「rl」の検索結果

Assemble a cosmic-mythology-voiceover reel from a config — one spoken voiceover carries the whole narrative while N curated stills in one chosen look are weighted beat-synced across the delivered VO duration (cut_dur = VO_dur times weight over the weight sum, so emotional beats hold longer), Ken-Burns-zoomed per still (scale 2x, center crop, zoompan, fade-in first and fade-out last), ffmpeg-concatenated, the VO composited under the picture (libx264 crf18 plus aac), the ONE on-screen hook line faded on over the open with a drawtext alpha window, and Whisper/VEED captions burned along the bottom — never in-world text on a still. This is the FREE deterministic assembly stage (weighted sequence plus Ken-Burns plus concat plus VO composite plus hook overlay plus caption burn); the VO and the stills come from create-vo-elevenlabs and create-image-fal. Use for the cosmic-mythology-voiceover 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。

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。

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。

Handles BED-format genomic intervals (BED3 through BED12, narrowPeak/broadPeak) and the coordinate-system substrate the whole interval category rests on, with bedtools (CLI) and pybedtools/pyranges/pandas (Python). Covers the 0-based half-open vs 1-based-closed convention boundary and the start-1/end-unchanged conversion, the silent failures (chrom-name mismatch, CRLF, lexicographic-vs-version sort under -sorted), genome/chrom.sizes generation, sorting contracts, BED12 block invariants, validation, makewindows, cross-assembly liftover (liftOver/CrossMap), and BED<->VCF/BAM/FASTA conversion. Use when reading, creating, validating, sorting, lifting between genome builds, or converting interval files, preparing inputs for bedtools/tabix/bigBed, or debugging an off-by-one or empty-overlap result.

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。

Corrects fluorophore spillover (conventional compensation) or spectral overlap (spectral unmixing) and applies variance-stabilizing transforms (logicle/biexponential, arcsinh, log) for flow and mass cytometry. Covers spillover-matrix estimation from single-stain controls, AutoSpill, the spillover spreading matrix and why panel design (not compensation) bounds resolution, compensate-then-transform ordering, and arcsinh cofactor choice (5 for CyTOF, ~150 for fluorescence, per-channel via flowVS). Use when correcting spectral overlap, preparing data for gating/clustering, choosing logicle vs arcsinh, deciding a cofactor, or distinguishing compensation from spectral unmixing.

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。

Performs differential expression on bulk RNA-seq count data with DESeq2's negative-binomial GLM, Wald and LRT testing, apeglm/ashr/normal LFC shrinkage, independent filtering, Cook's outlier handling, VST/rlog transforms, and design formulas including paired, batch, and interaction terms. Use when running bulk DE, choosing DESeq2 over edgeR or limma-voom, building a paired or interaction design, applying LFC shrinkage for ranking or GSEA, choosing Wald vs LRT, troubleshooting padj=NA, picking VST vs rlog, importing salmon/kallisto via tximport, or analyzing prokaryotic RNA-seq.

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。

Creates DE-specific diagnostic and result visualizations using DESeq2/edgeR built-in functions and lightweight ggplot2 wrappers. Covers MA plot (with the shrunken-LFC compression effect), volcano (with the apeglm caveat that p-values are unchanged), PCA on VST/rlog (never raw counts), sample distance heatmaps, top-DE-gene heatmaps with the row-scaling trap, dispersion / BCV plot interpretation, p-value histogram diagnostics, plotCounts for individual genes, blind=TRUE vs FALSE rationale, and the n=3 visualization stake. Use when generating DE diagnostic plots, choosing VST vs rlog for visualization, troubleshooting suspicious plot patterns (shifted MA cloud, batch-dominated PCA, anti-conservative p-value histogram), or building a standard QC figure panel.

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。

Estimates bivariate genetic correlation (rg) between traits from GWAS summary statistics or individual-level genotypes using cross-trait LDSC, HDL, LAVA, rho-HESS, GREML-bivariate, Popcorn, and HDL-L. Use when quantifying shared genetic architecture between two traits, screening MR validity before causal inference, distinguishing global from locus-level rg, estimating trans-ancestry rg, separating partial from full causation via LCV gcp, or producing a STROBE-MR-compliant cross-trait sensitivity battery. Cross-trait LDSC intercept absorbs sample overlap and is NOT a bias; HDL is biased under sample overlap above ~5%. High rg between exposure and outcome motivates CHP-aware MR sensitivity (CAUSE, LHC-MR).

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Use when accepting ANY real-world payment — Apple Pay, Wallet passes, Tap to Pay, Orders in Wallet. NOT in-app purchase / digital content (use axiom-integration). Covers entitlements, certs, signing, App Review payment 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 implementing or debugging ANY network connection, API call, or socket in an Apple app. Covers URLSession, Network.framework, NetworkConnection, connection diagnostics.

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Build SwiftUI layouts using stacks, grids, lists, scroll views, forms, and controls. Covers VStack/HStack/ZStack, LazyVGrid/LazyHGrid, List with sections and swipe actions, ScrollView with ScrollPosition and scroll-driven reveal surfaces, Form with validation, Toggle/Picker/Slider, .searchable, and overlay patterns. Use when building data-driven layouts, collection views, paged detail reveals, settings screens, search interfaces, or transient overlay UI.

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Build iOS App Clips with invocation URLs, App Clip Codes, NFC, QR codes, Safari banners, Maps, Messages, target setup, App Store Connect experiences, size/capability constraints, NSUserActivity routing, SKOverlay promotion, App Group/keychain handoff, ephemeral notifications, location confirmation, and full-app migration. Use when creating App Clips or wiring App Clip invocation, experience configuration, or full-app handoff.

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 doing ANY task involving Supabase. Triggers: Supabase products (Database, Auth, Edge Functions, Realtime, Storage, Vectors, Cron, Queues); client libraries and SSR integrations (supabase-js, @supabase/ssr) in Next.js, React, SvelteKit, Astro, Remix; auth issues (login, logout, sessions, JWT, cookies, getSession, getUser, getClaims, RLS); Supabase CLI or MCP server; schema changes, migrations, declarative schemas, security audits, Postgres extensions (pg_graphql, pg_cron, pg_vector); debugging and troubleshooting errors or unexpected behavior on Supabase projects (HTTP errors, Postgres errors, RLS surprises, permission denied, schema cache issues, timeouts, Edge Function crashes, Realtime drops, Storage failures) and reading or querying logs (Logs Explorer, ClickHouse).

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。

Share MATLAB content by guiding users through uploading to GitHub, MATLAB Drive, or File Exchange, then generating "Open in MATLAB Online" URLs. Covers the full sharing workflow: choosing a platform, uploading content (automated via gh CLI for GitHub, manual for MATLAB Drive and File Exchange), and constructing the correct URL. Use when a user wants to share MATLAB code with others, open local files in MATLAB Online, generate an open-in-MATLAB-Online button or badge, or when an AI agent has generated MATLAB code locally and the user wants to share it or run it in MATLAB Online.

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。

Foundation skill for all RoadRunner workflows: MATLAB path setup, connection, project/scene/scenario lifecycle, world settings, handle management, status, and close. Use when connecting to RoadRunner, managing projects/scenes/scenarios, setting world origin, checking status, closing RoadRunner, or when any downstream RoadRunner skill needs initialization.

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。

Deploy serverless functions on Google Cloud Functions. Configure triggers and manage deployments. Use when implementing serverless workloads on GCP.

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。

Build serverless applications on Azure Functions. Configure triggers, bindings, and deployment. Use when implementing serverless workloads on Azure.

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。

Build and deploy serverless functions on AWS Lambda. Configure triggers, manage permissions, and optimize performance. Use when implementing serverless 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 ctx as working memory for prior agent work. Before starting or continuing work in an unfamiliar area, resuming earlier work, or revisiting an investigation, search prior sessions to ground yourself in earlier context. Use ctx blame to trace a line, file, commit, or PR to the agent session that produced it. Use when prior decisions, constraints, attempts, tool calls, transcript evidence, or code provenance may matter. Use ctx graph queries on indexed projects to follow calls and dependencies and understand what a change might affect.

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 plan cold start, get first users, or launch a new product with zero traction. Also use when the user mentions "cold start," "cold start problem," "first users," "seed users," "finding users," "finding early users," "Fiverr Upwork," "comment outreach," "Twitter search users," "product launch strategy," "0 to 1 growth," "early-stage acquisition," "launch channels," "get first customers," "Product Hunt launch," "AppSumo," "LTD," "indie hacker," "bootstrapping," or "solo founder." For directory listing copy and submissions, use directory-submission. For Product Hunt day-of execution, use product-hunt-launch. For GTM motion design, use gtm-strategy.

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。

Route any website you need to visit through markdown.new by prefixing the URL. **WHEN TO USE:** - You would normally open a website link to read content (docs, blog posts, changelogs, GitHub issues, etc.) - You need a cleaner, Markdown-friendly view for copying notes or summarizing

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。

Given a Japanese NLP GitHub repo/model/dataset (URL / owner/repo / tool name) OR a topic, find what's already in awesome-japanese-nlp-resources and discover related resources NOT yet listed (contribution candidates). Mines the bundled dataset, then expands via web research across GitHub and Hugging Face. Use when the user names a SPECIFIC repository, model, or tool and wants alternatives/equivalents, OR wants to discover Japanese NLP resources for a topic that are NOT yet in the list, OR wants to prepare a contribution. Trigger phrases include 'mecabに似たツール', 'fugashiの代替', 'alternatives to fugashi', 'repos like manga-ocr', 'what else is like sudachi', 'リストに無い新しい日本語NLP', 'awesome-japanese-nlpに追加できそうな', '最近公開された日本語NLPツール', 'find unlisted Japanese NLP repos', 'new Japanese models on Hugging Face', 'contribute a new resource'. For a simple lookup of what already exists, use the search skill instead.

Deploy the dispatcher PCF for a third-party `.ppmplugin` control to a Power Platform environment via `pac pcf push`. The dispatcher PCF is the Studio-side control that dispatches the composite key `<name>/<receiver>` over the wrap shell's `SendMessagePlugin` bridge to the control's native module. Verifies deploy prereqs (Node.js 20+ with npm, .NET SDK, and active `pac auth`), then three confirmation gates — publisher prefix (2–8 chars; defaults to `pamext` or the last-used value from `.extension-state.md`), version bump (patch / minor / major / no-bump), target environment URL (from `pac org who`). Builds the PCF if needed, then pushes. Decoupled from /generate-pcf-companion so the engineer can scaffold and customize locally, then deploy when ready. Updates `.extension-state.md` with deployment history (timestamp, env URL, version, prefix used).

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 generated clips must become a finished video on Scenario via MCP: cutting a shot list together, laying a timeline, concatenating with transitions, overlaying a logo or title card, adding a music bed or voiceover, burning in or exporting captions and subtitles, trimming and splitting, or producing vertical and square variants of one master. Keywords: edit, assemble, stitch, concat, compositor, timeline, layers, overlay, captions, SRT, ad, UGC, social cut.

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。