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概要と使いどころ
Optimize ElevenLabs conversational AI agents for real estate applications. Use when creating new agents, improving conversation quality, selecting voices, engineering system prompts, configuring agent parameters, or analyzing agent performance metrics. Includes voice selection, model tuning, prompt engineering, and A/B testing strategies.
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。
LLM prompt management and evaluation platform. Version prompts, run A/B tests, evaluate with metrics, and deploy with confidence using Agenta's self-hosted solution.
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。
AI agent self-correction mechanisms: error detection, validation loops, recovery strategies, confidence scoring, and iterative refinement
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 before opening a PR, or whenever asked to self-review a diffusers contribution. Applies the same rubric as the `@claude` CI (checks the diff against references/review-rules.md, traces call paths for dead code). Reports findings grouped by severity, flagging what to fix before submitting (blocking issues + dead code) vs what to leave for the actual review. Report-only — does not edit files.
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 whenever the user wants to find, shortlist, vet, or enrich US B2B law firms — corporate, IP/patent, M&A and securities, employment, commercial litigation, regulatory/compliance, data privacy/cyber, real estate, and tax. Triggers on "find three boutique IP law firms in California", "shortlist M&A counsel for a Series-B fundraise", "patent prosecution for our hardware startup", or "pull contact info for these 10 law firm domains", even when described indirectly (outside counsel, cap-table review, GDPR/SOC2 oversight). Drives the ServiceGraph API (api.servicegraph.co) — a 100k+ US firm catalog filterable by industry, services, location, size, ratings. Skip personal/consumer legal services where the user is the end client (divorce, personal injury, criminal defense, family law, estate planning, wills) — the catalog is B2B-only. Also skip in-house GC hires, "is this NDA enforceable" DIY questions, non-US firms, individual freelancers.
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。
Assign the current or given task plan to oneself or to somebody else, with assigning it to oneself tracking the AI usage (time, tokens, and costs) of the session until the task is given back, which adds the accumulated usage to the usage attachment of the task. Use when the user wants to "assign", "take", "pick up", "give back", "hand over", or "unassign" the "task" or "plan".
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。
Intelligent pattern selection for Fabric CLI. Automatically selects the right pattern from 242+ specialized prompts based on your intent - threat modeling, analysis, summarization, content creation, extraction, and more. USE WHEN processing content, analyzing data, creating summaries, threat modeling, or transforming text.
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。
Fetches tweets from Twitter List, scores them using data metrics and AI analysis, and generates topic recommendation reports for content creators.
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 Gumroad-ready digital product from scratch — ebook, card deck, playbook, Notion template, or flipbook. Walks from concept → content outline → design brief → per-item markdown → images → multi-format build (PDF, HTML flipbook, Notion, card deck) → Gumroad sales page + email blast + launch assets. Use when "make a digital product", "build an ebook", "create a playbook", "card deck", "notion template product", "gumroad product", "make a pdf to sell", or any request to ship a sellable information product.
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。
Code-rendered motion video for a product or a client, built the way a motion studio would do it. Every frame comes from an HTML seek(t) page rendered by Playwright at 1080p60 with real motion blur, using real product UI and screenshots with a privacy blur, and an ElevenLabs hype score cut on bar lines with its drop verified on the reveal. Three formats — a 20-30 s hype launch spot, a polished feature walkthrough from real screenshots, and a 19 s pain-point video with a muted site cut and burned-in text. Delivered with baked posters, H.264 + VP9 web encodes at 1280 px (1.5-3 MB), a site-embed kit (muted autoplay or click-to-play), 9:16 social re-layouts and share copy, plus a service playbook for selling it. Use when "make a launch video", "make a commercial / promo / ad spot", "motion design video", "product walkthrough video from screenshots", "pain point videos for the site", "videos for the homepage", "sell video production", "price a video package", or a polished brand spot is wanted rather than a talking-head edit or a Remotion template batch (use /kai-video-production for those).
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。
Modern Java practices: design, errors, concurrency, security, testing, tooling. Targets Java 21 LTS baseline; Java 25 LTS features called out explicitly. Use when writing or reviewing Java code.
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。
ナッシュ均衡ソルバー。零和対戦 (ポケモン選出、構築マッチアップ、じゃんけん型メタ) の最適混合戦略、選出最適化 (pkdx select)、メタ乖離分析 (pkdx meta-divergence) を提供。「最適選出」「選出分布」「構築メタ」「対面ジャンケン」「使用率 vs 最適」等の質問時に使用。
Browserable is an open-source, self-hostable browser automation library built for AI agents. This skill turns Browserable into a repeatable workflow for navigation, form filling, extraction, and browser-based task execution with local control instead of a hosted black box.
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。
Scan a repository for secrets, keep an auditable baseline, and review only newly introduced findings during commits or CI checks.
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。
Integrate Audiobookshelf's self-hosted audiobook and podcast server into AI agent workflows. Agents can manage libraries, track listening progress, search metadata, and automate podcast episode downloads through the comprehensive REST API.
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。
Client-side initial access and social-engineering attack module. Use when the operator selects a human/client/browser/identity-delivery attack direction: ClickFix/FileFix, AiTM session phishing, OAuth device-code or consent abuse, Teams/helpdesk social engineering, HTML/file delivery, QR/mobile handoff, legacy HTA/OLE/Office paths. This is an Attack module: own the chain until host shell or remote interactive foothold. Credential/token/session are intermediate results, not the stop condition. If endpoint AV/EDR/AMSI/application-control blocks an otherwise-valid client execution path, the operator may temporarily select /edr-bypass and then resume this phishing chain until shell.
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。
Network reachability and pivoting after an operator already has a foothold. Use to make previously unreachable hosts, subnets, services or listener directions reachable via Ligolo-ng, Chisel, GOST v3, SSH/native forwarding, socat/netsh, Microsoft Dev Tunnels, DNS/HTTP/QUIC fallback transports, and multi-hop routing. This module does not exploit services, obtain credentials, or own C2/persistence. Its success condition is changed reachability: the operator can route/connect to the intended internal network/service through the selected foothold.
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 any Supabase project for security vulnerabilities, RLS misconfigurations, exposed API keys, auth bypasses, and storage issues. Use this skill whenever the user mentions Supabase security, RLS policies, database security audit, security review, penetration testing a Supabase app, checking if their database is exposed, hardening their Supabase project, fixing RLS, or anything related to securing a Supabase or vibe-coded application. Also trigger when the user asks about securing apps built with Lovable, Bolt, Replit, Cursor, or any AI coding tool that uses Supabase as a backend. Even if the user just says 'is my app secure' or 'check my database' and their project uses Supabase, use this skill. (DEPRECATED: this skill is a backwards-compat shim. Prefer the multi-backend `database-sentinel` skill, which covers Supabase plus Firebase, MongoDB, self-hosted Postgres, and self-hosted MySQL.)
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。
Work with the Toss Securities Open API for Korean and US stock market data, stock info, exchange rates, market calendars, account and holdings lookups, order history, buying power, sellable quantity, commissions, conditional orders, rankings, trading trends, market indicators, realtime WebSocket integration, and delegated trading workflows. Use when an agent needs to run user-delegated buy/sell/order-management loops, call or build against developers.tossinvest.com, inspect the Toss OpenAPI schema, generate client code, or operate with TOSS_API_KEY/TOSS_SECRET_KEY credentials.
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 should be used when the user asks to "buy token", "sell token", "swap token", "trade crypto", "check trade status", "query transaction", "scan tokens", "feed", "monitor chain", "query token", "token details", "check token safety", "list wallets", "show wallets", "my wallets", "AI scan", "AI扫链", "auto scan", "smart scan", "tweet scan", "推文扫链", "twitter scan", "onboarding", "get started", "check IP", "get IP", "IP whitelist", "查IP", "IP白名单", "launch token", "create token", "发币", "创建代币", "auto sell", "stop loss", "take profit", "trailing stop", "止盈止损", "移动止损", "holders", "top holders", "kol holders", "insider", "持仓", "持仓列表", or mentions trading on Solana/ETH/BSC/Base chains via XXYY. Enables on-chain token trading and data queries through the XXYY Open API.
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 for self-correcting implementation. Implements the reflexion loop: implement, validate, self-critique, retry (max 3 iterations).
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 benchmarking, profiling, or A/B-testing CUDA kernels or end-to-end perf in the imp inference engine on RTX 5090 (sm_120), including refreshing tests/perf_baseline.json or publishing numbers to docs/BENCHMARKS.md and the README. Triggers on "benchmark kernel", "profile cuda", "ncu", "nsys", "kernel timing", "kernel sum", "occupancy", "bandwidth bound", "compute bound", "roofline", "perf baseline", "is this regression real", "decode dropped", "aggregate throughput", "two-image A/B", "prefill kernel A/B". Do NOT use for writing/optimizing kernel code (sm120-cuda-expert) or output-quality checks (check-degeneration).
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。
Coordinates central clearing requirements with CCP selection, margin optimization, and clearing threshold monitoring. Use when managing clearing obligations, optimizing CCP selection, or analyzing clearing economics.
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。
Coordinates competitive auction workflows from teaser distribution through definitive agreement execution. Use when running sell-side processes, managing bid rounds, or tracking buyer engagement.
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。