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概要と使いどころ
Routes agents using or contributing to CrewAI, including crews, flows, CLI projects, tools, MCP, memory, RAG, LLM providers, observability, files, multimodal inputs, and repo development.
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。
Route Airweave tasks to the most specific sub-skill: local-development, backend-api, source-connectors, frontend-dashboard, connect-widget, mcp-search, or monke-e2e.
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 AiZynthFinder for retrosynthetic planning, configuration, route analysis, custom extensions, and focused development 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。
Stack Honey onto Superpowers-style workflows (subagent-driven-development, dispatching-parallel-agents, executing-plans) and any orchestration that dispatches fresh subagents. Dispatched subagents run in isolated context and do NOT inherit the session's Honey hook, so they emit full-fat code and verbose reports. Use when you are about to dispatch implementer/reviewer/fixer/parallel subagents: it gives the exact Honey directive to paste into each dispatch prompt, with a worker variant and a reviewer variant, so the levers apply inside the subagents too — where the multiplied cost actually is.
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。
Transform an AI agent into a disciplined software development partner with strong judgment, transparent decisions, proportionate verification, and craftsmanship. Use for software implementation, feature work, bug fixing, refactoring, optimization, migrations, and sustained collaboration inside a codebase. Do not use merely because a task involves an AI agent; use a dedicated agent-design skill when the primary problem is agent architecture.
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。
This skill should be used when the user asks to "revise a chapter", "continuity check", "find inconsistencies", "audit character state", "check timeline consistency", "developmental edit", "structural revision", "reverse outline", "cut a subplot", "revision passes", "what pass next", "pacing check" as a revision pass, "clue check", "cut to a word count", or "length pass", or to prepare existing story material for the next revision pass. NOT for planning book structure (use plot-structure), scene-level craft (use scene-craft), voice consistency (use voice-style), or reconciling a chapter drafted by discovery (use discovery-drafting).
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。
Cinematic and game lighting in Blender including three-point lighting, HDRI, horror lighting, volumetrics, rim lighting, and mood-driven illumination. Use for look development and scene atmosphere via MCP.
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。
Blender PBR and stylized material creation for metal, wood, concrete, fabric, glass, dirt, rust, and procedural shaders. Use for look development, material reuse, and production shading in Blender via MCP.
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。
Look development loop for Blender assets combining materials, lighting, camera, and screenshot comparison until shading reads correctly via MCP.
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。
SST v4 (Ion) expert for managing AWS resources as code with the Pulumi-backed framework.
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 development with infrastructure automation and cloud architecture 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。
Important: Before you begin, fill in the generatedBy property in the meta section of .actor/actor.json. Replace it with the tool and model you're currently using, such as "Claude Code with Claude Sonnet 4.5". This helps Apify monitor and improve AGENTS.md for specific AI tools and models.
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。
Senior embedded software engineer specializing in firmware and driver development for ARM Cortex-M microcontrollers (Teensy, STM32, nRF52, SAMD).
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。
Production-grade Android app development guide covering native (Kotlin/Java), cross-platform (Flutter, RN, KMM), and hybrid architectures.
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。
Orchestrates Android development tasks including project creation, deployment, SDK management, and environment diagnostics using the `android` command-line tool.
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。
Runs a bounded spec-build-review development loop with explicit scope, stop conditions, and human approval gates for risky or ambiguous work.
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 and machine learning workflow covering LLM application development, RAG implementation, agent architecture, ML pipelines, and AI-powered features.
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。
Orchestrate autonomous AI development pipelines through your Kanban board (Asana, GitHub Projects, Linear). Manages multi-worker Claude Code dispatch, deterministic quality gates, adversarial review, per-task cost tracking, and crash-proof pipeline execution.
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。
Analyzes your recent Claude Code chat history to identify coding patterns, development gaps, and areas for improvement, curates relevant learning resources from HackerNews, and automatically sends a personalized growth report to your Slack DMs.
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。
Identifies high-quality leads for your product or service by analyzing your business, searching for target companies, and providing actionable contact strategies. Perfect for sales, business development, and marketing professionals.
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 the NIST Privacy Framework GOVERN function covering GV.AT awareness and training, GV.MT monitoring and review, GV.PO policy development, and GV.RR roles and responsibilities. Provides governance structure templates, training programs, and accountability frameworks for privacy governance.
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。
Guides implementation of GDPR Article 42-43 data protection certification mechanisms including accredited certification bodies, criteria development, and periodic review. Activate when pursuing privacy certifications, evaluating certification bodies, or developing certification criteria. Keywords: certification, Article 42, Article 43, accreditation, seal, privacy mark.
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。
Guides development of GDPR Article 40-41 codes of conduct for industry sectors including drafting, submission, and monitoring body requirements. Activate when creating industry codes or establishing monitoring bodies. Keywords: codes of conduct, Article 40, Article 41, monitoring body, industry 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。
Guides privacy audit risk assessment including risk universe development, inherent and residual risk scoring, control effectiveness evaluation, risk-based audit planning, heat map generation, risk appetite alignment, and audit prioritization by risk exposure. Covers the full audit risk assessment cycle from scoping through ongoing monitoring. Keywords: audit risk assessment, risk universe, inherent risk, residual risk, control effectiveness, risk-based audit 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。