--- name: queue-review-2b6fc9074e58 description: > Review and resolve entries in `doc/app/decisions_queue.md` — the deferred decisions queue introduced in v5.29.0. Lists pending entries from one or many projects, lets the user confirm / adjust / revert each, and moves resolved ones to the historical section. Use when the user says "queue review", "review queue", "revisar cola", "resolver pendientes", or wants to batch-process decisions accumulated by the autopilot in `equilibrado` / `agresivo` modes when `autopilot.queue_enabled=true`. context: direct allowed-tools: Read, Write, Edit, Bash(pwd), Bash(ls:*) --- # /queue review — Resolver decisiones diferidas Procesa la cola en `doc/app/decisions_queue.md`. La cola solo se llena cuando el proyecto tiene `specbox.autopilot.queue_enabled = true` (off por default en v5.29.0). Cuando está apagada, las decisiones diferibles se preguntan síncronamente como en v5.28. ## Uso ``` /queue review # Lista pendientes en este proyecto /queue review --recent N # Solo las N más recientes pendientes /queue review --feature signup-flow # Filtrar por feature /queue review --resolve dq-XXX # Resolver una entrada específica /queue review --all-projects # Reservado para multi-proyecto (PR-15+) ``` --- ## MCP remoto: enviar la cola El servidor alojado (`mcp.specbox.build`) no lee ni escribe tu repositorio (UC-8604). Con él, cada llamada a estas tools lleva **`files_content`**: los ficheros que lee, como `{ruta relativa: contenido}` (léelos con `Read`; los que no existan, no los mandes). Después aplica la respuesta en el repositorio: - `files_changed` → escribe cada fichero con ese contenido completo (`Write`). - `files_deleted` → bórralos. - `files_appended` → añade ese texto al final del fichero, sin sobrescribir lo que tiene. - `files_requested` → ficheros que la tool buscó y no mandaste: si existen, repite la llamada añadiéndolos. Si la respuesta es `APP_DOCS_CONTENT_REQUIRED` o `CLIENT_CONTENT_REQUIRED`, faltó el contenido. Con el MCP local (`stdio`) basta `project_path` y nada de esto hace falta. Aquí el fichero es uno: `doc/app/decisions_queue.md`. Cada `resolve_queue_entry` devuelve la cola nueva en `files_changed`: escríbela y manda **esa** versión en la llamada siguiente (en un batch, encadena las resoluciones sobre el contenido actualizado). --- ## Paso 1 — Listar la cola Llama: ``` list_decisions_queue(project_path=".") # MCP remoto: list_decisions_queue(files_content={"doc/app/decisions_queue.md": }) ``` Si retorna `exists=false`, informa "La cola no se ha creado aún. Las decisiones diferibles solo se acumulan cuando `autopilot.queue_enabled=true`." y termina. Si retorna `pending_count=0`, informa "Sin decisiones pendientes." y termina. Si hay pendientes, formatea la salida así: ``` 🔄 Decisiones pendientes (N): [1] dq-XXXX-abcd-veg feature: signup-flow decision_key: veg_preview Generado: hace 2 horas Default aplicado: Per-ICP arquetipo Startup (score=0.82) Bloquea: marcar UC-003 como ACCEPTED Evidencia: doc/veg/signup-flow/preview.md Acción: [c]onfirmar [a]djust [r]everter [s]kip [2] ... ``` Pide al usuario que elija qué quiere hacer (uno por uno o batch). --- ## Paso 2 — Resolver entradas Cuando el usuario decide: | Acción | Lógica | |--------|--------| | **Confirmar** | El default tentativo era correcto. Llama `resolve_queue_entry(engine_id, resolution="confirmed: ")`. | | **Ajustar** | Pregunta el nuevo valor, aplica el cambio en el artefacto referenciado por `evidence`, y resuelve con `resolution="adjusted: "`. | | **Revertir** | El default fue incorrecto. Pregunta qué hacer (rehacer paso síncrono, abortar feature, etc.) y resuelve con `resolution="reverted: "`. | | **Skip** | No hacer nada — la entrada queda pendiente. | Si el usuario quiere batch-resolver con un patrón ("aprobar todos los veg_preview con score >0.85"): 1. Filtra `pendientes` por `decision_key` y/o por contenido en `default_applied`. 2. Aplica el `resolve_queue_entry` para cada match. 3. Reporta cuántas resolvió en batch. --- ## Paso 3 — Output final ``` ✅ Resueltas en esta sesión: N doc/app/decisions_queue.md actualizado (M pendientes restantes) UCs desbloqueados (si los hay): UC-003, UC-007 ``` Los UCs se desbloquean automáticamente cuando todas sus entradas pendientes se resuelven (esto lo gestiona el sync layer de PR-12+). --- ## Inviolables La cola **nunca** acepta: - `destructive_action` - `image_cost_over_budget` - `branch_to_main_push` - `definition_quality_gate` - `feature_problem_definition` - `feedback_field_classification` Estos siempre se preguntan síncronamente. Si el usuario invoca `/queue review` y ve uno de estos en la cola, es un bug — reportar para revisar el flujo del skill que lo encoló indebidamente. --- ## Auto-resolve Si una entrada tiene más de `autopilot.queue_auto_resolve_days` días (default 7), se auto-resuelve manteniendo el default tentativo. Esto evita que la cola se acumule indefinidamente. La auto-resolución queda registrada con `auto_resolved=true` para auditabilidad. `/queue review` puede mostrar warnings sobre entradas que están a punto de auto-resolverse. --- ## Reglas - Nunca borrar entradas resueltas — son histórico de decisiones del proyecto. - Editar `decisions_queue.md` a mano está OK (es una zona `manual` del usuario), pero el formato lo gestiona el parser; un fichero con marcadores rotos hace que `list_decisions_queue` retorne errores. - Después de resolver, mostrar al usuario el comando equivalente para que pueda automatizar: ``` resolve_queue_entry(engine_id="dq-XXX", resolution="confirmed: looks good") ``` --- Source attribution: EmbedBuild Original project: https://github.com/EmbedBuild/specbox-engine/blob/0d7a27c30d728b068215b9486667272160ed0d4e/.claude/skills/queue-review/SKILL.md License: Apache-2.0 License information: https://www.apache.org/licenses/LICENSE-2.0 Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice Business Source License 1.1 Parameters Licensor: Jesus Perez Sanchez (Embed Build) Licensed Work: SpecBox Engine v5.11.0 Copyright (c) 2026 Jesus Perez Sanchez Additional Use Grant: You may use the Licensed Work for non-production purposes, including personal evaluation, academic research, educational use, and contributing modifications back to the Licensed Work. 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