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Fix slow Flutter app startup caused by blocking network operations during initialization. Use when: (1) App takes several seconds to show first frame, (2) Startup logs show sequential network operations (WebSocket connections, API calls), (3) Services initialize during startup that aren't needed until user authenticates. Covers: converting sequential network ops to parallel with Future.wait(), deferring service initialization until actually needed (lazy init), and identifying blocking operations in Riverpod/provider initialization chains.

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。

Search and inspect the installed Blueish Blender Asset Library without mutating it. Use when a user asks for a local Blender asset, node preset, Blueish asset, Asset Browser entry, or named source, or when the Router has selected a node-centric/reusable Geometry Nodes, material, simulation, rigging, compositor, or NPR route with eligible local catalogs; return compatible, attributable candidates for the Router-approved workflow.

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 the weak-agent adversarial test harness against docx-cli. Spawns weak exercise agents (Haiku by default, Sonnet to probe, or a local agent harness's pre-produced runs) to perform real document tasks over six scenarios — five editing (MNDA form-fill + font fidelity, invoice table-edit/restructure + logo replace, résumé styling, contract redlining + commenting, contract finalize via accept/reject + comment reply/resolve) and one authoring (T. S. Eliot poetry journal: multi-column, verse, footnotes, links, figure) — renders every result with Word, has opus judge them against ground-truth rubrics, measures each exercise's tool economy, token cost, wall-clock, and correctness (from transcripts for Claude, the exercise.json ledger for the local harness), and synthesizes a prioritized ergonomics report. Use when the user says 'adversarial review', 'test docx-cli with weak agents', 'run the haiku harness', 'weak agent test', or wants to re-run yesterday's adversarial process.

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 in a repository that uses bd or Beads for durable project task tracking, issue dependencies, blocker management, multi-session handoff, or shared work memory. Trigger when the user asks to find ready work, claim or close tasks, create follow-up work, inspect blockers, recover project context, or choose between local planning and persistent project tracking.

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 in a repository that uses bd or Beads for durable project task tracking, issue dependencies, blocker management, multi-session handoff, or shared work memory. Trigger when the user asks to find ready work, claim or close tasks, create follow-up work, inspect blockers, recover project context, or choose between local planning and persistent project tracking.

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 user asks to translate videos, dub video content, or localize videos into other languages. Translate videos with AI-powered dubbing using iFlytek (Xfei) Video Translation API. Supports video language translation, voice dubbing, multilingual video localization, 视频翻译, 视频配音, 视频本地化. Features task creation, task list, task details retrieval. Ideal for content creators and localization teams.

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。

Provider-independent localization and dubbing production direction for AI agents producing translated videos, dubbed ads, social clips, explainers, avatar videos, documentaries, training media, and multi-market campaigns. Use when planning or reviewing subtitle-versus-dub strategy, translation adaptation, glossary/style-guide setup, casting or voice matching, lip-sync or phrase-sync direction, synthetic dubbing boundaries, captions/subtitles handoff, accessibility, platform delivery, client review, or localization QA.

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。

Plan, implement, or review vs code extension localization work in an existing codebase with compatibility, security, and verification controls. Use when the user explicitly requests vs code extension localization work.

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。

Maps GWAS-implicated loci to candidate effector (causal) genes by integrating variant-to-gene (V2G) features via Open Targets L2G (Mountjoy 2021), MAGMA gene-based association (de Leeuw 2015), FUMA SNP2GENE, cS2G combined SNP-to-gene scores (Gazal 2022), Polygenic Priority Scores (PoPS, Weeks 2023), FLAMES, INQUISIT, DEPICT, and enhancer-gene predictors (ABC, ENCODE-rE2G). Use when narrowing a GWAS lead locus to a candidate causal gene, picking between proximity, eQTL-based, and similarity-based prioritizers, integrating multi-evidence streams (fine-mapping, colocalization, ABC enhancer-gene, distance, chromatin), reconciling discordant L2G vs PoPS calls, prioritizing tissue-specific eQTL evidence, or triangulating across at least three independent lines of evidence for a publication-grade effector-gene nomination.

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。

Resolves GWAS associations to candidate causal variants and credible sets via SuSiE, susie_rss, FINEMAP, CAVIAR, DAP-G, PAINTOR, PolyFun, SuSiEx, MultiSuSiE, and FOCUS. Use when narrowing a GWAS lead SNP to a 95 percent credible set, choosing between in-sample and reference LD, calibrating non-sparse loci with SuSiE-inf or FINEMAP-inf, integrating functional priors via PolyFun, fine-mapping across ancestries with SuSiEx, diagnosing LD mismatch via estimate_s_rss and kriging_rss, handling HLA or long-range LD, or feeding credible sets into coloc.susie for colocalization.

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。

Agent Media OS, the single skill for every media need in a HyperFrames project. Resolve BGM, SFX, image, icon, brand logo, voice, color grade, or LUT into a frozen local file or paste-ready block + ledger record (one verb, `resolve`); generate via TTS / music / image models when the catalog misses; produce voiceover, transcription, captions, and background removal through one shared audio engine; operate on media (cut / reframe / transform); and reuse assets across projects. Keeps search noise on disk, hands the agent one path or block. Use for any audio, image, icon, logo, voiceover, caption, color-grading, or media-asset need.

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 the changes from all open Renovate bot pull requests of a GitHub repository into the local working tree. Use this skill when asked to apply, merge locally, consolidate, batch, or try out Renovate/dependabot-style dependency update PRs so the combined upgrade can be built and tested in one go. This skill only modifies local files; it never commits, pushes, merges, or closes anything on GitHub.

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 authoring reusable, idempotent MATLAB scripts that build System Composer architecture models via the architecture-modeling API — `systemcomposer.createModel`, `addComponent`, `addPort`, `setInterface`, `connect(srcPort, dstPort)`, interface dictionaries (.sldd) with `addInterface`/`addElement`, profiles/stereotypes with `Profile.createProfile` and `addStereotype`, or `systemcomposer.allocation.createAllocationSet`. Also trigger when debugging these APIs (connections that don't appear, interfaces that don't resolve, profile save errors, `createAllocationSet` signature-mismatch errors). Do NOT trigger for ad-hoc structural edits to an already-built model (adding one SubSystem, rewiring a port) — use `building-simulink-models` with `model_edit` for that.

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。

Break a plan, spec, or the current conversation into a set of tracer-bullet tickets, each declaring its blocking edges, published to the configured tracker (edges as text in one file per ticket locally, or native blocking links on a real tracker).

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。

Runtime per-test healing with evidence: multi-attribute selector healing, environment-aware diagnosis, flake classification, quarantine management, and confidence-scored auto-repair. Goes beyond simple locator fallbacks to cover action-level healing, data healing, and observable repair workflows. Use when: "flaky test," "test stability," "self-healing locator," "broken locator recovery," "unreliable test," "quarantine flaky test." Not for: bulk regenerating selectors after a planned UI refactor — use selector-drift-recovery (this skill heals ONE test at runtime; that one rewrites many tests offline). Not for: classifying/clustering CI failures into bug reports — use ai-bug-triage. Related: playwright-automation, selector-drift-recovery, ci-cd-integration, qa-metrics, ai-bug-triage.

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。

Symfony UX TwigComponent for reusable UI building blocks -- server-rendered components with PHP classes and Twig templates. Use when creating buttons, cards, alerts, badges, navbars, or any reusable UI element with props, blocks/slots, computed properties, or anonymous (template-only) components. Code triggers: AsTwigComponent, #[AsTwigComponent], ExposeInTemplate, PreMount, PostMount, <twig:Alert />, <twig:Button>, component(), computed properties, anonymous component, HTML syntax. Also trigger when the user asks "how to create a reusable component", "how to make a component library", "how to pass props to a component", "how to use slots/blocks in a component", "how to build a design system in Symfony", "what is the HTML syntax for components", "how to create a component without a PHP class". Do NOT trigger for components that re-render dynamically on user input (use live-component), for JS behavior (use stimulus), or for page navigation (use turbo).

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。

Interact with Ethereum and EVM blockchains using ethers.js. Use when a user asks to connect to Ethereum, read blockchain data, send transactions, interact with smart contracts, or build a dApp frontend.

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 local-first applications with ElectricSQL — sync Postgres data to client devices in real-time. Use when someone asks to "sync database to client", "local-first app", "ElectricSQL", "offline-first sync", "real-time Postgres sync", "sync Postgres to SQLite", or "build an app that works offline". Covers shape-based sync, real-time subscriptions, offline support, and conflict 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。

Write CI/CD pipelines as code with Dagger — portable, cacheable, container-based pipelines that run locally and in any CI system. Use when someone asks to "write CI pipeline in TypeScript", "portable CI/CD", "run GitHub Actions locally", "Dagger pipeline", "CI as code", "containerized build pipeline", or "test my CI locally before pushing". Covers Dagger SDK (TypeScript/Python), pipeline composition, caching, secrets, and multi-stage builds.

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 attacks from server logs and blocks malicious IPs with CrowdSec, an open-source, crowd-sourced alternative to fail2ban. Use when a user asks to block brute force attempts, protect SSH or a web server, set up a community blocklist firewall, add a WAF, or install CrowdSec with Docker.

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。

Runs GitHub Actions workflows on your own machine in Docker containers with act, so CI can be tested without pushing. Use when a user asks to test GitHub Actions workflows locally, debug a failing CI pipeline, pass secrets or inputs to a local run, or run workflows offline.

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。

World-class level design expertise - spatial storytelling, player flow, blockout methodology, and the invisible hand that guides players without them knowingUse when "level design, blockout, graybox, whitebox, player flow, level layout, combat arena, exploration space, map design, multiplayer map, pacing, weenie, landmark, gating, metroidvania, open world design, linear level, environmental storytelling, teaching through design, playtesting, heatmap, metrics, sightlines, level-design, game-development, spatial-design, blockout, graybox, player-flow, pacing, environmental-storytelling, combat-design, multiplayer-maps, open-world, linear-design, metroidvania" mentioned.

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。

Integrating local LLMs into Godot games using NobodyWho and other Godot-native solutionsUse when "godot llm, nobodywho, godot ai npc, gdscript llm, godot local llm, godot chatgpt, godot 4 ai, godot, llm, nobodywho, gdscript, game-ai, npc, local-llm" mentioned.

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。

替换占位定位符为真实选择器（六级优先级）。触发：替换定位符、locator、selector、定位失败、元素找不到、DOM 分析。

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。