1,310 件 ・ 関連度順
概要と使いどころ
Use when a mobile app needs a release pipeline - fastlane GitHub Actions to TestFlight (iOS) and Play internal track (Android), with code signing and the release naming that maps to TaskTrooper's prod deploy
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。
Fast-forward through OpenSpec artifact creation. Use when the user wants to quickly create all artifacts needed for implementation without stepping through each one individually.
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。
Review common AI slops of defensive programming patterns, avoid silent errors. TRIGGER when reviewing code for defensive anti-patterns, writing fail-fast code, or auditing error handling 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。
Audit a .glb or .gltf and make it small, correct, and fast to load in a browser, with a measured before/after report. Use when a model is "too big" or "slow to load", when the user asks to "optimize this GLB", "compress this glTF", or "export for web", or when they mention Draco, meshopt, gltfpack, KTX2, Basis, texture VRAM, draw calls, or a Blender / CAD / photogrammetry / Pascal export headed for Three.js, React Three Fiber (drei useGLTF), Babylon.js, or model-viewer. Covers inspection, spec validation, geometry and texture compression, scene-graph cleanup, and the correctness checks (metres, Y-up, node names, animations, PBR fidelity, alpha modes, vertex colors) that must not regress. Not for editing or modelling geometry, authoring or laying out a scene, generating 3D from text or images, converting from FBX/OBJ/CAD, or debugging a runtime frame rate that has nothing to do with asset size.
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。
Refill a prescription at a pharmacy. Works from a medication name, an Rx number, a photo of the bottle, or just "I'm running low." Confirms exactly what's being requested, gathers everything the pharmacy will ask for up front, and handles the refill online or by phone — whichever is fastest.
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。
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
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。
Fast sprint status check. Reads the current sprint plan, scans story files for status, and produces a concise progress snapshot with burndown assessment and emerging risks. Run at any time during a sprint for quick situational awareness. Use when user asks 'how is the sprint going', 'sprint update', 'show sprint progress'.
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。
Fast-lane prototype skill for the hybrid workflow. Builds a playable prototype in 2-3 days with minimal process overhead. Designed for discovery phase.
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。
Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.
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。
Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
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。
Delivering working code fastest via build-first product delivery through minimum agent chains; S/M scopes skip planning and build immediately. Use when compressing time-to-first-PR.
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。
Automating iOS UI via XCUITest and fastlane snapshot pipelines for App Store screenshots. Not for cross-platform E2E (Voyager), iOS feature impl (Native), or unit tests (Radar).
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。
AI가 쓴 한글 텍스트를 자연스럽게 윤문하는 진입 명령. humanize-korean 파이프라인을 Fast 모드(기본)로 실행하고 `--strict`면 정밀 3콜(진단→겨냥 윤문→finalize). 트리거 — "/humanize".
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。
Execute a trivial task inline — no subagents, no planning overhead
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。
Advanced and operational chat.agent capabilities for Trigger.dev, loaded on demand. Load this when working on the raw Sessions primitive (sessions / SessionHandle), a custom chat transport or the realtime wire protocol, durable sub-agents (AgentChat, chat.stream.writer), human-in-the-loop, steering, actions, background injection (chat.defer / chat.inject), fast starts (preload, Head Start via @trigger.dev/sdk/chat-server), context resilience (compaction, recovery boot, OOM, large payloads), chat.local run-scoped state, offline testing with mockChatAgent, or prerelease/version upgrades. For the everyday chat.agent({...}) definition and the useTriggerChatTransport happy path, use the trigger-authoring-chat-agent skill instead.
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。
Fast codebase scanner. Use when any skill needs codebase context. Finds files, patterns, dependencies, project structure. Pure read-only — never modifies files.
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 Model Context Protocol servers from specifications. Use when creating an MCP server for a tool, resource, or service that AI agents should access. Generates tool definitions, resource handlers, and test suites in TypeScript or Python (FastMCP).
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。
Comprehensive Python/FastAPI backend code review with optional parallel agents
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。
Run this repo's CI end-to-end — the kolu-specific procedure on top of the odu runner: the odu MCP front door, banned opt-out flags, linux-only platform pinning, venue-pool leasing, fail-fast surfacing, e2e timing evidence, and the green-gate. Triggers on "run CI", "drive CI", "re-run the pipeline", "close the red check", "warm the pool". Runner mechanics live in the `/odu` 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。
Python backend development standards for FastAPI, SQLModel, pytest, Ruff, and Pyright. Use when writing or modifying backend code in src/merchant, src/payment, src/apps_sdk, agents, tests, API routes, services, models, or protocol logic.
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。
60-Second Financial Snapshot — fast assessment of financial health based on six core inputs (income, expenses, savings, debt, age, retirement goal). No subagents. Produces a compact terminal scorecard with savings rate, DTI ratio, emergency fund coverage, retirement on-track status, and top 3 priority actions in under 40 lines.
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。
Emergency fund analyzer. Calculates the right emergency fund size based on job stability, family structure, fixed expenses, dependents, and employee vs. business-owner status. Recommends where to keep it (HYSA, money market, T-bills, I-Bonds), how fast to build it, what counts as a true emergency, and how to replenish after use. Produces FINANCE-EMERGENCY.md.
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。
Claim value trending and replacement cost tracking. Triggers: "claim value trending", "replacement cost tracking", "vehicle depreciation for claims", "residual value for insurance", "how fast is the insured vehicle losing value", "pre-loss value trajectory", "depreciation rate for settlement", "value retention for claims", "depreciation curve for total loss", "diminished value over time", "claim reserve adjustment", "portfolio depreciation exposure", "fleet depreciation risk", tracking vehicle depreciation for insurance claims valuation, replacement cost estimation, settlement trending, or reserve adequacy assessment.
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 knowledge of Behandlingsresultat (treatment result) domain in melosys-api. Use when: (1) Understanding result types and their meaning (FASTSATT_LOVVALGSLAND, MEDLEM_I_FOLKETRYGDEN, etc.), (2) Working with periods - Lovvalgsperiode, Medlemskapsperiode, Anmodningsperiode, Utpekingsperiode, (3) Debugging vedtak/decision metadata, criteria evaluation, or social insurance charges, (4) Understanding EU/EEA coordination logic and Article 16 exception handling, (5) Working with trygdeavgift (social insurance charge) calculations.
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。