1.1万 件 ・ 関連度順
概要と使いどころ
Implement, review, or improve SwiftUI features using the iOS 26+ Liquid Glass API. Use when asked to adopt Liquid Glass in new SwiftUI UI, refactor an existing feature to Liquid Glass, or review Liquid Glass usage for correctness, performance, and design alignment.
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, critique, set, create, activate, or run durable Codex goals for persistent or long-running objectives. Use when the user says "set a goal", "start a goal", "activate goal mode", "persistent goal", "long-running objective", "goal tree", or asks for a goal with verifiers, durable state, approval gates, completion proof, bounded delegation, or parent/child subagent 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。
Designs Rust command-line interfaces that are reliable for agents, scripts, and humans. Use when building or reviewing Rust binaries, clap command trees, diagnostics commands, codegen tools, or automation-facing 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。
React composition patterns that scale. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or designing reusable APIs. Triggers on tasks involving compound components, render props, context providers, or component architecture. Includes React 19 API changes.
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。
Derive and implement first-principles audio-coupled haptic and kinetic UI feedback. Use when designing, reviewing, or coding haptics/audio for mobile apps, native iOS/Android, React Native/Expo, SwiftUI, games, detent pickers, toggles, sliders, page curls, scroll gestures, wallet/signature flows, Solana transactions, backend/realtime state changes, confirmations, settlements, and semantic UI events where feedback should follow signal math instead of ad hoc vibration calls.
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。
Elite frontend image-direction skill for generating premium, conversion-aware website design references. CRITICAL OUTPUT RULE — generate ONE separate horizontal image FOR EVERY section. A landing page with 8 sections produces 8 images. Never compress multiple sections into one image. Enforces composition variety (not always left-text / right-image), background-image freedom, varied CTAs, varied hero scales (giant / mid / mini minimalist), narrative concept spine, second-read moments, and a single consistent palette across all images. Optimized for landing pages, marketing sites, and product comps that developers or coding models can accurately recreate.
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。
Elite mobile app image-generation skill for creating premium, app-native screen concepts and flows. Designed for iOS, Android, and cross-platform mobile products. Prioritizes clean hierarchy, comfortably readable text, strong multi-screen consistency, controlled color palettes, non-generic creative direction, textured surfaces, image-led composition, tasteful custom iconography, and clean phone mockup framing. By default, screens should be shown inside a subtle premium iPhone or similar phone mockup with a visible frame, while the main focus stays on the app content itself. This skill generates images only. It does not write code.
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。
Elite website image-to-code skill for Codex. For visually important web tasks, it must first generate the design image(s) itself, deeply analyze them, then implement the website to match them as closely as possible. In Codex, it must prefer large, readable, section-specific images instead of tiny compressed boards, generate fresh standalone images for sections or detail views instead of cropping old ones, avoid lazy under-generation, avoid cards-inside-cards-inside-cards UI, and keep the hero clean, spacious, readable, and visible on a small laptop.
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。
HTML -> UCUF (Cocos Creator UI) conversion skill. Use for turning a complete HTML source package with ui-design-tokens.json and colors_and_type.css into Cocos usable layout/skin/screen JSON, then validating with rule guard, visual fidelity risk, runtime interaction smoke, Cocos Editor final gate, and regression 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。
HTML -> UCUF (Cocos Creator UI) conversion skill. Use for turning a complete HTML source package with ui-design-tokens.json and colors_and_type.css into Cocos usable layout/skin/screen JSON, then validating with Plan5 final fidelity gates: stale-rule audit, rule guard, visual fidelity risk, runtime interaction smoke, Cocos Editor final gate, and 95% regression matrix.
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。
Idiomatic Go - package and interface design, error wrapping, table-driven tests, generics, the modern standard library (slices/maps/cmp/errors.Join), current syntax, and logging discipline. Use when writing, reviewing, or refactoring any Go code, especially code drifting toward Java/Spring shapes (deep layer trees, generic repositories, heavy frameworks) - even if the user never says "idiomatic". Distilled from spf13/go-skills and adapted to this repo.
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, build, validate, and ship cross-platform agent skills. Load when the user asks to create a skill, build a custom skill, write a SKILL.md, package a workflow as reusable agent capability, improve or audit a skill, publish a skill, or build a planned skill suite.
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。
Orchestrator for the pre-decision business-idea lifecycle — generate ideas, model them, evaluate them, validate them with customers, and only then hand off to product-soul / brainstorming. Routes through `idea-generation`, `business-modeling`, `idea-evaluation`, and `customer-discovery`. Load when the user asks to explore business ideas, find a startup idea, evaluate a venture, validate an idea, says "what business should I start", "should I build this", "is this a good business", "I have a startup idea", "evaluate this venture", "model this business", "validate this idea", "Mom Test this", "Lean Canvas this", "Business Model Canvas", "Value Proposition Canvas", "go/no-go on this idea". Pre-decision suite — once one idea is committed, hands off to `product-soul`. Does NOT design features (use `brainstorming`) or audit built products (use `reality-check`).
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。
Create a detailed, step-by-step implementation plan for a feature or project. Load when the user asks to plan a feature, create a technical roadmap, break down a PRD into tasks, design an implementation strategy, or sequence engineering work. Also triggers on "how should we build this", "implementation plan for", "technical breakdown", "task list for", or any request to turn a high-level requirement into a concrete execution plan. Supports phased rollouts, architecture-first, and MVP-focused planning.
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。
Decompose tasks into structured, outcome-defined process entries with complexity triage. Load when user says "decompose this", "break this down", "what steps do I need", "plan this out", "what's the process for", "how do I approach this", or when any complex task needs structured execution planning. Includes a problem-understanding pass before complexity triage. Routes to `problem-to-plan` when the user needs planning deliverables (spec + plan + TODO). Does NOT replace brainstorming — brainstorming is design approval (upstream), this is execution planning (downstream).
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。
Generate 5–10 business idea candidates from a blank page or a founder's domain context — using pain mining, jobs-to-be-done, trend × capability mapping, constraint relaxation, adjacency search, and founder-market-fit prompts. Each candidate is a structured idea card (segment, JTBD, current alternative, why-now, distribution wedge, monetisation, "feels like"). Load when the user asks to generate business ideas, brainstorm startup ideas, find ideas to work on, says "what business should I start", "give me startup ideas", "I don't know what to build", "ideate ventures", "blank-page idea generation", "find me a startup idea", "explore business opportunities". Sub-skill of `venture-exploration`. Hard-bans "Uber for X" / "AI for X" with no specific JTBD, "everyone" segments, and idea cards missing any of the 7 required fields. Does NOT design or evaluate ideas generated — for that use `idea-evaluation`.
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 a self-improvement loop for a shipped product's AI agents — production traces feed evals, evals feed improvement proposals (prompts, playbooks, retrieval configs), and a human approval gate promotes changes with rollback. Technique-agnostic: chooses per project between ACE-style evolving playbooks, GEPA/MIPROv2 offline optimization, or simple eval-driven iteration via references/techniques.md. Load when the user asks to make my product's agents self-improving, learn from production traces, add a learning loop, evolve prompts or playbooks safely, promote agent improvements, or GEPA-style optimization. NOT harness-evolution (that improves the coding agent), NOT experimentation (product A/B tests), NOT agent-run-retro (dev-phase manual retros — this skill is the production-scale continuation).
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。
Test and debug browser UIs using Chrome DevTools MCP — DOM inspection, console errors, network requests, performance traces, and visual verification. Load when building or debugging anything that renders in a browser, verifying a UI fix, profiling Core Web Vitals in a real page, or the user asks for browser testing with DevTools. Requires chrome-devtools MCP configured. Not for backend-only or CLI work. Pairs with frontend-design and performance-optimization.
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。
Deploy with unified build/test/deploy intent across providers using .agent-loom/deploy.yml and per-provider adapters. Load when the user asks to deploy, ship to preview, release to production, or run a provider-agnostic deploy flow. Also triggers on "deploy anywhere", "deploy to Vercel", "deploy with GitHub Actions", "preview deploy", or "ship this". Runs preflight before any deploy — stops on missing secrets. Pairs with ci-cd-and-automation for pipeline design. Ships vercel and github-actions adapters; extensible adapter 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。
Turn assumptions, funnel opportunities, and product questions into a prioritised, feasibility-checked experiment backlog. Filters by traffic reality, metric latency, and method feasibility — not just ICE/RICE scoring. Maintains a living portfolio with status (idea → designed → running → readout → archived). Load when the user says "what should we test next", "build an experiment backlog", "prioritise our tests", "where should we experiment", "what's worth testing", or when the experimentation orchestrator routes here.
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 Mom Test–style customer-discovery interviews to validate or kill an unbuilt idea — generate a non-leading interview guide, conduct or coach the conversations, and synthesize signal vs compliments. Load when the user asks to do customer discovery, run problem interviews, validate an idea with users, run a Mom Test, design an interview guide, or says "talk to customers", "validate the problem", "interview users", "Mom Test this", "did real users want it", "synthesize my interviews", "I just talked to N people". Sub-skill of `venture-exploration`. Hard-bans "would you use this?", solution-pitching, friend/family-only ICP, and treating compliments as validation. Calls `secure-*` before synthesizing any pasted external transcripts.
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。
Orchestrator for the experimentation skill suite — turn assumptions and product questions into rigorous, well-instrumented experiments and decision-grade readouts. Routes through backlog → spec → runbook → readout based on user need and existing artefacts. Platform-agnostic with PostHog as the primary binding. Load when the user asks to design an experiment, A/B test something, set up an experiment, run a holdout, test a hypothesis, decide what to test next, read out experiment results, analyse a test, or says "should we A/B test this", "experiment on the landing page", "is this lift real", "ship or kill this test", "what should we test next", "build an experiment backlog", "test the pricing page", "validate this with an experiment".
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 a structured retrospective after development-phase runs of your product's agents — interview the owner in plain language about what went well and poorly, draft ranked improvement hypotheses, then design and run small n=1/n=2 experiments with pre-declared success criteria, guardrails, stop conditions, and a cost/ROI kill-switch. Load when the user says how did that run go, retro this run, the agent output was bad, what should we improve, draft hypotheses, run a small experiment, or after repeated dev runs of an agentic system produce uneven quality. Priority: output quality over performance over cost, each with diminishing-returns stops. NOT a product A/B test (experimentation), NOT coding-agent harness repair (harness-evolution), NOT production-scale learning (runtime-learning-loop).
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。