com/pjt222/agent-almanac
Git CloneAlternativo
git clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/adaptic

Copia y pega este comando en Claude Code para instalar esta habilidad

Documentación

Adaptic

5-step synoptic cycle → panoramic synthesis across domains. Sequential = compromise ("little of each"). Synoptic = integration → unified understanding holds all domains at once → emergent whole.

Use When

  • Problem spans 3+ domains, interactions > depth in any one
  • Polymath sequential tried → synthesis feels like compromise
  • Existing approaches = "little of each" not unified vision
  • Before major architectural decisions, multi-stakeholder
  • Domain experts disagree → resolution lives between

Use NOT When

  • Single-domain → use domain agent direct
  • Well-understood trade-offs → polymath sequential enough
  • Self-care/wellness → tending team
  • Speed > depth → full cycle needs sustained attention

In

  • Required: Problem requiring multi-domain synthesis
  • Optional: Explicit domain list (default: auto-detect)
  • Optional: Depth — light, standard, deep (default: standard)
  • Optional: Expression form — narrative, diagram, table, recommendation (default: auto)

Config

settings:
  depth: standard          # light (skip meditate), standard, deep (extended perceive)
  domains: auto            # auto-detect or explicit list
  expression_form: auto    # narrative, diagram, table, recommendation

Do

Step 1: Clear — Empty Workspace

Run meditate → clear prior ctx, assumptions, single-domain bias.

  1. Full meditate proc: prepare, anchor, observe distractions, close
  2. Domain bias = tendency to frame via recently-active domain
  3. Clear premature solutions arrived pre-full-picture
  4. depth: light → brief ctx-clearing pause

Workspace empty. No domain priority. No solution pre-selected. Neutral receptive → hold multiple perspectives.

If err: Domain keeps asserting → name bias: "I frame this as primarily [domain]." Naming loosens. Clearing fails → genuinely single-domain → reconsider.

Step 2: Open — Panoramic Mode

Run expand-awareness → narrow → wide-field perception.

  1. Inventory all domains → no pre-filter/rank
  2. Per domain: core concerns, constraints, values — no eval
  3. Soften focus: hold all simultaneously vs cycling
  4. Resist "start solving" → opening field only
  5. Domains in inputs → starting set, open to more

Panoramic field open. All domains simultaneous. Full landscape sensed. Spacious not overwhelming.

If err: List incomplete → "What missing would change picture?" Simultaneous → sequential scan → slow down. >7 domains → cluster related.

Step 3: Perceive — Cross-Domain Patterns

While maintaining panoramic, run observe + awareness → notice patterns, tensions, resonances across domains.

  1. Hold Step 2 field open → no narrow
  2. observe → what present: patterns across domains? tensions? resonances?
  3. awareness → what not seen: ignored domains? blind spots? surface assumptions?
  4. Record cross-domain no interpret:
    • Tensions: domains pull opposite
    • Resonances: domains reinforce/echo
    • Gaps: no domain addresses, whole reveals
    • Surprises: domain unexpected contribution
  5. depth: deep → cycle multiple times → subtler patterns

Critical: perceive across all simultaneously, not each in turn. Sequential loses cross-domain patterns = entire point.

Rich cross-domain obs — tensions, resonances, gaps, surprises. Span boundaries not live within. Noticed something invisible from any single domain.

If err: All within single ("in domain A, I notice X") → field collapsed → Step 2. No cross-domain → problem not synoptic → genuinely decomposable. Overwhelming → prioritize tensions (integration happens there).

Step 4: Integrate — Emergent Whole

Run integrate-gestalt → synthesize cross-domain obs → unified understanding.

  1. Map Step 3 tensions → don't resolve prematurely → hold as creative constraints
  2. Find figure: unified understanding when all held together? Not compromise/avg → new pattern includes+transcends individual
  3. Test whole: honors each domain's core concerns? Resolves tensions or papers over?
  4. Name insight one clear statement → unstatable simply = incomplete
  5. Verify emergent: reachable sequentially? Yes → synoptic added no value → sequential suffices

Single integrated understanding holding all simultaneously. Feels like discovery not construction — emerged from whole. Each domain honored, tensions resolved not compromised.

If err: "Little of each" not unified → gestalt not formed → Step 3, find avoided tensions — integration happens through tension. No gestalt → decompose: 2-3 strongest-tension domains first, then expand.

Step 5: Express — Communicate

Run express-insight → communicate synthesis.

  1. Assess audience: what domains familiar? framing makes accessible?
  2. Expression form (or input):
    • Narrative: audience needs parts→whole journey
    • Diagram: structural relationships
    • Table: systematic comparison
    • Recommendation: actionable decision
  3. Express w/ transparency: which domains contributed, where tensions resolved, emergent insight beyond any single
  4. Invite challenge: which aspects strongest, which most speculative

Clear expression accessible to audience. Shows work → audience sees domain contributions → whole. Form matches audience needs.

If err: Feels like list not integrated → insight lost → Step 4 one-statement summary, build outward from center. Wrong framing → "Who needs this and what decision does it inform?"

Check

  • Step 1 (Clear) ran → ctx + domain bias released
  • Step 2 (Open) produced panoramic 3+ domains
  • Step 3 (Perceive) cross-domain patterns (not within-domain)
  • Step 4 (Integrate) single emergent transcends individual
  • Step 5 (Express) form appropriate to audience
  • Output unreachable by sequential single-domain
  • Each domain's core concerns honored
  • Tensions resolved through integration, not compromise

Traps

  • Sequential masquerading as simultaneous: Cycling domains + stapling results ≠ synoptic. Test: cross-domain interactions produced new, or just concatenation?
  • Premature integration: Jump synthesis pre-panoramic field open. Steps 2+3 build foundation → rushing = shallow.
  • Compromise instead of emergence: Avg ("50% security, 50% usability") = compromise. True integration finds frame where both fully met, or honestly names irreducible trade-off.
  • Overuse single-domain: Not every problem panoramic. Single domain → synoptic adds overhead no value. "Use NOT When" exists.
  • Losing insight in expression: Step 4 gestalt → Step 5 fragments back to domain list. Keep integrated insight center; domain details supporting evidence.
  • Domain inflation: Artificially expand count → justify synoptic. 3 genuinely relevant > 7 where 4 peripheral.

  • meditate — Step 1; clears ctx + neutral state
  • expand-awareness — Step 2; narrow → panoramic
  • observe — Step 3; what present across field
  • awareness — Step 3; what not seen, blind spots
  • integrate-gestalt — Step 4; emergent whole from cross-domain
  • express-insight — Step 5; communicate integrated understanding

Repositorio GitHub

pjt222/agent-almanac
Ruta: i18n/caveman-ultra/skills/adaptic
0
agentsagentskillsai-assisted-developmentclaude-codeskillsteams

Habilidades relacionadas

content-collections

Meta

Esta habilidad proporciona una configuración probada en producción para Content Collections, una herramienta centrada en TypeScript que transforma archivos Markdown/MDX en colecciones de datos con tipado seguro mediante validación Zod. Úsala al construir blogs, sitios de documentación o aplicaciones Vite + React con mucho contenido para garantizar seguridad de tipos y validación automática de contenido. Abarca todo, desde la configuración del plugin de Vite y compilación MDX hasta la optimización de despliegue y validación de esquemas.

Ver habilidad

polymarket

Meta

Esta habilidad permite a los desarrolladores crear aplicaciones con la plataforma de mercados de predicción Polymarket, incluyendo la integración de API para operaciones y datos de mercado. También proporciona transmisión de datos en tiempo real a través de WebSocket para monitorear operaciones en vivo y actividad del mercado. Úsela para implementar estrategias de trading o crear herramientas que procesen actualizaciones de mercado en tiempo real.

Ver habilidad

creating-opencode-plugins

Meta

Esta habilidad ayuda a los desarrolladores a crear complementos de OpenCode que se conectan a más de 25 tipos de eventos, como comandos, archivos y operaciones LSP. Proporciona la estructura del complemento, las especificaciones de la API de eventos y los patrones de implementación para módulos en JavaScript/TypeScript. Úsala cuando necesites interceptar, monitorear o extender el ciclo de vida del asistente de IA de OpenCode con lógica personalizada basada en eventos.

Ver habilidad

sglang

Meta

SGLang es un framework de alto rendimiento para el servicio de LLM que se especializa en generación rápida y estructurada para JSON, expresiones regulares y flujos de trabajo de agentes utilizando su caché de prefijos RadixAttention. Ofrece una inferencia significativamente más rápida, especialmente para tareas con prefijos repetidos, lo que lo hace ideal para salidas complejas y estructuradas, y conversaciones multiturno. Elige SGLang sobre alternativas como vLLM cuando necesites decodificación restringida o estés construyendo aplicaciones con uso extensivo de prefijos compartidos.

Ver habilidad