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概要と使いどころ
Search the Unity asset database using a search filter string. The filter accepts names, labels (`l:`), types (`t:`), AssetBundles (`b:`), areas (`a:`), and globs (`glob:`). See the body for the full filter syntax.
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。
Connect Modal and create reusable cloud machines with the bundled standard image, on-demand daemon installation, and snapshot lifecycle.
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 Apache Tika as a Docker container when you need guaranteed OCR (scanned PDFs, images) or geospatial raster support with zero local install — `apache/tika:<version>-full` bundles Tesseract, GDAL, ImageMagick, and fonts. Also covers the minimal image, port/volume/memory conventions, the path-identity mount gotcha, and how to confirm OCR actually ran rather than silently returning no text. Powered by Apache Tika. Use when a local `tika-app`/`tika-server` doesn't have Tesseract installed, or you want a disposable, self-contained parsing environment. Companion to the `file-to-markdown` skill, which covers the parsing calls themselves once a server is up.
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。
Provides React Native performance optimization guidelines for FPS, TTI, bundle size, memory leaks, re-renders, and animations. Applies to tasks involving Hermes optimization, JS thread blocking, bridge overhead, FlashList, native modules, or debugging jank and frame drops.
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。
Scaffold, build, and package SwiftPM-based macOS apps without an Xcode project. Use when you need a from-scratch macOS app layout, SwiftPM targets/resources, a custom .app bundle assembly script, or signing/notarization/appcast steps outside Xcode.
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, validate, publish, update, inspect, query, roll back, or archive a dynamic Marina applet. Use for Artifact+-style web apps that should run behind Marina authentication, carry small bundled assets or data, use an applet-owned Postgres schema, or add a trusted Python ASGI backend without a Marina image deployment.
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 LinkedIn data for profile, company, job, post, feed, inbox, recruiting, and outreach work through the bundled LinkedIn MCP server. Use only for an explicit LinkedIn request.
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。
Codex-only team orchestration: run a named team of cooperating Codex workers with durable, script-managed state. MUST USE when the user asks Codex to create, run, coordinate, inspect, archive, or delete a team of agents/threads/sessions, or to work on something as a team in parallel. FIRST inspects the active tool surface (checking tool_search for deferred tools) and tells the user the route: native MultiAgentV2 agents (flat spawn_agent with task_name) when available, Codex App threads as the fallback, or a plain-subagent split when neither set exists. The main session is always the leader; members are defined by a concrete part, ownership area, or perspective - never a vague job role; a bundled cross-platform script writes the .omo/teams state plus an auto-generated member field manual. Use a team when the work is not perfectly isolated but parallelizing helps; use plain subagents when scope is perfectly isolated or the goal is ambiguous. Triggers: team mode, teammode, make a team, run as a team, team of agents, coordinate threads, parallel Codex threads, archive the team.
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。
Contribute a verified bug fix for LazyCodex, lazycodex-ai, omo-codex, bundled Codex skills, or upstream Codex CLI bugs. Opens a fork PR only for upstream openai/codex; LazyCodex-owned defects become a verified-fix issue on code-yeongyu/lazycodex (never a PR — that repo is a generated distribution mirror). Use when the user asks to fix a bug, contribute a bug fix, contribute to fix bug, open a PR for a bug, or debug and PR a LazyCodex/Codex defect.
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。
Compare option candidates and score components, with funding, expiry and assignment risks. Use when the user asks to options strategies with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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 report views, ratings, key assumptions and risks with sources and dates. Use when the user asks to research report breakdown with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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。
Separate reported claims from impact inferences, with related assets and next checkpoints. Use when the user asks to news impact with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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。
Score Hong Kong and China A-share dividend candidates across yield quality, durability, cash flow, valuation and momentum. Use when the user asks to dividend strategy with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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。
Score observed price trend, confirmation, risk and participation without forecasting a price. Use when the user asks to momentum following with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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。
Score ETF trend, risk, liquidity, cost and available tracking and theme signals while preserving data gaps. Use when the user asks to etf strategy with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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。
Compare research records you provide to see changes in facts, scores and judgments. Use when the user asks to investment review with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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。
Connect fundamentals, sentiment and risk to supporting and opposing evidence. Use when the user asks to stock opportunities with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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。
Aggregate user-supplied disclosed buys and sells by source without automatically copying trades. Use when the user asks to smart money tracking with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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。
Find published research and institutional views with sources, dates and related assets. Use when the user asks to research reports with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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 an auditable grid from a price range, current price and capital. Use when the user asks to grid plan with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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 a contribution schedule and calculate a supplied price-path cost basis without predicting returns. Use when the user asks to dollar-cost averaging with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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 the user asks for text-to-speech narration or voiceover, accessibility reads, audio prompts, or batch speech generation via the OpenAI Audio API; run the bundled CLI (`scripts/text_to_speech.py`) with built-in voices and require `OPENAI_API_KEY` for live calls. Custom voice creation is out of scope.
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 the user asks to inspect Sentry issues or events, summarize recent production errors, or pull basic Sentry health data via the Sentry API; perform read-only queries with the bundled script and require `SENTRY_AUTH_TOKEN`.
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 the task requires automating a real browser from the terminal (navigation, form filling, snapshots, screenshots, data extraction, UI-flow debugging) via `playwright-cli` or the bundled wrapper script.
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。