「ada」の検索結果

Create a technical split-screen design system with dual panels, fine frame lines, mono metadata, quiet editorial typography, and premium inset surfaces.

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。

Reveal marked-up text word by word as scroll progress advances, while preserving semantic inline links, emphasis, responsive line wrapping, and reduced-motion readability. Use for headlines, quotes, manifestos, product statements, onboarding messages, or editorial passages where scrolling should pace comprehension rather than simulate typing.

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 dark-mode glassmorphism interfaces with readable contrast, frosted surfaces, and gradient borders using a pseudo-element mask. Use when asked for glass cards, frosted dark hero sections, blur panels, or dark UI systems with gradient/glow borders.

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。

Create readable, performance-safe Three.js game visual effects. Use for attacks, impacts, damage feedback, status effects, spell trails, particles, shaders, telegraphs, quality tiers, and reduced-motion alternatives.

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。

Profile, diagnose, and improve Three.js or WebGL game performance without regressing gameplay. Use for frame-time drops, CPU/GPU pressure, draw calls, texture and geometry budgets, animation loops, adaptive quality, mobile performance, and browser performance verification.

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。

Design, implement, tune, or test readable tactical action combat for web games. Use for attack timing, guard and dodge windows, hit contact, posture, lock-on, weapons, boss phases, combat feedback, and deterministic combat tests.

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。

Author or revise readable, flat-world Three.js game levels. Use for movement and camera routes, collision and navigation, encounter zones, landmarks, objectives, pickups, motivated lighting, visibility, deterministic level data, or desktop and mobile playthrough verification.

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 a game's combat skills and spells out of 10 with blind judges, then raise the weakest to a bar, for timing and readability (does a skill read as itself, does the blow land when it lands) and for art (detail, light, trails, impact, art direction, judged against a reference such as Diablo IV). Covers filming casts on a stopped, stepped clock, contact strips and close-ups, anonymised two-judge rounds, the levers that moved scores (hero props made from a painted concept with image-to-3D, own schedules and keyed moves, painted additive textures, camera-facing ribbons, light outside the body), the traps that cost points, asset and load budgets, and shipping each skill as its own version. Use when the user asks to score, review, improve, polish or rebuild combat skills, spells or attacks; says a skill "doesn't make sense", "looks bad" or should look like another game; names a target score; or starts a "next skill" thread. Project specifics (review hooks, harness settings, where each skill's code lives, scores so far) go in an optional local references/<project>.md next to this 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。

Build, integrate, audit, or refactor rigged monsters for Three.js and web action games. Use for monster asset contracts, procedural or imported creature rigs, semantic joints and sockets, hurtboxes and attack volumes, combat animation states, enemy-runtime adapters, LODs, deterministic review fixtures, and validating that every monster follows one shared system.

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。

HARD BLOCK — never use for prediction-market/Polymarket UpDown queries; route to okx-dapp-discovery when a named DApp (Polymarket/Aave/Hyperliquid/PancakeSwap/Morpho) appears with a timeframe, or 涨跌/updown for BTC/ETH/SOL/XRP/BNB/DOGE/HYPE. Otherwise, read-only on-chain DEX data, 6 groups: TOKEN (search, hot/热门, liquidity, holders/whale, risk metadata, cluster/持仓集中度, trade history, top traders); MARKET (price/价格, K线/OHLC, index price, wallet PnL/胜率, trade history); SIGNAL (smart money/KOL/whale tracking, buy signals/信号, leaderboard/牛人榜); SOCIAL (news/新闻, sentiment/情绪, token vibe/热度, KOL leaderboard); TRENCHES (pump.fun/meme launches/新盘/扫链, dev reputation, bundle/sniper detection/捆绑狙击者, co-investor — read-only; buy/snipe → okx-dapp-discovery); WS (onchainos ws CLI, or custom WebSocket script/脚本). Also owns Market API payment/x402, quota/额度, and MARKET_API_*_OVER_QUOTA/confirming:true for all 6 groups.

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。

Internet Court adapter for GenLayer Intelligent Contract supervision. Use to specify agent-performance rubrics, evidence schemas, decision outputs, and ERC-7710 connector expectations, while delegating actual GenLayer contract writing, linting, testing, deployment, and CLI interaction to the official GenLayer skills at https://skills.genlayer.com/.

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。

Metaplex development on Solana — NFTs, tokens, compressed NFTs, candy machines, token launches, autonomous agents. Use when working with Token Metadata, Core, Bubblegum, Candy Machine, Genesis, Agent Registry, or the mplx CLI.

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。

Upload one Kleros-ecosystem file per paid request to IPFS through the Kleros x402 gateway for $0.01 USDC on Base mainnet. Use for dispute evidence, MetaEvidence JSON, court/dispute/arbitrator policies, Curate item metadata, juror justifications, or any artifact a Kleros contract or subgraph will reference by CID. Trigger when the request mentions Kleros, court, arbitrator, dispute, juror, Curate, Proof of Humanity, evidence, meta-evidence, justification, explicitly names this gateway or skill, or asks to test or validate it. Do NOT use for generic IPFS/CID requests without Kleros context; recommend a general-purpose pinning service. Each request accepts exactly one file: different bytes require separate paid uploads, while identical bytes should reuse one CID.

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 user mentions Jupiter token verification, VRFD eligibility, paying 1000 JUP to verify a token, submitting a verification request, or updating metadata via the Jupiter express verification flow.

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。

Manage the user's shared agent-skill library via skills-manager-cli — install, update, remove, deploy or undeploy skills per agent, manage presets, organize tags, search, and adopt existing skills. Use this whenever the user wants Claude Code, Codex, Cursor, or another agent to gain or lose a skill, wants to organize the central library, or asks what is installed or deployed. Prefer this over direct agent-folder installs because Skills Manager preserves source metadata, preset membership, updates, and cross-agent deployment state.

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。

Add a DeepChat LLM provider through explicit reviewed source changes. Use when a developer asks Codex to add a provider, provider profile, upstream provider config, model catalog mapping, provider auth behavior, or a special provider adapter in this repository.

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 version freshness, FR/EN parity, and metadata quality of all whitepapers and recap cards

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 custom subagent definitions for Claude Code (.claude/agents/*.md) and Codex (.codex/agents/*.toml): loadability against the native schema, description overlap, model tier, tool scope, and headless-safe instructions. Use when onboarding to a project with agents, after adding or importing agents, or when the parent agent delegates to the wrong agent.

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 a project or library of skills for metadata, trigger boundaries, workflow completion criteria, local resource closure, instruction economy, tool scope, effort, and routing evidence. Use before shipping skills, after importing a skill collection, or when a skill triggers too often or not at all.

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。

Review Apache Pinot concurrency and state safety when locks, shared callbacks, lifecycle, or distributed metadata change.

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。

TikTok user profile video scraper: input a TikTok username → output the user's profile info plus paginated video list with full metadata (engagement stats, music, video meta). Use when user mentions TikTok profile scraping, scrape TikTok user videos, get TikTok creator videos, extract TikTok profile data, TikTok user posts, TikTok account video collection, collect TikTok profile page videos, TikTok creator video list, TikTok creator data, TikTok profile scraper, tiktok user scraper, tiktok creator scraper. Also applies to influencer research, competitor analysis, content archiving for a specific TikTok creator, or extracting all posts from a TikTok account.

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。

TikTok hashtag video scraper: input a hashtag name → output paginated video list with full metadata (author profile, engagement stats, music, video meta, hashtag list). Use when user mentions TikTok hashtag scraping, TikTok tag videos, scrape TikTok by hashtag, extract TikTok hashtag data, TikTok challenge videos, get videos from a TikTok tag, bulk collect TikTok hashtag posts, TikTok video collection by tag, TikTok topic videos, collect TikTok tag data, batch fetch TikTok videos by hashtag, tiktok tag scraper, tiktok challenge scraper. Also applies to competitive research on TikTok trending topics, influencer discovery by hashtag, content monitoring for specific TikTok tags, or any task requiring video lists from a specific TikTok hashtag or challenge.

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-crawl any website from start URLs, return per-page LLM-ready text/markdown/HTML plus metadata (title, description, author, language, canonical URL, OG) and in-scope outbound links. Use when user mentions deep crawl website, recursive crawl, crawl a whole site, scrape entire website, scrape docs site, scrape documentation, scrape knowledge base, scrape blog, build RAG corpus, build vector database from website, knowledge base for chatbot, GPT knowledge files, llms.txt, sitemap crawl, BFS crawl, scrape with depth or page limit, include exclude URL globs, remove boilerplate, strip navigation header footer, website to markdown, website to text, multi-page extraction, bulk page scraping, clean markdown from URL, docs site to markdown corpus, site to clean corpus. Also applies to building RAG pipelines, indexing a customer site, syncing docs into a vector store, generating training corpora from any docs hub, or expanding a single start URL into a clean corpus of every reachable in-scope page.

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。

This skill helps users automatically extract structured image data from Google Images via BrowserAct API. Agent should proactively apply this skill when users express needs like finding images for specific keywords, gathering product style images for competitors, building visual datasets at scale, scanning visual search results for market research, tracking localized image trends by country, compiling related image thumbnails and links, extracting image titles and source logos, fetching click through URLs from image results, monitoring competitor visual assets, sourcing creative content for specific topics, looking up product pictures in different regions, collecting structured image metadata without opening detail pages.

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。