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概要と使いどころ
the UGC fix-loop toolkit — surgically re-render a bad window/beat of a single-take UGC master (stitch_replacement.py, pure FFmpeg) and GPT cross-model review a Seedance prompt before render (vet_seedance_prompt.py, routed through the openai-proxy). Fetch it into a one-shot UGC recipe so both scripts resolve on any machine and the vet call bills the Ads agent.
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。
Generate an instrumental music bed via ElevenLabs Music, ROUTED THROUGH THE elevenlabs-proxy so it bills the Ads agent. Trims any sparse intro, loudnorm, fades the tail. Prompt + length from the template recipe. Use for the music layer of any video-ad format.
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Generate or edit an image via any FAL image model (nano-banana edit, gpt-image, flux, ...), ROUTED THROUGH THE fal-proxy so it bills the Ads agent. image_urls must be public URLs; --image puts a local file on the fal CDN first. The recipe names the model + prompt. Use for keyframes, flat-cover transforms, product hero edits. (For the OpenAI gpt-image family specifically, create-image-gpt-image-fal also exists.)
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。
Generate a voiceover (VO) clip via ElevenLabs text-to-speech, ROUTED THROUGH THE elevenlabs-proxy so it bills the Ads agent. Voice id + script text come from the template recipe. Use for the spoken narration of VO-driven video-ad formats (cgi-app-sizzle, flat-vector-explainer, hypermotion). Never call ElevenLabs directly — the proxy attribution is required.
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。
Generate a single photoreal or designed image with OpenAI gpt-image via fal.ai. Supports gpt-image-1 (default, fixed sizes — the FAL fallback for Higgsfield's `gpt_image_2`) and gpt-image-2 (`openai/gpt-image-2`, custom output sizes up to 3840px). Routes to text-to-image or the edit variant depending on whether a reference image is provided. Use for photoreal character anchors, scene keyframes, and designed sheets (e.g. storyboards) where precise layout and legible text matter.
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。
Shared helper that routes ALL paid media generation (FAL image/video, ElevenLabs music) through the GooseWorks proxies so every call bills the Ads agent — never a provider SDK's default host. Host-swaps the FAL queue URLs, loads the agent token from the sandbox env (GW_MEDIA_PROXY_TOKEN) or ~/.gooseworks/credentials.json, and returns the result CDN URL. Every video-ad media capability imports this; templates never call a provider directly.
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。
Image-to-video (or text-to-video) via any FAL video model (Kling, Seedance, Veo), ROUTED THROUGH THE GooseWorks fal-proxy so the call bills the Ads agent. The template recipe names the model + params; image_url inputs must be public URLs (the orchestrator hosts local frames with the MCP media_upload). Returns the result video URL and downloads it. Use for the generative base clip of any video-ad format.
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。
Check that a change to a web app actually works in the running app before calling it done. Drives the real page and returns a pass/fail verdict with the request that fired, the state that moved, and the file:line to fix. Use after editing a component, a form, a route, or an API call; when you have said "fixed" but have not opened the app; when the user asks "does it actually work?"; or when a change looks right on screen and you cannot prove it.
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。
Install, instrument and verify a web app end to end without pausing for a human. Use in an autonomous or goal-mode agent, in CI, or in any client that asks for approval on every command: it never says "restart your client" or "open a browser", because it takes a route that needs neither. Prefer the normal install-and-verify skill when a human is present and can answer.
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。
Prove sign-in lands the user where they should be, sign-out really ends the session so a protected page sends them back to sign in, and an expired session asks to sign in again instead of breaking. Use when auth, a login form, a logout button, route guards or token refresh were added or changed, or when a user reports being logged out, or not logged out, unexpectedly.
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。
Set up signal capture for a Simulink Real-Time application using `slrealtime.Instrument`. Use when choosing which signals a real-time application captures and where the data goes — test-pointing or canvas-badging a signal before build (`TestPoint`, `DataLogging`), constructing an Instrument from an `.mldatx`, calling `addSignal`, `addInstrumentedSignals`, `addFileLogSignals`, `validate`, `connectCallback`, `copy`, or `generateScript`, attaching an instrument to `tg.Instruments` via `addForFileLog`, `addForSDI`, or `addForMATLAB`, setting up live-streaming signals, dynamic file-log workflows, or persisting an instrument as M-code. Selects and routes signals only — not for configuring, building, running, or connecting applications onto targets.
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。
Create and maintain AGENTS.md / CLAUDE.md snippet indexes that route tasks to the correct dotnet-skills skills and agents (including compressed Vercel-style indexes).
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Performs set operations on genomic intervals - intersect (-wa/-wb/-wo/-wao/-loj/-c/-v/-u), subtract (-A), merge (-d, -c/-o), complement, cluster, multiinter, unionbedg, map, and groupby - with bedtools (CLI) and pybedtools/pyranges/bioframe (Python). Covers the sorted-input contract and the -sorted chromosome-order footgun, reciprocal/fractional overlap (-f/-F/-r/-e) and the A-vs-B asymmetry, -split for spliced/BED12/BAM features, and jaccard/fisher as mechanics only. Use when finding overlapping or unique regions between BED/peak/feature files, building consensus peaksets, removing blacklisted regions, transferring annotation values onto intervals, or computing interval-set similarity; route overlap-significance testing to overlap-significance.
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。
Balances Hi-C contact matrices (ICE via cooler.balance_cooler, KR/SCALE/VC context), computes distance-decay expected with cooltools (expected_cis per-diagonal P(s), expected_trans scalar), builds observed/expected (O/E) matrices, and diagnoses polymer state from the P(s) log-derivative. Covers the within-matrix-vs-cross-sample distinction (balancing is NOT a normalizer), the equal-visibility assumption that CNV/aneuploidy violates (use raw counts for copy-number), cis-only balancing, mad_max/blacklist masking before balancing, multiplicative cooler weights vs divisive juicer weights, and the resolution-vs-depth budget. Use when balancing a .cool/.mcool, computing expected or P(s), making O/E matrices for compartments/loops, deciding ICE vs KR vs SCALE, choosing a resolution for a given depth, or troubleshooting NaN/all-NaN balanced matrices; route cross-sample comparison to hic-differential.
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。
Detects TAD boundaries from balanced Hi-C contact matrices via the diamond-window insulation score (cooltools insulation) and HiCExplorer hicFindTADs, returning a continuous log2 insulation track, valley-prominence boundary_strength, and Li/Otsu-thresholded is_boundary flags across a list of window sizes. Covers the multi-scale window sweep (sub-TAD to compartment-domain), why the boundary is reproducible but the domain partition is not, cross-condition comparison via differential SCORE not differential partition, and the insulation-vs-compartment orthogonality. Use when calling TADs or domain boundaries, computing insulation scores, choosing a window size, ranking boundary strength, comparing boundaries across conditions, or annotating CTCF-backed boundaries; route domain rendering to hic-visualization and boundary-feature overlap to genome-intervals.
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 differential m6A methylation between conditions from MeRIP-seq paired IP/input data using exomePeak2 (GC-bias-aware differential via its bam_ip/bam_input control + bam_treated_ip/bam_treated_input treatment arms), QNB beta-binomial, MeTDiff HMM, and RADAR, plus the paired-symmetric edgeR/DESeq2-on-peak-counts route when batch/lot covariates need fixed-effect handling that exomePeak2's API does not accept. Covers paired vs unpaired vs interaction designs, batch confounding and per-lot meta-analysis, the stoichiometry-vs-expression-vs-IP-efficiency confound, and effect-size filtering against under-powered N=2 designs. Use when comparing m6A across two or more conditions, choosing between exomePeak2/QNB/RADAR/MeTDiff for a design, handling batch confounding when exomePeak2's API is too rigid, distinguishing real hyper/hypo-methylation from expression shifts, applying effect-size thresholds, or planning orthogonal stoichiometry validation (GLORI/SAC-seq/m6Anet mod_ratio).
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 camera, photos, audio, haptics, ShazamKit, on-device music analysis, face grouping and video highlights, screen recording, casting to non-AirPlay routes, SharePlay playback, the user's Apple Music library, lock-screen metadata, or CarPlay app design, templates, and navigation. Covers AVCaptureSession, AVFoundation, Core Haptics, MediaPlayer, MusicKit, NowPlaying, ScreenCaptureKit, DockKit.
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。
Workflow skill for KiCAD PCB layout and routing via MCP tools. Triggers on: "layout the board", "route traces", "PCB", "place footprints", "copper pour", "board outline", "differential pair", "board setup", "track width", "via", "zone", "design rules", "stackup", "silkscreen".
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。
Apply modern Swift language patterns and idioms for non-concurrency, non-SwiftUI code. Covers if/switch expressions (Swift 5.9+), typed throws (Swift 6+), result builders, property wrappers, opaque and existential types (some vs any), guard patterns, Never type, Regex builders (Swift 5.7+), basic Codable shaping (CodingKeys, custom decoding, nested containers), modern collection APIs (count(where:), contains(where:), replacing()), basic FormatStyle usage, and string interpolation patterns. Use when writing core Swift code involving generics, protocols, enums, closures, or modern language features; route deep Codable to swift-codable, detailed formatting/localization to swift-formatstyle, and API naming to swift-api-design-guidelines.
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。
Maintain and extend existing SceneKit 3D scenes and visualizations. Use when working with SCNView, SCNScene, SCNNode scene graphs, SceneKit geometry/materials/lights/cameras, SCNAction animation, SCNPhysicsBody physics, SCNParticleSystem effects, .scn/.dae/.abc SceneKit assets, shader modifiers, or SwiftUI SceneView. SceneKit is soft-deprecated and in maintenance mode; route new apps, significant updates, USD/USDZ pipelines, and migration planning toward RealityKit.
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。
Access research-grade sensor data using SensorKit for approved studies. Use when an app needs SensorKit entitlement setup, Research Sensor & Usage Data authorization, ambient light, recorded motion, device usage, keyboard metrics, visits, speech, face, wrist temperature, ECG, PPG, acoustic settings, or sleep-session data. Route ordinary motion to CoreMotion and health records/workouts to HealthKit.
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, review, or improve maps and location features in iOS/macOS apps using MapKit and CoreLocation. Use when working with Map views, annotations, markers, polylines, user location tracking, geocoding, reverse geocoding, search/autocomplete, directions and routes, geofencing, region monitoring, CLLocationUpdate async streams, or location authorization flows. Also use when working with maps, coordinates, addresses, places, directions, distance calculations, or location-based features in Swift apps.
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。
Guide for implementing smooth, native-feeling animations using React's View Transition API (`<ViewTransition>` component, `addTransitionType`, and CSS view transition pseudo-elements). Use this skill whenever the user wants to add page transitions, animate route changes, create shared element animations, animate enter/exit of components, animate list reorder, implement directional (forward/back) navigation animations, or integrate view transitions in Next.js. Also use when the user mentions view transitions, `startViewTransition`, `ViewTransition`, transition types, or asks about animating between UI states in React without third-party animation libraries.
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Use this skill when the user asks about Stripe Connect configuration, charge patterns, Dashboard access, or how to get started with Connect, is building a marketplace, platform, multi-vendor store, gig platform, or subscription platform, needs to pay out sellers, vendors, or providers, mentions split payments, revenue sharing, multi-party payments, or similar payment distribution concepts, provides a company URL or business description for a recommendation, builds SaaS that routes money between parties (for example, POS, booking, invoicing — not operational SaaS without payment routing), asks about onboarding or KYC for merchants, sellers, and vendors, mentions connected account Dashboard or responsibility configurations, or asks about payment flows, white-label payments, or embedded payments.
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。