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Build sequence logos from aligned DNA, RNA, or protein motifs using ggseqlogo (R), Logomaker (Python), or WebLogo with explicit bits vs probability encoding, background-frequency correction, custom alphabets, and multi-logo stacking. Use when visualizing motif PWMs (TF binding, splice sites, CRISPR spacers), aligned-position composition, or comparing two motif sets.

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Discovers de novo motifs and tests known motif enrichment in ChIP-seq, ATAC-seq, or other peak sequences using HOMER, MEME-ChIP (STREME, CentriMo, TOMTOM, FIMO), monaLisa, and AME. Handles background selection (GC-matched, dinucleotide-shuffled, Markov order-2, peak-flanks), motif databases (JASPAR 2024 CORE PWMs, JASPAR 2026 deep-learning collection, HOCOMOCO v12, HOMER built-in), centrally-enriched motif testing, and differential motif analysis. Use when identifying TF binding motifs in peaks, testing for known TF enrichment, scanning for motif instances, comparing motif content between conditions, or interpreting motifs from deep learning models.

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Analyze TF motif accessibility variability across samples or single cells using chromVAR. Use when identifying TF motifs whose accessibility correlates with conditions, computing per-sample motif z-scores after matched background correction, comparing to ArchR / Signac equivalents, or distinguishing motif-accessibility signal from per-site footprinting.

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 the user asks about FCRA adverse action procedures — what to do when a background check (MVR, criminal, drug test) returns information that may lead to denying employment or terminating a CDL driver. Covers the 5-business-day pre-adverse-action notice, FCRA Summary of Rights, final adverse action notice, state-specific add-ons (CA, NY, etc.), and how to handle disputes. Cite 15 USC § 1681 (FCRA) and 49 CFR 391.

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。

Analyze a Coval audio-quality testing report from runs across different voice, speaking-style, volume, interruption, and background-noise scenarios. Use when a user provides a Coval report URL, report export, run IDs, screenshots, or metric summary and wants evidence-backed next steps such as prompt changes, tool handling fixes, STT/TTS adjustments, trace setup, or expanded audio-scenario coverage.

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。

Elite frontend image-direction skill for generating premium, conversion-aware website design references. CRITICAL OUTPUT RULE — generate ONE separate horizontal image FOR EVERY section. A landing page with 8 sections produces 8 images. Never compress multiple sections into one image. Enforces composition variety (not always left-text / right-image), background-image freedom, varied CTAs, varied hero scales (giant / mid / mini minimalist), narrative concept spine, second-read moments, and a single consistent palette across all images. Optimized for landing pages, marketing sites, and product comps that developers or coding models can accurately recreate.

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When the user requests to create or customize an academic personal website from a GitHub template repository. This skill handles the complete workflow of forking academic template repositories (like academicpages.github.io), extracting structured personal information from memory or provided data, and systematically updating configuration files (_config.yml), navigation menus (_data/navigation.yml), content pages (_pages/about.md), and publication listings (_publications/). It specifically handles academic profiles including personal details, education background, research experience, publications, skills, and contact information. Triggers include requests to 'fork and customize academic homepage', 'build personal academic website', 'create research portfolio', or 'set up GitHub pages with academic template'.

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Swift 6.2 Approachable Concurrency — single-threaded by default, @concurrent for explicit background offloading, isolated conformances for main actor types.

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。

BullMQ expert for Redis-backed job queues, background processing, and reliable async execution in Node.js/TypeScript 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。

Use this skill when building analytics dashboards with nuxt-ui-tools as a package consumer. Covers schema and view functions (defineDashboardSchema, defineDashboardView) that take their context as typed params, useDashboard with a getter that rebuilds on input change, typed injection (useDashboardView, injectDashboard, InferDashboard, InferDashboardView), filters declared inline with the f builder and synced with the URL, memory, or an external store (one value per key across views), headless filters, filter controls and the shipped UI (UiDashboardPage, UiDashboardFilters, UiDashboardFilter, UiDashboardViewTabs) with slot overrides, remote paginated pickers and remoteTableOptions, staged queries (essential / background / deferred) with select and dependent requires, lazy enabled conditions on views, queries, and filters (blocks of disabled queries hidden, grids closing up), derived values, views (tabs), query-scoped filters, number formats (presets, Intl options, useDashboardFormat), and the dashboard blocks (stats with trends, goals, and comparisons, stat groups, gauges, unovis charts with highlights, value labels, and totals, lists with progress rings, bars, funnel, alerts, activity feeds, sortable tables, custom widgets) with their automatic loading, error, empty, and refresh states, card menus, header and footer actions, row actions, drill-down and selected state, card tabs, split cards, comparison periods, auto-refresh, and data freshness.

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Drafts formal explanation letters for Canadian Study Permit applications by structuring the argument around program attractiveness, background relevance, choice rationale, and family benefits.

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Gate scheduled work on Claude usage limits — /mxm-tasks schedule, run-cycle, scheduled task fire time, background batch dispatch. Checks 5-hour and 7-day usage before firing and sleeps until reset when over threshold.

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Improve how interfaces use photos, screenshots, icons, illustrations, and user-uploaded media so visuals support clarity instead of undermining it. Use when the user mentions images, screenshots, background photos, hero images, icon sizing, user-uploaded media, crops, overlays, or image readability.

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Create any visual design using Adobe Express templates — including flyers, posters, banners, social media posts (Instagram stories, Facebook posts, LinkedIn graphics), business cards, invitations, greeting cards, resumes, cover letters, brochures, newsletters, certificates, presentations, YouTube thumbnails, email headers, logos, menus, labels, and more. Use this skill whenever the user wants to make, design, create, or build any visual — even if they just say "make me a flyer", "design a poster", "I need something for Instagram", "create an event invite", "make a business card", or any similar request. Also handles requests to find or browse templates, edit text/copy, change background colors, or animate a design. Access: 🔐 Signed-In required | Gen AI: ❌

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Creates modern CSS gradients using Tailwind CSS including linear, radial, conic, mesh gradients, animated gradients, glassmorphism, and gradient text effects. Use when users request "gradient background", "tailwind gradient", "modern gradient", "mesh gradient", or "animated gradient".

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。

Elite frontend image-direction skill for generating premium, conversion-aware website design references. CRITICAL OUTPUT RULE — generate ONE separate horizontal image FOR EVERY section. A landing page with 8 sections produces 8 images. Never compress multiple sections into one image. Enforces composition variety (not always left-text / right-image), background-image freedom, varied CTAs, varied hero scales (giant / mid / mini minimalist), narrative concept spine, second-read moments, and a single consistent palette across all images. Optimized for landing pages, marketing sites, and product comps that developers or coding models can accurately recreate.

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。

Launch background Claude sessions to explore and analyze business ideas. Say 'Idea: [description]' to trigger.

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。

Run Codex CLI, Claude Code, OpenCode, or Pi Coding Agent via background process for programmatic control.

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。

General-purpose orchestration for Codex. Uses update_plan plus background PTY terminals to run parallel codex exec workers.

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。

Requires OFOX_API_KEY — create one at https://app.ofox.ai. Shared execution layer for the Ofox image API (api.ofox.ai) — validates parameters client-side, sends one synchronous request, base64-decodes the result, saves it to a file, and reports the real usage token counts and the computed dollar cost. Does both text-to-image (generate) and editing an existing image you supply as a local file (edit — change the background, recolour an element, alter a product photo, while leaving the rest of the picture intact). This is a library skill, not a standalone user-facing one — it is meant to be invoked by scenario skills that build model/prompt/size choices for a specific use case and then call into this skill's script rather than re-implementing the API calls — image-edit owns "change this image so that...", product-image owns a set of product images to choose between, and seedance-anime-drama owns character images for a video pipeline. Load this skill directly only when a user explicitly names the Ofox image API, asks to call it with specific low-level parameters, asks to debug a failed Ofox image request, or wants a plain "generate an image of..." from text — which is the one common case no scenario skill covers.

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Architects the encryption, codec/transport, and premium-feature layer of a group video-calling product, on top of an already-chosen SFU topology. Covers E2EE patterns (Zoom leader-fan-out, Signal pairwise-fan-out, MLS/TreeKEM as in Discord's DAVE, Telegram's ledger consensus), the SFrame (RFC 9605) + WebRTC Insertable Streams mechanism letting an SFU relay encrypted frames it can't read, codec/transport choice (AV1/VP9 SVC vs. simulcast, Opus, congestion control, Media-over-QUIC, WHIP/WHEP), and which "premium" features (virtual backgrounds, live captions, recording, breakout rooms, spatial audio) survive E2EE vs. structurally can't. Use when adding E2EE to an SFU-based call, choosing a 2026 codec/SVC strategy, or deciding which features to disable under E2EE mode. NOT for call topology/platform choice (see webrtc-adhoc-video-chat, which this composes with). NOT for one-way broadcast (see managed-video-streaming-pipeline). NOT for the DM/group-chat text backend (see realtime-messaging-backend-architecture).

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Research AI coding assistant products, audiences, user stories, social proof, hacks, and unmet needs for apps like Cursor, Claude Code, Codex, Warp Code, Devin, Windsurf, GitHub Copilot, Cline, Aider, and homegrown agent stacks. Use when designing or positioning agentic developer tools, Port Daddy Agent Harbor, swarm consoles, background coding agents, or competitive/product research for AI software engineering. NOT for implementing the coding agent runtime, generic market research, or UX mockups without developer workflow evidence.

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Run initial NanoClaw setup. Use when user wants to install dependencies, authenticate messaging channels, register their main channel, or start the background services. Triggers on "setup", "install", "configure nanoclaw", or first-time setup 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。