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概要と使いどころ
Build agents and multi-agent systems with the Swarms framework — the Agent class, tools, autonomous loops, memory, and the 15+ multi-agent architectures (SequentialWorkflow, ConcurrentWorkflow, GraphWorkflow, HierarchicalSwarm, SwarmRouter, and more). Use whenever writing, reviewing, or debugging code that imports `swarms`.
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。
When the user wants to define GTM metrics, build a metrics dashboard, measure pipeline efficiency, or track AI product performance. Also use when the user mentions 'GTM metrics,' 'revenue latency,' 'pipeline metrics,' 'TTFV,' 'time-to-first-value,' 'data health,' 'attribution,' 'conversion rate,' 'CAC,' 'LTV,' 'NRR,' 'GTM dashboard,' 'magic number,' 'pipeline velocity,' or 'funnel metrics.' This skill covers GTM measurement from metric selection through dashboard design, including AI-specific cost metrics, attribution models, and weekly review cadences. Do NOT use for technical implementation, code review, or software 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。
When the user wants to build video-first cold outreach, create personalized video at scale, implement async selling, or use AI demo generation for prospecting. Also use when the user mentions 'video outreach,' 'personalized video,' 'video prospecting,' 'Tavus,' 'Sendspark,' 'HeyGen,' 'video email,' 'async selling,' 'video demo,' or 'made this for you.' This skill covers video-first outreach systems from personalization through conversion optimization. Do NOT use for technical implementation, code review, or software 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。
When the user wants to sell through social media, optimize LinkedIn for sales, build DM sequences, or convert content engagement into pipeline. Also use when the user mentions 'social selling,' 'LinkedIn selling,' 'LinkedIn DMs,' 'social prospecting,' 'LinkedIn Sales Navigator,' 'DM sequences,' 'LinkedIn outreach,' 'social pipeline,' or 'LinkedIn optimization.' This skill covers social selling strategy from profile optimization through DM-to-deal conversion. Do NOT use for technical implementation, code review, or software 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。
React and Next.js performance optimization guidelines from Vercel Engineering. Use when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements. Do NOT use for component API architecture or composition patterns (use react-composition-patterns 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。
When the user wants to launch a product across multiple platforms, plan a Product Hunt launch, build a waitlist, or execute a multi-channel launch strategy. Also use when the user mentions 'product launch,' 'Product Hunt,' 'launch strategy,' 'waitlist,' 'beta launch,' 'BetaList,' 'Hacker News,' 'launch day,' 'AppSumo,' 'multi-channel launch.' This skill covers multi-platform launch execution from pre-launch through post-launch optimization. Do NOT use for technical implementation, code review, or software 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。
When the user is a solo founder building their GTM motion, wants to scale without hiring, or needs to design an AI agent team for go-to-market. Also use when the user mentions 'solo founder,' 'one-person startup,' 'solopreneur,' 'bootstrapped,' 'no team,' 'AI agents as team,' 'scaling without hiring,' 'founder-led sales,' 'lean GTM,' 'one-person company,' or 'no employees.' This skill covers the complete solo founder GTM playbook from stack selection through agent team design, revenue-stage transitions, time allocation, and when to finally hire. Do NOT use for technical implementation, code review, or software 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。
Repository-grounded threat modeling that enumerates trust boundaries, assets, attacker capabilities, abuse paths, and mitigations, and writes a concise Markdown threat model. Use when the user asks to threat model a codebase or path, enumerate threats or abuse paths, or perform AppSec threat modeling. Do NOT use for general architecture summaries, code review, security best practices (use security-best-practices), or non-security design 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。
When the user wants to build programmatic SEO with AI, create competitor alternative pages, optimize for AI Overviews, or scale content production. Also use when the user mentions 'SEO,' 'programmatic SEO,' 'AI content,' 'competitor alternative pages,' 'AI Overviews,' 'search optimization,' 'DataForSEO,' 'content at scale,' 'keyword strategy,' or 'organic traffic.' This skill covers AI-powered SEO strategy from keyword research through programmatic page generation. Do NOT use for technical implementation, code review, or software 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。
When the user wants to build data enrichment workflows, score leads against ICP, set up Clay waterfalls, or improve contact data quality. Also use when the user mentions 'enrichment,' 'data enrichment,' 'Clay,' 'waterfall enrichment,' 'ICP scoring,' 'lead scoring,' 'intent data,' 'contact verification,' 'Apollo,' 'ZoomInfo,' or 'data quality.' This skill covers lead enrichment waterfalls, ICP scoring frameworks, and contact verification systems. Do NOT use for technical implementation, code review, or software 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。
When the user wants to create AI-generated ad creative, test performance creative, manage creative fatigue, or optimize paid media with AI tools. Also use when the user mentions 'ad creative,' 'performance creative,' 'creative testing,' 'creative fatigue,' 'Meta ads,' 'Google ads,' 'TikTok ads,' 'AI ads,' 'ad budget,' 'ROAS,' 'Advantage+,' or 'Performance Max.' This skill covers AI-powered paid creative from generation through performance optimization. Do NOT use for technical implementation, code review, or software 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。
When the user wants to reduce churn, build expansion revenue, automate customer success, or optimize net revenue retention. Also use when the user mentions 'churn,' 'retention,' 'expansion revenue,' 'upsell,' 'NRR,' 'net revenue retention,' 'customer success,' 'land and expand,' 'closed-lost,' or 'renewal.' This skill covers expansion and retention systems from usage triggers through automated customer success. Do NOT use for technical implementation, code review, or software 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。
When the user wants to create UGC ad campaigns, recruit UGC creators, generate AI UGC content, or scale with user-generated content. Also use when the user mentions 'UGC,' 'user-generated content,' 'creator ads,' 'Spark Ads,' 'whitelisting,' 'AI UGC,' 'Arcads,' 'Creatify,' 'creator brief,' or 'UGC testing.' This skill covers the UGC growth framework from creator recruitment through AI-powered scaling. Do NOT use for technical implementation, code review, or software 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。
When the user wants to build a partner program, launch an affiliate program, design integration partnerships, or create distribution partnerships. Also use when the user mentions 'partnerships,' 'affiliate program,' 'referral program,' 'partner ecosystem,' 'integration partner,' 'reseller,' 'co-marketing,' 'PartnerStack,' or 'revenue share.' This skill covers partner and affiliate program design from recruitment through performance optimization. Do NOT use for technical implementation, code review, or software 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。
When the user wants to turn content into revenue, build a content-led GTM motion, reverse engineer distribution, or repurpose content across platforms. Also use when the user mentions 'content marketing,' 'content-led growth,' 'content to pipeline,' 'distribution,' 'content repurposing,' 'content strategy,' 'thought leadership,' 'newsletter,' 'content flywheel,' 'organic growth.' This skill covers content-to-revenue systems from creation through pipeline attribution. Do NOT use for technical implementation, code review, or software 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。
When the user wants to price an AI product, choose a charge metric, design pricing tiers, or optimize margins. Also use when the user mentions 'AI pricing,' 'usage-based pricing,' 'consumption pricing,' 'outcome pricing,' 'BYOK,' 'bring your own key,' 'per-seat pricing,' 'pricing tiers,' 'AI margins,' 'cost per token,' or 'pricing model.' This skill covers pricing strategy, packaging, and margin management for AI-native products. Do NOT use for technical implementation, code review, or software 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。
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. Do NOT use for React/Next.js performance optimization (use react-best-practices 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。
Technology-agnostic guidance for modular systems: bounded contexts, clear boundaries, composability, state isolation, explicit contracts, failure containment, scaffolding workflows, split/merge criteria, sub-units inside a context, and compliance review signals. Use when designing or reviewing module structure, service boundaries, package layout, cross-cutting dependencies, "how should we split this?", modularity assessments, coupling between domains, greenfield context design, or architecture discussions without assuming a specific framework, language, or repository layout. Do NOT use for executing the full Patterns 1–5 repo decomposition pipeline or per-pattern inventories (use modular-decomposition), phased extraction roadmaps as the main deliverable (use decomposition-planning-roadmap), or end-to-end legacy migration strategy (use legacy-migration-planner).
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。
When the user wants to build an AI-powered outreach system, write cold emails, improve deliverability, or scale personalized outreach. Also use when the user mentions 'cold email,' 'cold outreach,' 'outreach automation,' 'Instantly,' 'Smartlead,' 'Clay,' 'email sequences,' 'deliverability,' 'personalization at scale,' 'reply rate,' or 'outreach stack.' This skill covers the complete AI cold outreach system from signal detection through conversion. Do NOT use for technical implementation, code review, or software 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。
Feature planning and implementation with 4 adaptive phases (Specify, Design, Tasks, Execute). Auto-sizes depth by complexity. Writes testable requirements in EARS notation, atomic tasks, atomic Conventional Commits, and requirement traceability. Ships deterministic Python validation scripts so structural gates are enforced by code, not memory. Features an independent Verifier (author != verifier, evidence-or-zero), a discrimination sensor, a decision log (STATE.md), a test-coverage matrix, and a self-improving lessons layer. Stack-agnostic and tool-agnostic. Use when (1) planning features, (2) implementing with verification and atomic commits, (3) validating an implementation against a spec. Triggers on "specify feature", "discuss feature", "design", "tasks", "implement", "validate", "verify work", "UAT", "record decision", "pause work", "resume work". Do NOT use for pure architecture decomposition analysis or standalone technical design documents.
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 a question, decision, plan, tradeoff, or claim needs a rigorous verdict and one perspective is not enough. Spawns a panel of 3 to 5 subagent jurors that form independent blind opinions, deliberate anonymously under an anti-anchoring and anti-sycophancy protocol, and return one committed verdict with confidence, preserved dissent, and a concrete next action. Domain-agnostic across engineering, architecture, data, product, hiring, strategy, vendor choice, build-vs-buy, and research design. Trigger phrases include "convene a jury", "have agents debate and decide", "get a panel to decide", "multi-agent decision", "stress-test this and decide", "monte um juri", "tribunal de agentes", "painel para decidir". Do NOT use to only critique without deciding (use the-fool for that), to build a plan or write the solution itself, or for simple factual lookups.
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。
Groups existing components into logical business domains to plan service-based architecture. Use when asking "which components belong together?", "group these into services", "organize by domain", "component-to-domain mapping", or planning service extraction from an existing codebase. Do NOT use for identifying new domains from scratch (use domain-analysis) or analyzing coupling (use coupling-analysis).
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 comprehensive Technical Design Documents (TDD) with mandatory and optional sections through interactive discovery. Use when user asks to "write a design doc", "create a TDD", "technical spec", "architecture document", "RFC", "design proposal", or needs to document a technical decision before implementation. Do NOT use for README files, API docs, or general documentation (use docs-writer 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。
Spec-driven feature work that freezes obligations instead of the plan: one human-reviewed plan with EARS criteria, path, entities, interface and one-way doors, then proof-backed checks, then build, then an independent Verifier. Use when the user says "tlc-spec-lean", "plan feature", "specify feature", "write the checks", "build this plan", or "verify work". Do NOT use for standalone design documents unattached to a feature, architecture decomposition analysis, or work that already has a task list or checklist to execute.
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。