1.2万 件 ・ 関連度順
概要と使いどころ
Use when a carrier asks about fuel-card vendor selection (Comdata, EFS, WEX, RTS, Pilot Flying J, Love's Connect), discount levels, fraud control, driver authorization PINs, IFTA reporting features, cash advance, money codes, or how the card fits into payroll/settlement workflows.
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 this skill to handle the subrogation and claim process after a crash. Covers when subrogation applies, how to pursue it, and timeline.
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。
Design error handling strategies for TypeScript and Python applications — exception hierarchies, Result/Either types, retry patterns, error boundaries, and structured error logging. Use when designing error handling architecture, choosing between exceptions and Result types, implementing retry logic, or building error recovery flows. Activate on "error handling", "exception hierarchy", "Result type", "retry pattern", "circuit breaker", "error boundary", "Pokemon exception". NOT for debugging specific runtime errors, logging infrastructure setup, or monitoring/alerting configuration.
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。
Flutter state management expert with BLoC/Cubit, Riverpod, Provider, and Navigation 2.0 (GoRouter). Activate on: Flutter state management, BLoC pattern, Cubit, Riverpod, Provider, GetX, GoRouter, Flutter navigation, flutter_bloc. NOT for: React Native (use react-native-architect), SwiftUI (use swiftui-data-flow-expert), Jetpack Compose (use jetpack-compose-navigation-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。
Expert in drone systems, computer vision, and autonomous navigation. Specializes in flight control, SLAM, object detection, sensor fusion, and path planning. Activate on "drone", "UAV", "SLAM", "visual odometry", "PID control", "MAVLink", "Pixhawk", "path planning", "A*", "RRT", "EKF", "sensor fusion", "optical flow", "ByteTrack". NOT for domain-specific inspection tasks like fire detection, roof damage assessment, or thermal analysis (use drone-inspection-specialist), GPU shader optimization (use metal-shader-expert), or general image classification without drone context (use clip-aware-embeddings).
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 optimizing Docker builds with BuildKit, designing multi-stage Dockerfiles, leveraging cache mounts, building multi-arch images, choosing distroless vs alpine, or signing images with cosign. Triggers: docker build slow, layer cache not hitting, npm install / pip install reruns, multi-stage final image bloat, glibc vs musl issues, RUN --mount=type=cache, BUILDKIT_INLINE_CACHE, registry cache exporters, qemu emulation for arm64, COPY ordering for cache. NOT for Docker daemon admin, Kubernetes-specific image policies, container security scanning workflows, or Buildpacks (different paradigm).
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。
Managing third-party dependencies — version pinning, security auditing, license compliance, update workflows, lockfile management, supply chain security. Activate on "npm audit", "dependabot", "renovate", "pin versions", "dependency update", "supply chain", "license compliance", "lockfile", "security advisory", "typosquatting", "SBOM". NOT for internal monorepo package management (use monorepo-management) or publishing your own packages to npm/PyPI.
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。
dbt Core/Cloud data transformations, testing, documentation, and CI/CD. Activate on: dbt, data transformation, analytics engineering, ref, source, staging model, mart, dbt test. NOT for: orchestration/scheduling (use airflow-dag-orchestrator), data warehouse tuning (use data-warehouse-optimizer).
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。
The intelligence layer of Jury-rig. Decomposes natural language tasks into proposed Hierarchical Task DAGs (HTDAGs), matches subtasks to skills, proposes wave and revision contracts, and expands nodes only when evidence supports a revised graph. Use for 'orchestrate', 'execute DAG', 'parallel agents', 'decompose task', 'coordinate skills'. NOT for single-skill tasks or simple linear workflows.
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。
Monitors a specified object against explicit stopping criteria and distinguishes replica convergence, iterative progress, and workflow terminal state. NOT for execution or setting goals.
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。
Analyze undirected cycle structure within a valid DAG using the source paper's orientation and contraction method. Use for cycle-basis analysis with explicit graph and reduction choices. NOT for directed feedback loops, workflow deadlocks, or runtime resilience claims.
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。
Operations, debugging, and optimization for DAG workflows. Performs root cause analysis on failures, profiles execution performance, aggregates results from parallel branches, bridges context between nodes, and learns patterns from execution history. Activate on "DAG failed", "why did it fail", "root cause", "performance profile", "aggregate results", "merge branches", "execution patterns", "optimize DAG". NOT for planning DAGs (use dag-planner), executing DAGs (use dag-runtime), or validating outputs (use dag-quality).
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。
Executes DAG waves with controlled parallelism using the Task tool. Manages concurrent agent spawning, resource limits, and execution coordination. Activate on 'execute dag', 'parallel execution', 'concurrent tasks', 'run workflow', 'spawn agents'. NOT for scheduling (use dag-task-scheduler) or building DAGs (use dag-graph-builder).
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。
Design modern, intuitive DAG/workflow visual editors that feel like LEGO, not LabView NOT for runtime DAG admission, graph execution, or claiming usability without user testing.
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 production computer vision pipelines for object detection, tracking, and video analysis. Handles drone footage, wildlife monitoring, and real-time detection. Supports YOLO, Detectron2, TensorFlow, PyTorch. Use for archaeological surveys, conservation, security. Activate on "object detection", "video analysis", "YOLO", "tracking", "drone footage". NOT for simple image filters, photo editing, or face recognition APIs.
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。
Choose, compare, and decompose work into the right coordination topology: dag, workflow, manager-driven team, swarm, blackboard, team-builder, or recurring loop. Use when the coordination shape is unclear, when you need topology-native breakdown instructions instead of a generic DAG, or when planning topology and runtime topology may differ. NOT for actual execution, node-level skill matching, or framework/tool installation.
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。
Design polished terminal UX for CLIs and TUIs. Use for setup flows, dashboards, tables, and actionable errors. NOT for web UIs, desktop windows, API schemas, or shell automation.
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。
API migration strategies, deprecation workflows, and header/URL/content versioning. Activate on: API versioning, backward compatibility, deprecation, breaking change, API migration, v1 v2, sunset header. NOT for: schema evolution in data (use schema-evolution-manager), gateway routing (use api-gateway-reverse-proxy-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。
Model an organization with BDI-inspired perceptions, expressed goals, accommodations, and levels of agency. Use for socio-technical diagnosis where actors interpret the same situation differently and agreement is partial. NOT for individual AgentSpeak execution, normative conflict algorithms, or ordinary workflow diagrams.
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。
Expert API designer for REST, GraphQL, gRPC architectures. Activate on: API design, REST API, GraphQL schema, gRPC service, OpenAPI, Swagger, API versioning, endpoint design, rate limiting, OAuth flow. NOT for: database schema (use data-pipeline-engineer), frontend consumption (use web-design-expert), deployment (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。
Research AI coding assistant products, audiences, user stories, social proof, hacks, and unmet needs for apps like Cursor, Claude Code, Codex, Warp Code, Devin, Windsurf, GitHub Copilot, Cline, Aider, and homegrown agent stacks. Use when designing or positioning agentic developer tools, Port Daddy Agent Harbor, swarm consoles, background coding agents, or competitive/product research for AI software engineering. NOT for implementing the coding agent runtime, generic market research, or UX mockups without developer workflow evidence.
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。
Discipline an AI agent needs to work an issue/task tracker (Jira, Linear, GitHub Issues) as the shared source of truth: pull the right next item instead of inventing work, search before creating to avoid duplicates, write actionable items with checkable acceptance criteria, keep status transitions honest, and link work to items via branches/PRs/commits so progress is legible. Use when an agent picks up tracker work, files a new issue, updates status, or closes an item. NOT for authoring the PR itself (use agent-pr-authoring), roadmap-level planning and prioritization (use legible-roadmap-with-sidequests), or the mechanics of multiple agents coordinating on the same codebase (use multi-agent-coordination).
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。
Expert in script-to-video production pipelines for Apple Silicon Macs. Specializes in hybrid local/cloud workflows, LoRA training for character consistency, motion graphics generation, and artist commissioning. Activate on 'AI video production', 'script to video', 'video generation pipeline', 'character consistency', 'LoRA training', 'cloud GPU', 'motion graphics', 'Wan I2V', 'InVideo alternative'. NOT for real-time video editing, video compositing (use DaVinci/Premiere), audio production, or 3D modeling (use Blender/Maya).
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 stateful Agents on Cloudflare Workers with current, source-verified SDK APIs. Covers durable state, RPC, chat, schedules, queues, fibers, Workflows, MCP, and channels while keeping authorization and external effects application-owned. NOT for assuming SDK helpers grant application authorization or effect approval.
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。