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Scout the TouchDesigner community for what's HYPED right now — community showcases, recent tutorials, generative-AI bridges, hardware interaction trends, visual-aesthetic trends of 2025-2026 — then propose tdmcp tools that ride those trends AND are easy to build. Use whenever the user wants to brainstorm new feature ideas based on what's trending in TouchDesigner, asks for 'hype' or 'trending' features, asks 'what are people doing in TD right now / what's hot / what's hype', wants tools inspired by community trends, asks to scout TD trends/aesthetics/integrations, or says things like 'ideias hype', 'novas ideias', 'o que está em alta', 'criar ferramentas para o que está bombando', 'tendências do TouchDesigner'. Also for follow-ups: refresh, rescout one surface, re-rank under another profile, deepen a trend, or filter for buildable-easy items. This is an EXTERNAL trend ideation harness — complementary to tdmcp-feature-discovery (which is INTERNAL gap analysis). It produces `_workspace/hype-scout/HYPE_TOOL_BACKLOG.md` ranked by Hype × Build-Ease; it does NOT build. Once a feature is chosen from the backlog, hand it to tdmcp-pipeline.

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 wants a research-paper figure Skill Factory: build, patch, package, or use reusable specialized paper-figure-making skills from lawful literature/corpus evidence. Generated skills must use a specialized-skill-first workflow, full-feasible local PDF coverage where available, startup-plan-only first replies, target-paper candidate/final image isolation, mandatory image-embedded visual-structure explanation, mandatory non-target concept/modeling example display for abstract visual decisions, saved subtype/style illustration atlases, ChatGPT web Create image / ChatGPT Images 2.0 rendering, Codex $imagegen-first rendering, sample-image transfer rules, all-step/current-position state footers, and a mandatory first-round diverse candidate board followed by P6b/P6c paper-local best-practice optimization before final prompt construction.

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 prototype in Paper Design (app.paper.design) — read/write designs via MCP, convert to React/Tailwind code, import HTML/CSS, sync design tokens. Also covers Paper Shaders (@paper-design/shaders-react) — 30+ shader React components (mesh gradient, fluted glass, liquid metal, god rays, halftone, grain gradient, pulsing border). Pairs with minoan-frontend-design for creative direction. Triggers on Paper Design, paper.design, design-to-code, artboard, Paper Shaders, Paper MCP, prototype.

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。

5つの専門エージェントがディスカッション型で競合のビジネスモデル・機能・価格・弱点を網羅的に分析し、 差別化ポイントと参入戦略を導出するスキル。 エージェント同士が対話・批判し合いながら調査し、ca-data-critic がライブモデレーターとして矛盾を検出・収束を判定する。 Phase 1 で競合プロファイル・レビュー・機能をディスカッション型で調査し、 Phase 2 でポジショニング戦略家が統合。 Gate 1（中間合意形成）→ Gate 2（最終検証 + Independent Validation + Devil's Advocate）の2段階ゲートで品質を担保。 Use when: 競合を分析したい、差別化ポイントを見つけたい、 市場のプレイヤーを調べたい、ポジショニングを考えたい。 Triggers: "競合分析", "competitive analysis", "競合調査", "差別化", "ポジショニング", "competitor", "競合", "市場プレイヤー", "ライバル調査", "competitive landscape"

HyperFrames (HTML + GSAP → MP4) でアプリのプロモ動画を決定論的に生成するスキル。 HyperFrames 公式スキル（19本）を土台として前提にし、素材の橋渡し・検証ゲート・ 納品仕様・誇張表現の禁止という「公式が扱わない層」だけを担当する。 SNS リール、LP ヒーロー動画、リリース告知、機能デモが対象。 Use when: プロモ動画を作りたい、告知動画を作りたい、HTML から動画を作りたい、 HyperFrames で動画を作りたい、リリース動画を作りたい、SNS 用の縦動画を作りたい。 Triggers: "HyperFrames", "hyperframes", "プロモ動画", "告知動画", "宣伝動画", "HTML から動画", "html to video", "リリース動画", "SNS動画", "縦動画", "リール"

Downloads a competitor's live ad creatives — the actual MP4s and JPEGs — from the Meta Ad Library into a local swipe folder, through the Novoads API. One sweep per competitor, priced by a live estimate before anything is charged, media pulled the moment the response lands because the CDN links expire, and every ad carried with its permanent Ad Library URL, the page running it, and how many audiences the creative is running against, closing with the three most established and why. Use when asked to spy on competitors, find what ads a brand is running, pull a competitor's video or static creatives, build or refresh a swipe file, check who is outspending you on Meta, or source a reference ad to recreate. It finds, ranks and files ads; it does not rebuild them — a static becomes your own ads, or a reusable template, via clone-image-ad. It writes no craft analysis and no creative brief. A sweep that finds nothing is a result, never an apology.

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 open Dependabot PRs, classifies by risk (patch/minor/major, security, lockfile-only), and merges safe ones or advises on what to do. Use when user mentions "dependabot", "dependabot PRs", "dependency updates", "merge dependabot", "review dependabot", "dependency PRs", "bump PRs", "update dependencies", or runs /dependabot-review command.

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。

Sync delta specs from an OpenSpec change to main specs. Use when the user wants to update main specs with changes from a delta spec, without archiving the change. Also use when the user says "openspec sync" or "opsx sync".

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。

Implements advanced TypeScript type systems, creates custom type guards, utility types, and branded types, and configures tRPC for end-to-end type safety. Use when building TypeScript applications requiring advanced generics, conditional or mapped types, discriminated unions, monorepo setup, or full-stack type safety with tRPC.

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 designing the human-executable UAT test cases that prove a Salesforce feature works for a specific persona — the per-persona scripts with preconditions, data setup, permission setup, ordered steps, and pass/fail evidence that close out an RTM row. Trigger keywords: UAT test case salesforce, user acceptance test script salesforce, manual test salesforce feature, UAT script per persona, UAT precondition data setup, UAT permission set assignment for testing, negative path UAT case. NOT for high-level UAT planning, defect classification, regression strategy, or sign-off (use admin/uat-and-acceptance-criteria). NOT for the Given/When/Then technique used to write the AC the case is derived from (use admin/acceptance-criteria-given-when-then). NOT for Apex test method generation (use agents/test-class-generator). NOT for test data factory patterns (use templates/apex/tests/TestDataFactory.cls). NOT for performance or load testing.

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。

Scaffold a Spec Kit (spec-driven development) project for GitHub Copilot by running `specify init --integration copilot --integration-options="--skills"`. USE FOR: starting a new spec-kit project, bootstrapping spec-driven development in an existing repo, installing spec-kit templates/scripts/commands for Copilot. DO NOT USE FOR: managing extensions/presets/bundles of an already-initialized project (use the speckit-extension / speckit-preset / speckit-bundle skills 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。

Manage Spec Kit workflow step types via `specify workflow step`. USE FOR: listing built-in and custom workflow step types, installing/removing a custom step type from a catalog, searching/showing step-type info, managing step-type catalog sources. DO NOT USE FOR: running or installing whole workflows (use speckit-workflow), or bundles (use speckit-bundle).

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 competitor comparison or alternative pages for SEO and sales enablement. Also use when the user mentions 'alternative page,' 'vs page,' 'competitor comparison,' 'comparison page,' '[Product] vs [Product],' '[Product] alternative,' 'competitive landing pages,' 'how do we compare to X,' 'battle card,' or 'competitor teardown.' Use this for any content that positions your product against competitors. Covers four formats: singular alternative, plural alternatives, you vs competitor, and competitor vs competitor. For sales-specific competitor docs, see sales-enablement.

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。

Structures a vague engineering request into a well-scoped task brief before any implementation begins. Use when the user has an engineering goal but the ask is missing which repos are in scope, what "done" means, constraints, or open questions. Triggers on "shape this", "scope this out", "frame this work", "write a brief for", "I want to build" (with unclear scope), or the /shape slash command. Produces a filled task template (multi-repo feature, single-repo change, investigation, or bugfix). Not for already-scoped work — go straight to execution. If the domain is unclear, ask one qualifying question before routing — for marketing intake see marketing-shaper, game-design intake see game-design-shaper.

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。

Calculates statistical power for high-dimensional genomics experiments (bulk RNA-seq, scRNA-seq, ATAC-seq, ChIP-seq, methylation, proteomics) under negative-binomial count models using RNASeqPower, PROPER, and simulation via powsimR, distinguishing per-gene from marginal (transcriptome-wide) power, the role of mean expression and dispersion, and the sequencing-depth-versus-replicate tradeoff. Covers simulation as the honest default for overdispersed counts, FDR-aware average power versus single-test power, observed/post-hoc power as an anti-pattern, and the winner's-curse / Type-S / Type-M consequences of underpowering. Use when planning replicate number for a sequencing experiment, deciding whether to add depth or samples, choosing closed-form versus simulation power, estimating power from pilot dispersions, or justifying replication in a grant. For clinical-trial power see clinical-biostatistics/power-and-sample-size; for the inverse sample-size question see experimental-design/sample-size.

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 species-environment relationships with constrained ordination (CCA, RDA, db-RDA), variance partitioning, indicator species (indicspecies IndVal.g group-equalized), PERMANOVA paired MANDATORILY with PERMDISP (Anderson & Walsh 2013; dispersion confounds centroid tests), Joint Species Distribution Models (HMSC, sjSDM, gjam) with explicit rejection of "residual covariance equals biotic interaction", phylogenetic community ecology (SES_MPD/MNTD), trait-environment via RLQ + fourth-corner with corrected modeltype=6 (Dray 2014), bipartite network metrics (NODF, modularity) with curveball null (Strona 2014), and Mantel-test replacements (dbRDA, GDM) for spatial data. Use when testing how environmental gradients structure communities, identifying habitat indicator taxa, partitioning variance among predictors, deciding whether PERMANOVA significance is location vs dispersion, picking among HMSC/sjSDM/gjam, or replacing Mantel tests for landscape data.

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。

Derive an execution roadmap from a project's vision/spec docs by first principles, then diff that fresh derivation against the existing roadmap to prove the task ORDER is correct. Use this whenever the user wants to review, validate, re-derive, or sanity-check an execution roadmap or delivery plan; asks whether the tasks/epics are "in the right order"; suspects a task is scheduled before its prerequisite (a producer-after-consumer / dependency-inversion error like "OpenAPI after the web client that consumes it", OR a cross-cutting inherited default like observability/auth/tenancy scheduled after the feature work that inherits it — a seam-after-consumer error); wants to find missing tasks, circular dependencies, or over-fragmented epics; or wants to compact a plan to raise velocity. Also trigger on "review the roadmap", "re-derive the plan from the spec", "is this the right build order", "check the dependency graph of our epics", "which task should come first". It reads the vision + spec corpus, decomposes actors → use-cases → modules → epics → typed tasks, identifies cross-cutting inherited-default seams, builds a real dependency graph with hard + soft (seam) edges (deterministic helper), breaks cycles, topologically orders, compacts, and emits a derived roadmap PLUS a delta report against the current one — it never blindly overwrites a hand-crafted roadmap.

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 6-step procedure for improving, renovating, or rebuilding existing pipelines, individual project folders, documentation structures, or software stacks. Addressable as "pipeline optimizer" (for whole topic pipelines, e.g. a software, research, or game-dev pipeline) or "project-folder optimizer" (for individual project folders within a pipeline, e.g. a single software tool or paper project). Triggers on tasks like "improve pipeline X", "optimize the stack", "rebuild Y", "renovation", "pipeline refactoring", "clean up project folder", "improve folder structure", "unify conventions", "documentation consolidation", "integrate into existing system", or any substantial intervention in established structures. Delivers building-stock analysis, purpose clarification, ideal sketch, gap plan, empirical pain-point identification, and retests with fresh subagents. Prevents parallel standards, duplication, and pipeline breaks.

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 competitor comparison or alternative pages for SEO and sales enablement. Also use when the user mentions 'alternative page,' 'vs page,' 'competitor comparison,' 'comparison page,' '[Product] vs [Product],' '[Product] alternative,' 'competitive landing pages,' 'how do we compare to X,' 'battle card,' or 'competitor teardown.' Use this for any content that positions your product against competitors. Covers four formats: singular alternative, plural alternatives, you vs competitor, and competitor vs competitor. For sales-specific competitor docs, see sales-enablement.

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。

既存機能のSpec化。実装済みコードを分析して要件定義書を逆生成する。 spec-map.yml にコードとSpecの対応関係を記録する（コード変更なし）。 「ツイート機能のSpecを作って」「認証周りをドキュメント化して」「既存の○○機能を設計書にして」 「この機能の要件を整理して」「○○の仕様を分析して」などのリクエストで使用する。 既に動いているコードからドキュメントを起こすときに使う。新規機能にはdraft-specを使う。 コード変更後のドキュメント追従にはupdate-docsを使う。

Full SEO audit: Google Search Console data + URL Inspection API + PageSpeed Insights API + technical crawl + keyword research + metadata audit + schema markup audit + search intent analysis + Core Web Vitals monitoring. Feeds real GSC data and PageSpeed metrics into AI to surface quick wins, diagnose traffic drops, find content gaps, identify metadata mismatches, detect schema gaps, monitor page performance, and produce an actionable 30-day plan. Use this skill whenever the user asks about SEO, search rankings, organic traffic, Google Search Console, keyword performance, traffic drops, content gaps, search visibility, technical SEO, meta tags, schema markup, structured data, URL indexing, keyword research, indexing issues, page speed, performance, Core Web Vitals, LCP, INP, CLS, or Lighthouse scores. Also trigger on: "why is my traffic down", "what keywords am I ranking for", "improve my rankings", "check my search console", "SEO audit", "analyze my SEO", "technical SEO", "meta tags", "indexing issues", "crawl errors", "content strategy", "keyword cannibalization", "search intent", "schema markup", "structured data", "URL inspection", "page speed", "performance score", "core web vitals", "lighthouse", or any organic search question. If in doubt, trigger. This skill handles everything from quick GSC checks to deep technical audits with performance monitoring.

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。

Diagnoses bias, anomalies, and strange-looking results on a specific PostHog experiment. Covers empty / 0-exposure experiments, sample ratio mismatch, identity fragmentation, multi-variant exposure, uneven-split exclusion bias, significance traps (peeking, A/A, Bayesian vs Frequentist), PostHog-vs-SQL discrepancies, and surprises after mid-run edits. Symptom-driven dispatch to the right diagnostic. TRIGGER when: user asks 'is my experiment biased?' or 'why 0 exposures?', references the bias banner, says a variant looks strange / wrong / off, sees significance flipping, notices PostHog numbers disagreeing with their SQL, sees an A/A test showing significance, or reports surprises after mid-run edits. DO NOT TRIGGER when: creating a new experiment (use creating-experiments), only configuring rollout (use configuring-experiment-rollout) or metrics (use configuring-experiment-analytics), or only asking lifecycle questions (use managing-experiment-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。

Calculates statistical power for high-dimensional genomics experiments (bulk RNA-seq, scRNA-seq, ATAC-seq, ChIP-seq, methylation, proteomics) under negative-binomial count models using RNASeqPower, PROPER, and simulation via powsimR, distinguishing per-gene from marginal (transcriptome-wide) power, the role of mean expression and dispersion, and the sequencing-depth-versus-replicate tradeoff. Covers simulation as the honest default for overdispersed counts, FDR-aware average power versus single-test power, observed/post-hoc power as an anti-pattern, and the winner's-curse / Type-S / Type-M consequences of underpowering. Use when planning replicate number for a sequencing experiment, deciding whether to add depth or samples, choosing closed-form versus simulation power, estimating power from pilot dispersions, or justifying replication in a grant. For clinical-trial power see clinical-biostatistics/power-and-sample-size; for the inverse sample-size question see experimental-design/sample-size.

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。

Fix the psychologically significant moment, not the logically significant metric — Rory Sutherland on experience. Use when the outcome is fine but the journey feels bad: complaints about waiting, anxiety, uncertainty, or 'it's technically fast/cheap/correct but people still hate it'; when the user asks 'how do we reduce complaints', 'how do we make waiting/onboarding/checkout feel better', 'people are anxious during X', or is about to spend big to shave a number (wait time, load time, steps) when the real pain is how the moment feels. Covers uncertainty reduction, idle vs occupied waiting, and the peak-end rule. Inspired by Rory Sutherland's *Alchemy*. Routed to from psycho-logic. 日本語の相談（「待ち時間のクレームが多い」「手続きの途中で離脱される」「お客様を不安にさせている」）にも使う。中文咨询（“等待时间投诉多”“办理中途流失”“让客户感到不安”）也适用。