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verificar

Verifica que un cambio realmente funcione antes de afirmar que está completo.

¿Qué es verificar?

Esta habilidad, denominada 'verificar', está diseñada para que el agente de IA (como Claude Code, Cursor o Codex) pueda confirmar con evidencia concreta que una característica, corrección o refactorización realmente funciona antes de declararla completa. Es útil para evitar afirmaciones vagas del tipo 'debería funcionar' y proporcionar certeza tanto al desarrollador como al revisor. La habilidad sigue un flujo de trabajo estructurado: primero identifica el comportamiento exacto que debe probarse, luego prioriza el uso de pruebas existentes, después busca comandos de verificación directos y, si no es suficiente, describe pasos manuales de validación. Finalmente, reporta solo lo que se verificó realmente, incluyendo los comandos o pruebas ejecutadas, los resultados exitosos y los fallos o aspectos no verificados. Está pensada para cualquier plataforma de agente de IA en el contexto de desarrollo de software.

Compatible con~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/Yeachan-Heo/oh-my-claudecode/tree/main/skills/verify
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Preguntar en tu IA favorita

Abre un nuevo chat con esta habilidad de agente ya precargada.

OpenAIChatGPTClaudeClaudeGeminiGeminiGrokGrokPerplexityPerplexityDeepSeekDeepSeek

Documentación

¿Qué hace verificar?

Usa esta habilidad cuando el usuario quiera tener la seguridad de que una característica, corrección o refactorización realmente funciona.

Objetivo

Convertir afirmaciones vagas de "debería funcionar" en evidencia concreta.

Flujo de trabajo

  1. Identifica el comportamiento exacto que debe demostrarse.
  2. Prioriza el uso de pruebas existentes primero.
  3. Si falta cobertura, ejecuta los comandos de verificación directa más acotados disponibles.
  4. Si la automatización directa no es suficiente, describe los pasos de validación manual y recopila evidencia concreta y observable.
  5. Reporta solo lo que se verificó realmente.

Orden de verificación

  1. Pruebas existentes
  2. Verificación de tipos / compilación
  3. Comandos directos y acotados
  4. Validación manual o interactiva

Reglas

  • No digas que un cambio está completo sin evidencia.
  • Si una comprobación falla, incluye el fallo de forma clara.
  • Si no existe una ruta de verificación realista, dilo explícitamente en lugar de improvisar.
  • Prefiere resúmenes concisos de evidencia sobre registros ruidosos.

Salida

  • Qué se verificó
  • Qué comandos/pruebas se ejecutaron
  • Qué pasó
  • Qué falló o sigue sin verificarse

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

agent-doc-discipline

Writing-time discipline for documents agents consume (the five surfaces, specs, tickets, .omc/skills/) — every rule checkable and carrying a why, steps before reference, one meaning in one home, no restating what the environment already says. Mandatory at drydock seed generation and the launch C5 sediment pass; opt-in for any other agent-facing doc edit. The companion of minimal-code-discipline: that one disciplines code, this one disciplines papers.

ai-slop-cleaner

Clean AI-generated code slop with a regression-safe, deletion-first workflow and optional reviewer-only mode

ask

Process-first advisor routing for Claude, Codex, Gemini, Antigravity, Grok, or Cursor via `omc ask`, with artifact capture and no raw CLI assembly

ask-navigator

Shipyard

autopilot

Full autonomous execution from idea to working code

autoresearch

Stateful single-mission improvement loop with strict evaluator contract, markdown decision logs, and max-runtime stop behavior

cancel

Cancel any active OMC mode (autopilot, ralph, ultragoal, swarm, ultrapilot, pipeline, team) and clean up retired legacy state

configure-notifications

Configure notification integrations (Telegram, Discord, Slack) via natural language

debug

Diagnose the current OMC session or repo state using logs, traces, state, and focused reproduction

deepinit

Deep codebase initialization with hierarchical AGENTS.md documentation

deep-interview

Socratic deep interview with mathematical ambiguity gating before explicit execution approval

drydock

Lay the keel of the shipyard harness in any repo — the 4-pillar shared environment (Context, Rules, Tools, Standards) across 5 surfaces (CLAUDE.md, skills, design-system, mcp/cli, shared context) so that every human and agent inherits the same design language and anyone can ship. Run once per repo; re-run with --check to audit drift.

execute

Carry an approved task through to working, verified code

external-context

Invoke parallel document-specialist agents for external web searches and documentation lookup

graph

Deterministic orchestration graph runtime - declarative DAG pipelines with journal-based crash recovery

harbor

Harbor intake for external work — the captain only handles unresolved decisions. Sweeps incoming issues and PRs, verifies every claim before disposition, reuses every decision already made, and hands the maintainer a docket whose pending items each carry one question with options, recommendation, impact and evidence. Agent-autonomous for facts and for actions covered by standing authorization; signed for every new judgment. Never merges.

hud

Configure HUD display options (layout, presets, display elements)

launch

Shipyard

loft

Loft the shape before cutting steel — answer a design question that prose cannot settle by building a throwaway artifact: a pure logic module in a clickable shell, or structurally different UI variants behind one route. The captain reacts to the artifact; the answer folds into the decision; the artifact never docks. Use when a design question stalls in words, when a navigator map carries a loft ticket, or when a spec discussion reaches

minimal-code-discipline

YAGNI-ladder coding discipline for writing changes — existence-first, reuse before writing, dependency ladder, shortest correct diff, with non-negotiables that must never be minimized away

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