「ema」の検索結果

Automate ActiveCampaign tasks via Rube MCP (Composio): manage contacts, tags, list subscriptions, automation enrollment, and tasks. Always search tools first for current schemas.

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。

Automate Amplitude tasks via Rube MCP (Composio): events, user activity, cohorts, user identification. Always search tools first for current schemas.

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。

Systematically evaluate architecture decisions, document trade-offs, and select appropriate patterns. This skill should be used when the user asks about 'architecture decision', 'ADR', 'design pattern selection', 'technology choice', or needs to evaluate architectural trade-offs. Keywords: architecture, ADR, patterns, trade-offs, technical debt, quality attributes, decision record.

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。

Automate Asana tasks via Rube MCP (Composio): tasks, projects, sections, teams, workspaces. Always search tools first for current schemas.

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。

Automate Airtable tasks via Rube MCP (Composio): records, bases, tables, fields, views. Always search tools first for current schemas.

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。

Captures clause risks, compliance gaps, precedent shifts, contract deviations, regulatory changes, and litigation exposure to enable continuous legal operations improvement. Use when: (1) An unfavorable clause is accepted or slips through review, (2) A compliance deadline is missed or approaching, (3) A new regulation impacts the organization, (4) A contract remains unsigned past SLA, (5) An IP infringement notice is received, (6) New case law changes interpretation in a relevant jurisdiction, (7) A data subject access request reveals process gaps.

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。

Systematic performance profiling and optimization methodology. Covers CPU profiling, memory profiling, heap analysis, goroutine/thread analysis, FlameGraph generation, latency profiling, database query profiling, network I/O profiling, and continuous performance regression detection. USE WHEN: investigating performance issues, optimizing slow code, reducing memory usage, diagnosing GC/CPU bottlenecks, finding N+1 queries, analyzing pprof/flamegraph output, or establishing a performance baseline. Triggers on "profiling", "performance analysis", "slow code", "flame graph", "pprof", "heap dump", "memory leak", "CPU spike", "bottleneck".

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。

Temu, SHEIN, AliExpress, and TikTok product selection big data analysis agent. Identify trending products, analyze competition, estimate demand, and find sourcing opportunities across fast-fashion and marketplace platforms. Triggers: temu product selection, shein product research, aliexpress trending, tiktok shop products, temu selector, fast fashion products, temu trending, shein trends, product sourcing, dropshipping products, temu winning products

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。

Fetch personalized daily horoscope forecasts from zodiac-today.com API based on natal chart calculations. Use when a user wants: (1) daily guidance on what activities to pursue or avoid, (2) life planning help — best days for interviews, travel, romance, important decisions, (3) energy/focus/luck/romance forecasts to optimize their schedule, (4) lucky colors and numbers for the day, (5) future date analysis for planning events, trips, or milestones (paid tiers). Triggers: horoscope, zodiac, star sign forecast, daily guidance, lucky day, best day to, astrology advice, what should I do today, is today a good day for, plan my week astrology. Required env: ZODIAC_API_KEY (hsk_ API key), ZODIAC_PROFILE_ID (birth chart profile ID). Collects sensitive PII (email, birth date, birth city) for natal chart — requires user consent.

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。

World-class autonomous sales and revenue skill system. Use ANY time the user asks to sell, pitch, prospect, close, negotiate, launch, monetize, build funnels, write outreach, craft proposals, develop pricing, design offers, write sales copy, create email sequences, plan campaigns, position products, handle objections, create playbooks, build pipeline, forecast revenue, develop GTM strategy, optimize conversions, write ad copy, create sales decks, score leads, nurture prospects, upsell, cross-sell, retain customers, write case studies, price products, structure enterprise deals, create battle cards, script discovery calls, build affiliate programs, plan product launches, create webinar funnels, design pricing pages, A/B test offers, analyze unit economics, calculate LTV/CAC, or ANY other sales, revenue, monetization, go-to-market, or commercial growth task. If it involves selling, revenue, deals, pipeline, or commercial strategy — USE THIS SKILL. Trigger aggressively.

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。

Complete marketing strategy for Shopify stores. SEO, email marketing, paid ads, social media, conversion optimization, and retention tactics specifically tailored for Shopify/DTC brands.

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。

Breaks down trading ideas into component parts for systematic Pine Script implementation. Use when analyzing trading concepts, decomposing strategies, planning indicator features, or extracting ideas from YouTube videos. Triggers on conceptual questions, "how would I build", YouTube URLs, or video analysis requests.

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。

Research markets with sizing, segmentation, competitor mapping, pricing checks, and demand validation that turn fuzzy ideas into decision-ready evidence. Use when (1) you need TAM, SAM, SOM, whitespace, or category sizing; (2) you must compare competitors, pricing, positioning, or customer segments before acting; (3) the user asks whether a niche, launch, expansion, or go-to-market bet is actually worth pursuing.

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 to "optimize entity presence", "build knowledge graph", "improve knowledge panel", "entity audit", "establish brand entity", "Google does not know my brand", "no knowledge panel", or "establish my brand as an entity". Works standalone with public search and AI query testing; supercharged when you connect ~~knowledge graph + ~~SEO tool + ~~AI monitor for automated entity analysis. For structured data implementation, see schema-markup-generator. For content-level AI optimization, see geo-content-optimizer.

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。

Query Google Search Console for SEO data - search queries, top pages, CTR opportunities, URL inspection, and sitemaps. Use when analyzing search performance, finding optimization opportunities, or checking indexing status.

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。

Gmail API integration with managed OAuth. Read, send, and manage emails, threads, labels, and drafts. Use this skill when users want to interact with Gmail. For other third party apps, use the api-gateway skill (https://clawhub.ai/byungkyu/api-gateway).

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。

Your brand voice locked across AI outputs. 15 cinematic styles. Design that does not read as AI.

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。

14 regulated-industry frameworks enforced on every output. Audit-ready on demand.

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。

Maxim Design System Intelligence — token architecture (primitive→semantic→component), component library governance, CSS variable systems, Tailwind integration, design-to-code handoff, Storybook, Figma token export. Activate for design system creation, token audits, component specs, dark mode systems, brand-to-token sync. Powered by Maxim behavioral science + Atomic Design + TOGAF 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。

Audit context files (CLAUDE.md, .claude/ tree, READMEs, docs) for broken references and verifiably stale content. Runs a deterministic offline link/path checker first, then a bounded semantic review where every finding must cite evidence. Reports findings; fixes only on request. Use when the user says "docs check", "/docs-checker", "check the docs for stale content", "audit CLAUDE.md", or when a scheduled cloud routine fires.

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。

PostgreSQL-specific code review assistant focusing on PostgreSQL best practices, anti-patterns, and unique quality standards. Covers JSONB operations, array usage, custom types, schema design, function optimization, and PostgreSQL-exclusive security features like Row Level Security (RLS).

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。

End-to-end skill for building, testing, linting, versioning, and publishing a production-grade Python library to PyPI. Covers all four build backends (setuptools+setuptools_scm, hatchling, flit, poetry), PEP 440 versioning, semantic versioning, dynamic git-tag versioning, OOP/SOLID design, type hints (PEP 484/526/544/561), Trusted Publishing (OIDC), and the full PyPA packaging flow. Use for: creating Python packages, pip-installable SDKs, CLI tools, framework plugins, pyproject.toml setup, py.typed, setuptools_scm, semver, mypy, pre-commit, GitHub Actions CI/CD, or PyPI publishing.

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。

Systematic Power BI performance troubleshooting prompt for identifying, diagnosing, and resolving performance issues in Power BI models, reports, and queries.

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。

OpenInference semantic conventions and instrumentation for Phoenix AI observability. Use when implementing LLM tracing, creating custom spans, or deploying to production.

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。