「chat」の検索結果

Build AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, or chat applications.

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Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.

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Design, create, run, monitor, and maintain Vapi Simulations for assistants and squads. Use for turning plain-language requirements into a coverage plan, simulation personalities, scenarios, structured-output success criteria, simulations, suites, extending an existing suite, chat or voice runs, tool mocks, target variables, lifecycle webhooks, regression coverage, launch readiness, CI quality gates, run-result analysis, and simulation API validation errors. Do not use for fixed-turn mock-conversation Evals unless the user is deciding between Evals and Simulations.

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 runs /dd or /ㅇㅇ to act on the current OS clipboard (text or image) without pasting it into chat. It captures the live clipboard into a local cache and uses only the manifest plus a short preview as context, so error logs and reference images do not bloat the conversation. Korean triggers: "/dd", "/ㅇㅇ", "클립보드 보내줘", "이거 분석해줘", "방금 캡처한 거", "이 레퍼런스로", "스크린샷 드롭". English triggers: "/dd", "drop clipboard", "use what I copied", "this screenshot", "this reference".

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Earnings analysis — pre- and post-earnings. Pre-earnings preview: prior-guidance review, recent-events tracking, last call's Q&A, and a key-things-to-watch framework for an upcoming release. Post-earnings: two tiers — a fast in-chat summary card (default) and a full Markdown research report (on request). Covers beat/miss, segments, margins, guidance, estimates, valuation. US / HK / A-share. Use whenever the user wants an earnings preview or a post-earnings / quarterly-results writeup. Triggers: "earnings update", "quarterly results", "Q1/Q2/Q3/Q4 results", "earnings report", "post-earnings analysis", "beat/miss", "guidance update", "earnings preview", "pre-earnings", "what to watch this earnings", "before earnings", "财报分析", "业绩更新", "季度业绩", "季报", "年报", "盈利分析", "财报点评", "财报前瞻", "业绩前瞻", "财报预览", "上季度指引", "財報分析", "業績更新", "季度業績", "季報", "年報", "財報點評", "財報前瞻", "業績前瞻", "財報預覽".

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Check a text fragment for potential secrets (API keys, tokens, passwords) BEFORE sending to chat / committing / publishing. Second protection layer on top of the pre-commit hook — manual gate, user explicitly calls on potentially sensitive text.

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Generate a topic-focused briefing in HTML from public news sources. Use when user asks for a briefing / observation / digest / 简报 / 观察 on any subject — region (Middle East, ASEAN, India), industry (semiconductors, EV supply chain, AI), policy issue (AI regulation, critical minerals, cross-border payments), institution (Fed, ECB, IMF), or theme. Output is a single self-contained HTML file with blue-color "TOPIC BRIEF" branding, optimized for both browser viewing and direct copy-paste into 微信公众号 / WeChat Official Account editor. Walks through 5 steps with one user confirmation midway. Do NOT use this skill for short summaries (<1000 字), single-piece news commentary, or already-defined report templates.

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。

How to use AI APIs like OpenAI, ChatGPT, Elevenlabs, etc. When a user asks you to make an app that requires an AI API, use this skill to understand how to use the API or how to respond to the user.

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 assistant for creating clear, actionable task descriptions for GitHub Copilot agents

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Transition from static LLM chats to autonomous agents that execute multi-step tasks. Use this when you need to automate cross-platform reports (e.g., Snowflake to Google Docs), build self-service tools for non-technical teams, or create "anticipatory" engineering workflows that draft PRs based on Slack discussions.

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 persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.

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 the current chat session for durable learnings (clarifications, corrections, decisions, pitfalls) and update .agent/memory.md. Use after critical review and before concluding 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。

Add Qdrant embedding support to v3 WordPress components for RAG chatbot. Implements component-level content chunking for searchable, structured embeddings. Use when adding embedding to new or existing v3 components.

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 'why does X work this way', 'why we picked Y', design rationale, regressions, postmortems, or data-backed thresholds. Discovers available MCPs and queries each evidence category (source control, issue tracker, long-form docs, real-time chat, infrastructure observability, error tracking, product analytics warehouse) in parallel, then returns a cited read on decisions and tradeoffs. Use how for runtime behavior.

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Investigate an alert, page, or production symptom in an incident channel or a team's oncall / monitoring channel, and report findings a human can verify. Ordinary conversation and chatter are not alerts; leave those alone. Use when an alert or page lands, when error rate, latency or saturation is up, when someone asks "why is X broken", "investigate", "what changed", "root cause this", pastes a monitor, dashboard, trace or error-tracker link, or reports production trouble; also by default when an alert lands in a covered channel unasked. Feed-level asks land here too ("which alerts matter", "triage today's alerts"), plus the scheduled alert-review routine and the ticket path ("customer X can't check out"). Runs a fast first pass posted as a short interim update with a TL;DR, every finding carrying the query or link to verify it, then proposes the fix and — with connector access and confirmation — carries it out, never unattended. Afterwards `incident-postmortem` writes it 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。

Use whenever the user wants to find, rank, or shortlist directories and listing sites where they can submit an AI product — an AI tool, AI app, AI agent, or agent skill / plugin — to get backlinks, referral traffic, and discovery. Triggers on "where can I list my AI tool", "directories to submit my AI agent", "agent-skills directories", "best AI tool directories for backlinks", "where do I get my GPT/Claude app discovered", or "pull submission details for these AI-directory domains", even when described indirectly (we built an AI agent, where do we get it in front of people). Drives the ServiceGraph API (api.servicegraph.co) — a catalog of 1,000+ product directories enriched with Domain Rating, backlinks, and organic traffic. Defer to find-mcp-directories for MCP-server listings specifically, and to find-product-directories for general SaaS/software/app launches with no AI angle. Skip finding an AI consultancy/agency to hire (use find-ai-consultancy), comparing AI products ("ChatGPT vs Claude"), building an AI tool (do-the-work), and AI link-building *services*.

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。

Iteratively edit and refine a named plan for a task through a conversational loop. Each round, the current plan is shown and the user is asked whether to keep refining, mark the plan as done, or proceed to the implementation or draft. Use when the user wants to plan a task purely through chat-driven 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。

Plan, evaluate, and produce paid ad campaigns across platforms (Meta, Google, LinkedIn, TikTok, Microsoft, Pinterest, Snapchat, Amazon, X). Evaluate existing ads, map funnel stages (TOF/MOF/BOF), produce ad variants per platform with policy compliance, output ready-to-upload copy. Use when "ad campaign", "create ads", "run ads for", "paid campaign", "media plan", "launch ads", "Meta campaign", "Google Ads campaign", "multi-platform ads", "evaluate my ads", "how are my ads doing", "audit my ads", "ad performance", "analyze ads", or any request to evaluate existing or create new advertising.

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 platform-compliant ad copy for Meta, Google, TikTok, LinkedIn, Pinterest, Snapchat, Amazon, or X. Loads TOS rules automatically. Shows char counts and format preview.

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Author, compile, inspect, and revise WAM low-poly 3D characters, creatures, props, rigs, and animations with ChatGPT Codex. Use for WAM or .wam requests, WoW-style or game-ready models, and one or more reference images or requested render views.

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。

Send third-party WhatsApp messages or sync/search WhatsApp history via wacli, not normal active chats.

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。

Give Claude Code, Codex, Cursor, ChatGPT and other MCP clients 1,000+ apps and 400+ expert-built Skills through one reusable Aident Loadout setup, with credentials kept in Aident Vault and every action recorded in Audit.

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。

Operate Lark and Feishu work objects from one agent-ready CLI instead of stitching together separate APIs and browser flows.

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Generates optimized meta descriptions using OpenAI Chat Completions API with token-aware truncation. Integrates with Yoast SEO REST API fields and Google SERP Preview validation for CTR optimization.

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。