Run a supplied task in headless AGY (Antigravity, Gemini) and collect its result. Use when: AGY, Antigravity or Gemini is requested by name; never a fallback.
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。
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概要と使いどころ
Run a supplied task in headless AGY (Antigravity, Gemini) and collect its result. Use when: AGY, Antigravity or Gemini is requested by name; never a fallback.
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。
Registry fallback entry point for the VidSeeds.ai MCP connector. Use the bundled domain skills for setup, efficiency, thumbnails, projects, analytics, local video, and publishing workflows.
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。
Scrape blog posts via RSS feeds (free, no API key) with Apify fallback for JS-heavy sites. Use when you need to monitor competitor blogs, track industry content, or aggregate blog posts by keyword.
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。
Multi-provider waterfall lead enrichment. Takes an email (+ optional name) and returns person + company data by cross-referencing cheap APIs first, using expensive AI agents only as fallback. Cost-efficient (~$0.04-$0.10/lead) with confidence scoring and full error visibility.
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。
Extract speaker names, titles, companies, and bios from conference websites. Supports direct HTML scraping and Apify web scraper fallback for JS-heavy sites. Use for pre-event research and outreach targeting.
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。
Assemble an animated character-explainer video ad (any art style — Pixar-style 3D, claymation, anime, paper-cut, felt) (~77s, 9:16) built on an "N types of X" listicle spine — a recurring human protagonist plus a locked cast of N persona characters, one per list item. Given the per-scene i2v clips + a per-scene target-duration table + a narration track, it trims each clip to its scene window, re-encodes every segment to identical 1080x1920/30fps/libx264/yuv420p (decrease+pad, never crop) so the concat demuxer never drops frames, concats, and muxes audio — in RESTYLE mode the source ad's VO+music mix is reused verbatim, in ORIGINAL mode fresh per-scene VO (loudnorm I=-14) is mixed under an optional music bed (loudnorm I=-26). A static-still fallback loops a scene's keyframe when its clip is missing/failed, so the master always assembles; libass captions are burned last. FREE deterministic assembly (Python + ffmpeg, no bash, no paid calls); the recipe supplies the clips, keyframes, VO or source audio, and caption table and gates the paid cast-anchor/keyframe/Kling-i2v/VO/music calls to their own capabilities. Use for the 3d-character-explainer listicle 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。
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。
Assemble a 3D-CGI app sizzle — nano-banana CGI plates (blank-glow floating phone + a CGI studio with rim-light + placeholder burst shapes; studio look and phone finish come from the recipe choices) plus PIL compositing of the REAL App Store screenshots onto the bezel + burst-out overlays, driven by Kling 3.0 i2v steady-float per beat with a per-beat Ken-Burns FFmpeg push-in fallback when Kling garbles the UI, then VO/music mix (sidechain duck, loudnorm) + 1.15x speed + anti-AI grain finalize. The on-screen UI, any faces in it, and the wordmark are ALWAYS real assets composited via PIL — never AI-rendered. The paid steps (plates, i2v clips, VO, music) are separate capabilities; this ships the config + PIPELINE + FREE assembly and the recipe orchestrates the spend. Use for the cgi-app-sizzle video 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。
Deploy an API gateway for LLM traffic with load balancing, rate limiting, key management, semantic caching, fallback routing, and cost tracking. Covers LiteLLM Proxy, OpenRouter-compatible setup, and custom Nginx/Traefik patterns.
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 building, debugging, or evaluating CloudBase PostgreSQL / CloudBase PG / PG mode apps, including Postgres schema setup, queryPgDatabase/managePgDatabase, JS SDK v3 app.rdb() CRUD/RPC, PG HTTP API fallback, RLS-style permissions, username-password auth, and Web CMS/admin CRUD flows backed by CloudBase PG.
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。
CloudBase CLI (tcb, 云开发CLI, Tencent CloudBase命令行) resource management skill. Use when deploying cloud functions, CloudRun, storage, NoSQL/MySQL, static hosting, permissions, CORS/domains via tcb; for CI/CD and batch ops; when the user prefers CLI; or as the first-session fallback when CloudBase MCP tools are not loaded yet (after install/config, before IDE restart). Covers tcb login (device code for Tencent Cloud accounts; --cloudbase-api-key -e for environment API Key without an account; --apiKeyId/--apiKey for CI) and domain commands (fn/hosting/cloudrun/…) as MCP auth/manage parity — do not default to tcb deploy.
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 risk-screen a compact role-based method shortlist for a mathematical-modeling subquestion. Use after problem framing and data profiling, before model code generation, to propose a main candidate, a usable baseline, and at most one conditional fallback without padding the pool.
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。
Summarize modeling experiment evidence, compare the approved main method with a usable baseline, surface fallback triggers, and produce a decision-point or final report without creating routine per-round prose.
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。
A fast Rust-based headless browser automation CLI with Node.js fallback that enables AI agents to navigate, click, type, and snapshot pages via structured commands.
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。
Ensures the tenant has a usable Power Platform Pipelines host environment before any pipeline operation runs. Detects host state via the same resolution order as the Power Apps UI (org-db setting → BAP env metadata → default-custom-host setting); if any existing host (Platform or Custom) is found, uses it. If no host is bound to the source env, provisions a new **Platform Host** (recommended, idempotent) or a **Custom Host** via the BAP env-create API with the `D365_ProjectHost` template, or guides the user through PPAC install / `New custom host` (manual fallbacks). Polls lifecycle operations, verifies the host responds to Pipelines API calls, writes a host-check artifact other ALM skills consume. Use when asked to: "set up pipelines host", "ensure pipelines host", "no pipelines host", "install pipelines", "create pipelines host", "provision platform host", "provision custom host". Also invoked transparently by /power-pages:setup-pipeline when its host discovery step finds nothing.
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。
Adds any Power Platform connector to a Power Apps code app. Generic fallback for connectors not covered by a specific skill.
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 making or fixing particle effects and game feel in Godot 4.7: GPUParticles3D or GPUParticles2D explosion, fireball projectile with trail, impact, sparks, smoke, shockwave, ribbon trails, sub-emitters, particle collision, color curve does nothing, particles pop out or vanish, effect too heavy on mobile, CPUParticles fallback for Compatibility or web, overdraw, hit-stop, freeze frame, screen shake, juice.
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 a Unity 6.3 game must run in a browser: 'export to WebGL', Web build settings or Build Profiles, gzip or Brotli, Decompression Fallback, server headers, 'Unable to parse .framework.js.br', build too big or slow to load, itch.io, CrazyGames or Poki limits, Addressables or AssetBundles on the Web, 'Could not produce class with ID', Task.Run freezing the browser, WebGL 2 vs WebGPU, .jslib and SendMessage interop, a page text field that gets no keystrokes, mobile browsers crashing, HTTPS for sensors, hosting and rollout.
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。
Audit code for correctness and rigor — logic errors, silent error swallowing, wishful thinking, and unjustified fallbacks. This is not a style review; it's a logic review. Use when you want a focused correctness audit separate from the full code-police pass.
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。
Prepare a customer demo or executive walkthrough around an evidenced outcome. Use before show-and-tell to rehearse the journey and prepare a fallback.
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。
Diagnose NCCL failures and adjacent training-pod failures on HyperPod GPU clusters (EKS or Slurm) — training hangs, AllReduce / collective-op timeouts, EFA or libfabric errors, rendezvous failures, EFA TCP fallback, /dev/shm or memlock issues, NCCL version mismatch across pods, container OOM / exit-137 / OOMKilled, GPU OOM (CUDA out of memory), CrashLoopBackOff / Pending pods, MASTER_ADDR DNS, NetworkPolicy blocking. Not for single-node hardware faults (→ hyperpod-node-debugger § G) or cluster-creation EFA / SSM failures (→ hyperpod-cluster-debugger § A / § F).
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。
Deep clause-by-clause NDA review from Recipient or Discloser perspective. Produces issue log with redlines, fallbacks, rationales, owners, deadlines. Use when reviewing NDAs for negotiation or approval.
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 Terraform provider configuration and authentication with the Plugin Framework: provider schema for credentials (Optional + Sensitive attributes), environment variable fallbacks, credential provider chains (static config, then environment variables, shared credentials file, and platform identity), unknown-value guards in Configure(), secret redaction, configure-time credential validation, and diagnostics that name every source tried. Use when implementing or reviewing a provider's Configure method or provider schema, adding authentication options (API keys, tokens, profiles, credentials files, assume-role), deciding how a provider should resolve credentials, debugging "no valid credential sources" or missing-credentials errors, or unit testing credential resolution.
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。
Pick the right LLM for LEGAL RESEARCH & ANALYSIS — issue-spotting, rule application, case/statute analysis, memos, and multi-step agentic research. Vendor-neutral routing grounded in mid-2026 benchmarks (Vals AI LegalBench across 124 models; Harvey Legal Agent Benchmark for agentic work). Asks up to 4 quick questions (cost, speed, accuracy/stakes, privacy/jurisdiction/language), then recommends a primary model + fallback + what to avoid + what a human must verify. Use when someone asks "which model for legal research / case analysis / a memo", "best AI for legal reasoning", "route this research task", or is starting legal analysis without a fixed model.
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。