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概要と使いどころ
Discover, compare, and compose existing open-source GitHub repositories for a user's goal, using GitHub MCP for live discovery and verification plus Context7 semantic retrieval over repository code and official documentation. Use when a user asks for GitHub repo recommendations, open-source alternatives, a multi-repository solution stack, project comparison, or help choosing an implementation to adopt.
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。
Provider-neutral entry point for discovering, planning and synchronizing MCP configuration between user-selected providers and app classes. The user selects truth, targets and scope; no provider is an implicit hub.
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。
Provider-neutral planner for synchronizing MCP configuration, skills and rule files across agent providers and app classes. It discovers evidenced local options and lets the user choose truth, targets, direction and conflicts.
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。
Produces a DRAFT product requirements document from the discovery notes, interview summaries, support themes, analytics notes and stakeholder messages the user provides: problem statement, target users, goals with measures as stated, numbered requirements each with a testable acceptance criterion, non-goals, constraints, dependencies and open questions, with every statement tagged evidenced, assumed or UNKNOWN so each assumption is visible for the product owner to confirm. Use when the user asks to "write a PRD", "draft the product requirements", "turn these discovery notes into requirements", "document what this feature needs to do" or "build the requirements doc for this epic". Do not use for supplier-facing requirements in a tender, use rfp-requirements-pack instead; for a technical design decision, use architecture-decision-record; for the change ticket that ships the work, use change-request-pack. Drafts for human review; never approves, authorises or signs off.
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。
Discover AAS skills for an explicit task and compare their complete instructions without installing them.
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 "find influencers", "build an influencer list", or "discover creators in [niche]"; produces a multi-platform candidate pool, per-influencer profiles, authenticity red-flag screening, and a tiered shortlist with preliminary triage signals. Not for STAR scoring or ranking a known shortlist — use fit-scorer. 达人挖掘/找达人/创作者名单
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。
Sales enablement, technical presales and deal acceleration for B2B SaaS revenue teams. Use this skill when planning outbound campaigns, running discovery calls, building deal strategy, creating battle cards, writing proposals, responding to RFPs, preparing a product demo, scoping a proof of concept or pilot, answering a security questionnaire, executing sales sequences, or coaching qualification. Also triggers on: outbound, cold outreach, deal strategy, pipeline, battle card, proposal, RFP, discovery call, MEDDPICC, sales sequence, qualification, sales engineer, solutions engineer, presales, demo plan, demo script, POC, proof of concept, pilot success criteria, technical evaluation, technical win, security questionnaire, vendor security review, SOC 2 questionnaire, technical objection, mutual action plan, MAP, close plan, mutual close plan, buyer enablement, the deal is stalled, deal stalled after the demo, how do I get this deal to close, close date keeps slipping, JOLT, buyer indecision, no-decision loss.
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。
Interactive Domain-Driven Design modeling sessions based on DDD Distilled (Vaughn Vernon) and Domain Modeling Made Functional (Scott Wlaschin). Guides users through strategic and tactical design via 13 phases: discover, storming, contexts, mapping, aggregates, events, validate, glossary, workflows, types, simulate, publish, sync. Phase 13 (sync) reconciles divergences found by --analyze between the domain model and the implementation — judging whether the model or the code is authoritative, then planning and implementing the fix and re-aligning the model. Phases 9-11 take the conceptual model from phases 1-8 and produce workflow pipeline designs, compilable type definitions (TypeScript, Kotlin, Scala, Rust, C#, F#), workflow verification via type-level tests, and automatic UI field enumeration from the domain model. Phase 12 (publish) renders all docs/domain artifacts into one self-contained, cross-linked HTML site (separate files joined by a shared nav). Each phase is an interactive dialogue where AI acts as facilitator and domain expert challenger. Use when: "DDD", "ドメイン設計", "ドメインモデリング", "Event Storming", "Bounded Context", "集約設計", "ユビキタス言語", "コンテキストマップ", "ワークフロー設計", "パイプライン設計", "ステップ分割", "中間型", "型駆動フロー", "型駆動設計", "Domain Modeling Made Functional", "Railway Oriented Programming", "入力画面項目", "フォーム項目洗い出し", "UI 項目抽出", "HTMLにまとめる", "ドキュメントサイト化", "成果物を1つのHTMLに", "publish", "モデルと実装の差異", "差異解消", "実装との乖離", "モデルとコードを一致", "差異の実装計画", "sync", "複数フェーズを逐次実行", "フェーズをまとめて実行", "/ddd run", "サブコマンド一覧", "/ddd list", "/ddd", "ドメイン分析したい", "モデリングしたい", or any domain design / type modeling activity.
Execute recursive breadth-before-depth ideation discovery with Deep Think, CX gate enforcement, and feature deepening
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 working with Cyberark — cyberArk privileged access management for safe management, privileged account discovery, session monitoring, credential rotation status, and security audit. Covers Vault, PVWA, PSM, and CyberArk Privilege Cloud. Read this skill before any CyberArk operations — it enforces discovery-first patterns and strict read-only safety rules.
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 working with Consul — hashiCorp Consul service discovery and mesh management. Covers service registration, health checks, KV store operations, intentions (ACLs), Connect service mesh, datacenter federation, and prepared queries. Use when managing service discovery, debugging health checks, configuring service mesh intentions, or working with Consul KV store.
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 the AgentD workflow to mine evidence, design molecules, and rank candidates with SAR plus ADMET annotations for early drug discovery tasks.
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。
Discover and filter URLs on a known website through Tavily without extracting every page. Use to locate a specific subpage, inspect site structure, or prepare a bounded map-then-extract workflow.
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。
Expert en biotechnologies avancées (bioinformatics, genomics, CRISPR, drug discovery, DZ research)
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。
Find and rank influencers by niche, engagement, and authenticity using Xpoz. Searches Twitter, Instagram, and Reddit for active voices in any topic. Use when asked to "find influencers", "discover thought leaders", "who's talking about X", "influencer research", or "find KOLs".
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。
Survey one surface of tdmcp (artist controls, library/packaging, CLI/DX, AI/LLM, or TouchDesigner depth) for candidate NEW features — inventory what exists, cross-check the roadmap, apply the gap-finding lenses, vet each idea, and emit a structured, novelty- and confidence-labelled candidate list to _workspace/discovery/. Use when a td-surveyor agent is scouting a surface during the feature-discovery harness.
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。
Survey the whole tdmcp project and produce a prioritized list of NEW features it could implement — across artist controls, CLI/DX, AI/LLM integration, and TouchDesigner depth. Use whenever the user wants to brainstorm, discover, survey, list, or audit what features/tools/effects/controls/commands/prompts/capabilities tdmcp *could* add, asks 'what could we build / what's missing / what are the opportunities / ideas for the project', or wants a feature backlog or gap analysis. Also for follow-ups: re-run, refresh, update, re-survey, deepen, or re-prioritize the backlog, or survey just one surface (e.g. 'CLI ideas only'). This is the IDEATION harness — it produces a list to decide from; it does NOT build. When the user has already chosen a feature and wants it implemented/shipped/added, use tdmcp-pipeline 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。
Drive a whole tdmcp feature BACKLOG to completion as resumable, wave-by-wave releases — the campaign layer ABOVE tdmcp-pipeline/tdmcp-feature-lead. Use whenever the user wants to implement an ENTIRE backlog or discovery file (e.g. _workspace/discovery*/FEATURE_BACKLOG*.md), 'all the features', many features across multiple releases, or a long autonomous build campaign, AND for every follow-up: continue/resume the campaign, run the next wave, re-run a failed wave, fold in QA results, or check campaign status. Backed by a ledger.json so re-running is idempotent (skips shipped work, resumes interrupted work) and resilient (retry-once then quarantine-and-continue). For a SINGLE feature or one small batch, use tdmcp-pipeline instead; this skill is for the whole ledger.
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。
web アプリの機能を構造化して書き下すワークフロー。新規/既存の 2 モード、5 フェーズで構造化（先行事例調査は並列3エージェント、Reader Test 付き）。「機能を考えたい」「機能定義したい」「web アプリ作りたい」「機能から設計したい」「新しい機能」で発動。※ 曖昧な状態の掘り下げは deep-interview、要件統合は discovery-council、設計は design を使う。
要件が曖昧なとき、ソクラテス式に1問ずつ質問して要件を掘り下げる。十分に明確になったら discovery-council にハンドオフ。「要件が曖昧」「何を作ればいいか」「掘り下げて」「インタビューして」で発動。※ 完成した plan/design を詰問するなら grill、非対話で一括批判するなら critic。
When the user wants to implement, optimize, or use App Clips for app discovery and conversion. Use when the user mentions "App Clip", "app clip code", "mini app", "instant app", "App Clip card", "App Clip link", "no download required", "instant experience", or wants to understand how App Clips appear in App Store search. For general App Store discoverability, see aso-audit. For marketing campaigns, see ua-campaign.
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。
Discover and configure Bluetooth and Wi-Fi accessories using AccessorySetupKit. Use when presenting a privacy-preserving accessory picker, defining discovery descriptors for BLE or Wi-Fi devices, handling accessory session events, migrating from CoreBluetooth permission-based scanning, or setting up accessories without requiring broad Bluetooth permissions.
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。
Integrate AFL++ coverage-guided fuzz testing into CI/CD pipelines to discover memory corruption, input handling, and logic vulnerabilities in C/C++ and compiled applications.
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 API Security Posture Management to continuously discover, classify, and score APIs based on risk while enforcing security policies across the API lifecycle.
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。