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概要と使いどころ
Preserve output from expensive one-shot commands for monitoring and later analysis. Use when rerunning a build, API query, CI inspection, or diagnostic would be costly and a managed background process is not the better interface.
日本語の概要は準備中です。原文の説明を表示しています。
Deep knowledge about deploying applications to Netlify (static sites, edge functions, serverless functions).
日本語の概要は準備中です。原文の説明を表示しています。
Drafts certificates of service (proofs of service) for court filings. Use when a filing must be accompanied by proof that copies were served on all parties or counsel. Covers FRCP Rule 5, state equivalents, ECF/e-service, U.S. mail, hand delivery, and overnight courier methods.
日本語の概要は準備中です。原文の説明を表示しています。
DataLoader, subscriptions, federation, and schema stitching for GraphQL APIs. Activate on: GraphQL, DataLoader, subscription, federation, schema stitching, resolver, SDL, Apollo, Yoga. NOT for: REST API design (use api-architect), frontend GraphQL clients (use relevant frontend skill).
日本語の概要は準備中です。原文の説明を表示しています。
iOS Core Data architect for persistent storage, CloudKit sync, schema migrations, and SwiftData migration. Activate on: Core Data, NSManagedObject, CloudKit sync, Core Data migration, NSFetchedResultsController, NSPersistentContainer, SwiftData migration path. NOT for: SwiftUI state management (use swiftui-data-flow-expert), server databases (use data-pipeline-engineer), SQLite direct (use mobile-offline-sync-architect).
日本語の概要は準備中です。原文の説明を表示しています。
Diagnose and eliminate the GraphQL N+1 resolver explosion using Facebook DataLoader's per-request batching, plus the second-order defenses (persisted queries, depth limits, cost analysis). Use when a GraphQL query that returns N items in a list triggers N+1 database round trips, when designing nested resolvers that load associations, when a list query times out under load, or when you need to budget query cost before resolvers run. NOT for REST-style endpoint design (use api-versioning-strategy), generic database query optimization (use database-query-optimizer), or schema design (use graphql-server-architect).
日本語の概要は準備中です。原文の説明を表示しています。
Build daemon/background processes that start on boot, run continuously, and manage their own lifecycle. Covers macOS launchd (plist files, agents vs daemons), Linux systemd (unit files), Windows services, process supervision, logging, health checks, graceful shutdown, auto-restart, and AI-powered daemons that manage LLM API connections and rate limits. Activate on: "daemon", "background process", "launchd", "systemd", "service file", "plist", "launch agent", "launch daemon", "auto-start", "always running", "process supervisor", "pm2", "background service", "boot service", "AI daemon", "long-running process". NOT for: container orchestration (use devops-automator), cron jobs that run and exit (use task-scheduler), web server deployment (use backend-architect).
日本語の概要は準備中です。原文の説明を表示しています。
Naturalistic causal reasoning for failures and disputed attribution. Use when postmortems or root-cause debates need reframing. NOT for causal inference, fault trees, or fully observed failures.
日本語の概要は準備中です。原文の説明を表示しています。
Marketing and promotion specialist for Claude ecosystem technology - MCP servers, skills, plugins, and agents. Expert in community engagement, registry submissions, content marketing, and developer relations. Activate on 'promote MCP', 'share skill', 'market plugin', 'launch agent', 'developer marketing', 'MCP registry'. NOT for creating MCPs/skills (use agent-creator), general marketing (use content-marketer), or SEO optimization (use seo-visibility-expert).
日本語の概要は準備中です。原文の説明を表示しています。
How to design contextual inputs for an always-on AI agent with episodic memory. Covers what data to feed the agent, how to structure observations and triggers, ambient context capture (screen, audio, calendar), context window budgeting, and retrieval strategies that keep the agent grounded in what's actually happening. Activate on: "what should the agent observe", "context inputs for agent", "ambient context capture", "agent triggers", "agent input design", "screenpipe integration", "context window budget", "what data to feed my agent", "/always-on-agent-inputs". NOT for: memory architecture and storage (use always-on-agent-architecture), application ideas (use always-on-agent-applications), safety concerns (use always-on-agent-safety).
日本語の概要は準備中です。原文の説明を表示しています。
Meta-agent for creating new custom agents, skills, and MCP integrations. Expert in agent design, MCP development, skill architecture, and rapid prototyping. Activate on 'create agent', 'new skill', 'MCP server', 'custom tool', 'agent design'. NOT for using existing agents (invoke them directly), general coding (use language-specific skills), or infrastructure setup (use deployment-engineer).
日本語の概要は準備中です。原文の説明を表示しています。
Use when building content-heavy sites with Astro, deciding between SSG/SSR/hybrid, choosing client directives (idle/visible/load/media), structuring content collections with type-safe schemas, integrating React/Vue/Solid/Svelte components in the same project, or migrating from Next.js for marketing/docs. Triggers: client:idle vs client:load tradeoffs, content collections schema with zod, image optimization via @astrojs/image, view transitions, server islands, MDX layouts. NOT for SPA-style apps that need full interactivity (use Next/Remix), Astro internals/plugin authoring, or non-content sites where islands provide no benefit.
日本語の概要は準備中です。原文の説明を表示しています。
AWS CDK infrastructure builder using TypeScript with L2/L3 constructs and Well-Architected patterns. Activate on: AWS CDK, CDK construct, CDK stack, CDK pipeline, AWS infrastructure as code TypeScript, L2 construct, CDK patterns. NOT for: Terraform IaC (use terraform-module-builder), Kubernetes manifests (use kubernetes-manifest-generator), serverless framework (use devops-automator).
日本語の概要は準備中です。原文の説明を表示しています。
Architecture and systems design for building always-on AI agents with episodic memory. Covers the memory hierarchy (core/recall/archival), persistence layers, agent server infrastructure, vector stores, and framework selection. Provides concrete deployment patterns for agents that maintain identity and learn across sessions. Activate on: "always-on agent", "persistent agent architecture", "episodic memory system", "agent memory design", "long-running agent", "stateful agent", "agent that remembers", "MemGPT architecture", "Letta deployment", "/always-on-agent-architecture". NOT for: choosing what data to feed the agent (use always-on-agent-inputs), brainstorming applications (use always-on-agent-applications), safety and privacy concerns (use always-on-agent-safety), general agentic patterns (use agentic-patterns).
日本語の概要は準備中です。原文の説明を表示しています。
Convert existing code into agent-consumable CLI/MCP server + companion skill. Use for 'agentize', 'expose as MCP', 'wrap as CLI'. NOT new code from scratch (mk:bootstrap) or review (mk:review).
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user wants to connect, set up, or configure Fusionaly in their AI client, or when the fusionaly MCP tools are missing. Verifies the Fusionaly URL and agent key, then adds the MCP server to Claude Code, Codex, Cursor, Gemini CLI, or another client.
日本語の概要は準備中です。原文の説明を表示しています。
Control and inspect the built-in Web UI (packages/serve) — start, stop, status, open
日本語の概要は準備中です。原文の説明を表示しています。
Persistent, adaptive vector memory for agents on a ruOS desktop — a Rust-native vector database with local semantic embeddings, HNSW retrieval, and graph relationships. Use to remember and recall across sessions with no database server or API key.
日本語の概要は準備中です。原文の説明を表示しています。
Inspect reviewed Grafana infrastructure evidence for host or fleet CPU usage, memory load, disk space, and system load. Use for server-health checks, capacity symptoms, resource saturation, disk pressure, cloud or local host comparisons, and bounded infrastructure triage.
日本語の概要は準備中です。原文の説明を表示しています。
Publish a runnable prototype and return a shareable link. Prepares the prototype to run, starts/serves it (or deploys), and hands back a URL plus run instructions for review. Use when the user says "share the prototype", "give me a link", "publish this", "let the team see it", "deploy the preview", or is ready to circulate a prototype for feedback. Final stage of the Product Design set.
日本語の概要は準備中です。原文の説明を表示しています。
Suggests manual context compaction at logical intervals to preserve context through task phases rather than arbitrary auto-compaction.
日本語の概要は準備中です。原文の説明を表示しています。
Stop AI agents from secretly bypassing your rules. Mechanical enforcement with git hooks, secret detection, deployment verification, and import registries. Born from real production incidents: server crashes, token leaks, code rewrites. Works with Claude Code, Clawdbot, Cursor. Install once, enforce forever.
日本語の概要は準備中です。原文の説明を表示しています。
Search cloud memory backup when local results are insufficient. Use when memory_search returns few/no results for a topic you know was discussed before. Cloud preserves everything - even memories that were deleted or compacted locally.
日本語の概要は準備中です。原文の説明を表示しています。
End-to-end smoke against the local rembric dev server (`pnpm run dev`, host Next.js dev on :3000). Apply when the user says "smoke", "probar contra docker", "dev:up", or after applying an OpenSpec change that touches HTTP (`apps/web/src/app/api/`), MCP tools (`packages/mcp/src/`), or DB migrations (`packages/db/src/migrations/`). Encodes bring-up, readiness verification, probe pattern and teardown — not the probes themselves.
日本語の概要は準備中です。原文の説明を表示しています。