Web3 Infrastructure Architect: Indexers, RPC, wallets, account abstraction, key management and off-chain services.
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。
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Web3 Infrastructure Architect: Indexers, RPC, wallets, account abstraction, key management and off-chain services.
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。
Map business goals to user psychology through structured workshops
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 UX scenario outlines from Trigger Map through structured micro-steps
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。
AI-assisted development, testing, and reverse engineering through structured agent collaboration
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。
Write and rewrite Turkish so it reads as native Turkish rather than translated English. Use for Turkish marketing copy, product and UI text, localization, documentation, support, legal or security prose, and reviews of AI-written Turkish. Detect translationese, copied clause structure, nominalization, wrong case and collocations, generic helper verbs, SaaS and sales calques, jargon leakage, forced slogans, corporate abstraction, cross-sector template residue, unsupported operational claims, and page-level repetition.
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 distinctive, production-grade frontend interfaces with high design quality using Mobile First strategy. Analyzes design systems from screenshots, generates Tailwind CSS + Shadcn UI configurations, and retrofits existing projects. Optimized for Claude Opus 4.5 with structured decision trees and self-verification checkpoints.
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 code changes adversarially using parallel review layers (Blind Hunter, Edge Case Hunter, Acceptance Auditor) with structured triage into actionable categories. Use when the user says "run code review" or "review this 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。
Use this skill when building, debugging, or answering questions about Liveblocks. Liveblocks gives you the building blocks and infrastructure to enable people and AI to work together inside your app, powering realtime collaboration. Liveblocks features include collaboration, rooms, organizations, workspaces, comments, composer, threads, notifications, multiplayer, conflict resolution, realtime presence, avatar stacks, AI collaborators, AI agents, text editors, Tiptap, BlockNote, Lexical, React Flow, Chat SDK. Common components include AiChat, Thread, InboxNotification, Composer, Toolbar (for Lexical Tiptap), FloatingToolbar, FloatingComposer, FloatingThreads, AnchoredThreads. Common hooks include useThreads, useStorage, useMutation, useOthers, useInboxNotifications, useAiChats. Common issues are related to authentication (ID tokens vs access tokens), permissions, room limits, connection errors, user info.
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。
Generate Marp-compatible slide decks from structured JSON schema. Converts context into presentations for tech talks, sprint demos, and tutorials.
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 structured implementation plans from requirements. Produces master plan + phase files for enterprise-scale project management. Master plan = overview (<80 lines). Phase files = execution detail (<200 lines each). Each session handles 1 phase. Uses opus for deep reasoning.
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。
Business Analyst agent. Use when starting a new feature requiring requirements elicitation BEFORE plan or cook. Asks probing questions, identifies hidden requirements, maps stakeholders, defines scope boundaries, and produces a structured Requirements Document that plan and cook consume.
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。
Root cause analysis for bugs and unexpected behavior. Traces errors through code, uses structured reasoning, and hands off to fix when cause is found. Core of the debug↔fix mesh. When the diagnosed cause is a memory leak in a long-running process, escalates to perf for cost-impact framing (leaks drive OOM-restart → cold-start → autoscaler spend, often 20-40% bill inflation).
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。
Autonomous project bootstrapper. Generates complete project from a description — structure, code, tests, docs, config. Orchestrates ba → plan → design → fix → test → docs → git in one pipeline. The "0 to production-ready" 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。
Use when receiving external input that needs structured intake before action — PR review feedback, code review comments, OR issue tracker items (bug reports, feature requests). PR Review Mode (default) verifies suggestions before implementing. Issue Triage Mode classifies issues into a state machine (ready-for-agent / ready-for-human / needs-info / wontfix) and emits AGENT-BRIEFs for AFK execution. Prevents blind implementation, enforces verification-first discipline.
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。
Creates structured handoff briefings between agents. Use when delegating complex work to subagents that would otherwise lose context. Packages task context, constraints, and progress into a compact packet that subagents can consume without re-reading the full conversation. Prevents the 'lost context' problem in multi-agent delegation.
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。
Structured incident response. Use when user reports an outage, production error, or says 'incident', 'something is down', 'users are affected'. Triage severity, contain blast radius, root-cause, document timeline, generate postmortem.
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。
Structured reasoning frameworks for complex problems. 19 analytical frameworks, 12 cognitive bias detectors, 10 decomposition methods, 10 mental models, Cynefin domain classification, ethical dimension check, and 6 communication patterns. McKinsey-grade problem solving for AI coding assistants.
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。
Creative ideation and solution exploration. Generates multiple approaches with trade-offs, uses structured frameworks (SCAMPER, First Principles), and hands off to plan for structuring.
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。
Developer reference for building applications, tools, and agents on the Pi Durable agent harness (@earendil-works/pi-durable) and the pi-ai model layer. Use when writing or debugging code that imports @earendil-works/pi-durable or pi-ai: assembling a Harness over memory/SQLite/JSONL/Durable Object storage, submitting input and waiting for answers, defining tools with TypeBox schemas and structured output, calling tools from tools, hooks and guards, durable tasks with checkpoints and ownership, subagents and child tasks, documents and migrations, code mode, tool search, per-conversation environments, compaction, recovery after a crash, storage and environment conformance tests, or choosing models and providers. Also use when a durable/agent-runtime behavior question comes up: what survives a restart, why an input stayed queued, why a task is blocked or orphaned, how abort cascades, or what the Pico5 specification requires.
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 asks for a literature review, academic deep dive, research report, state-of-the-art survey, topic scoping, comparative analysis of methods/papers, grant background, or any request that needs multi-source scholarly evidence with citations. Also trigger proactively when a user question clearly requires academic grounding (e.g. "what's known about X", "compare approach A vs B in the literature", "summarize the field of Y"). Runs an 8-phase (Phase 0..7), script-driven research workflow across 7 federated sources (OpenAlex, arXiv, Crossref, PubMed, DBLP, bioRxiv, Exa) with optional Semantic Scholar / Brave MCP enrichment, with deduplication, transparent ranking, dual-backend citation chasing (OpenAlex + Semantic Scholar), self-critique, and structured report output with verifiable citations.
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。
Reviews Rust test code for unit test patterns, integration test structure, async testing, mocking approaches, and property-based testing. Covers Rust 2024 edition changes including async fn in traits for mocks,
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。
Automatic graph layout using dagre with React Flow (@xyflow/react). Use when implementing auto-layout, hierarchical layouts, tree structures, or arranging nodes programmatically. Triggers on dagre, auto-layout, automatic layout, getLayoutedElements, rankdir, hierarchical graph.
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 and plan iOS animations with structured specs covering transitions, micro-interactions, gesture-driven motion, and loading states. Use when the user asks to plan, design, or spec out animations for an iOS app — including screen transitions, navigation animations, interactive gestures, onboarding flows, or any motion design work. Also use when the user wants animation recommendations or wants to decide between animation approaches before writing 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。