「chat run」の検索結果

Grida AI agent system work: `@grida/daemon` (DaemonServer, loopback HTTP perimeter, files/workspaces, secrets store, daemon discovery) and `@grida/agent` (the agent tenant: sessions, providers/BYOK, runtime/tool execution, skills discovery, prompts, tiers, sandbox hosts). Use for `packages/grida-daemon/**`, `packages/grida-ai-agent/**`, desktop sidecar protocol changes, agent chat transport, and bugs in agent state or streams. For pure Electron window, preload, menu, deep-link, or CDP work, use `desktop`.

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Run or inspect local music analysis and plan or apply beat-, downbeat-, or section-synced video cuts or photo placements. Use for BGM beat edits, rhythm cuts, 卡点剪辑, musical structure, BPM, mood, genre, or instrument questions.

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Administers the email, chat, meeting and file-sharing platform the organization runs on — tenant and domain configuration, mail authentication and routing, phishing and spam controls, shared mailboxes and distribution groups, external sharing and guest access, permission sprawl in file storage, and retention and legal hold. Use this to configure a tenant, tighten sharing, investigate a mail delivery or phishing problem, or work out who can see a file and why.

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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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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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Generate and render Mermaid diagrams for architecture docs, READMEs, PRs, terminals, chats, and CI as themed SVG, PNG, or ASCII/Unicode art. Use this skill whenever the user provides Mermaid code or .mmd files; asks for a flowchart, sequence/state/class diagram, ERD, XY chart, or architecture/workflow/data-model visualization; or wants to beautify, theme, batch-convert, or make a diagram terminal-friendly. Runs locally without a browser or DOM, with 15 built-in themes and custom colors.

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Set up and run a body-doubling session — using another person's presence (in the room, on a call, or a chat check-in) to start and stay on the task your ADHD brain keeps bouncing off. Use when someone says 'I can't start this task', 'body double with me', 'I only work when someone's around', or has ADHD/executive-dysfunction and a task that won't begin. Produces a session plan, the exact ask to send a body-double partner, and a solo fallback for when no one's available.

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Deterministic pre-publish scan that refuses AI-slop tells in anything about to be written, published, or sent: files, artifacts, slide titles, table headers, diagram labels, chat messages, commit messages. Use before publishing or sending any deliverable, in CI, or wired as a Claude Code hook so the check runs without being remembered. The editorial counterpart is no-ai-slop, which rewrites; this one blocks.

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Check and improve your brand's visibility across AI search engines (ChatGPT, Perplexity, Gemini, Grok, Claude, DeepSeek). Set up tracking, run visibility analyses, audit your website for AI readability, and get actionable recommendations. Uses the npx goose-aeo@latest CLI.

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Fast path for a minimal CloudBase Web + database demo (最小前后端 / 最小可用 fullstack / Lovable-like BaaS). Defaults to @cloudbase/js-sdk client CRUD (NoSQL app.database / PG app.rdb), MCP-only schema, preview-first, and forbids cloud functions unless secrets, cron/background jobs, or logic that security rules/RLS cannot express. Use for 搭一套 demo、留言板、Todo、Notes、Kanban, or when users say 带云函数+云数据库 but only need CRUD. NOT for production multi-service backends, CloudRun, WeChat Mini Programs, or tasks that truly need server secrets.

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Use when animating characters or objects in Blender through Python, a bouncing ball, walk or run cycle, jump, acting shot, lip sync, eye darts or facial animation, blocking in stepped keys, splining, polish, timing and spacing, arcs, overlap, squash and stretch, graph editor handles, slotted actions or NLA layers, staging a playblast, or when animation looks floaty, stiff, slides, pops, chatters, the subject is too small in frame, or a knee pops and needs an expert review.

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Use when animating a character or prop in Maya through Python: a walk or run cycle, a jump or landing, a heavy lift, throw or punch, an acting or dialogue shot, lip sync, eye darts and blinks, stepped blocking, splining, polish, Graph Editor tangents, animation layers, mocap cleanup or retargeting, game clips and root motion, or reviewing a playblast. Also when motion looks floaty, weightless, mushy, poppy, posey, sliding or chattery, or feet slap or skate.

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Use for the owner's personal creator-content thumbnails and covers for short video, Bilibili, Douyin, WeChat, or similar platforms from a title, summary, established real portrait, kangaroo IP, product Logo, screenshot, or app reference. It enforces the owner's visual signature, runs a four-concept selection stage, then five responsive platform ratios. Do not use for generic clients, book or album covers, slide title pages, generic posters or social cards, article body illustrations, document headers, website hero art, or unrelated image edits unless the user explicitly invokes cover-skill and accepts the personal-signature rules.

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Create, revise, validate, or package Bot Generator Bot agent specifications and runnable MetaHarness agents using its CLI or MCP. Use for this repository's agent creation workflow, not unrelated chatbot products.

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Implement or review SignalR hubs, streaming, reconnection, transport, and real-time delivery patterns in ASP.NET Core applications. USE FOR: building chat, notification, collaboration, or live-update features; debugging hub lifetime, connection state, or transport issues; deciding whether SignalR or another. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.

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Manages Volcano Engine ContextSearch control-plane and application-console operations. Use for ContextSearch scene, AgenticSearch, data source, indexer, search-config, model, deployment, network, specification, and API-key administration. Do not use for generic web search or runtime RAG, image, or video retrieval and chat.

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Send and receive WhatsApp messages via the unofficial linked-device client pywhats (pip install pywhats) — pair with QR, send text/images, group chat, read receipts, presence/typing, and a long-running JSON event stream. Use when the user wants to script WhatsApp as a linked companion device (like WhatsApp Web), pair a device, send a WhatsApp from Python, or listen for inbound messages. Triggers: 'whatsapp', 'send whatsapp', 'pair whatsapp', 'pywhats', 'linked device', 'whatsapp web client'. NOT the official WhatsApp Business/Cloud API.

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Use this skill for maintaining, migrating, debugging, and safely operating Microsoft AutoGen Python 0.7.x applications, including AgentChat, Core runtimes, extensions, Studio, Magentic-One, AG Bench, and pyautogen compatibility.

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Use when the user wants to humanize text, trim slop, de-AI or de-slop writing, remove AI tells, fix robotic or ChatGPT-sounding prose, or make writing sound human and natural. Also run before delivering a CV, cover letter, email, report, or essay to be sent. Removes 71 documented AI-writing patterns with a local detector, preserves numbers, names and citations, and rebuilds toward a human voice rather than a flat husk. Mode-aware, so it never fabricates voice on factual content.

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After you give a substantive answer or draft that the user may act on — advice or recommendations, drafted artifacts such as goals, plans, pitches, proposals, or emails, estimates or projections, analysis or interpretation of data, factual claims they may rely on, or a multi-step argument — invoke this skill BEFORE finalizing your reply and then, if it applies, append 2-3 short follow-up questions, each tied to something specific in what you just produced, that help the user check key facts, probe the reasoning or assumptions, and notice missing context. Do this at most once per conversation. Skip it when the user asked a trivial how-to or simple lookup, wants a purely educational explanation, asked you only to format, convert, or assemble a file from content they provided, is writing code they will run, is doing creative writing or casual chat, or already asked you to double-check, cite, or review — the skill file explains these boundaries and the exact output format.

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Send an end-to-end-encrypted message to a peer, autonomously. Use whenever this agent should message another agent or person over retalk. Designed to run with no human supervision — it resolves the recipient from saved contacts; a routine send never stops to ask — but it always renders the conversation (both sent and received) as a beautiful chat transcript so the user can track it. (Recipient/relay are set up once by the init skill.)

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Dify is an open-source platform for building LLM apps such as chatbots, agents, workflows and RAG knowledge bases, and it exposes every published app as a REST API. Use when a user asks to self-host Dify with Docker Compose, configure Dify environment variables, call a Dify app or workflow API, upload documents to a Dify knowledge base, export or import a Dify DSL file, run a Dify app from the terminal with difyctl, or upgrade and back up a Dify instance.

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Continue is an open-source AI code assistant for VS Code, JetBrains and the terminal (the cn CLI) that works with any LLM: Claude, GPT, Gemini, Ollama and other local models. Use when a user asks to configure Continue with config.yaml, add chat or tab autocomplete models, write rules or custom prompts, connect MCP servers, run cn headless in scripts, or migrate from config.json. Continue was acquired by Cursor in June 2026: the release from that month is final and the Hub is offline, so the skill covers local, self-configured use.

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Cerebras Inference is a hosted LLM API that runs open models on Cerebras wafer-scale chips at thousands of tokens per second, through an OpenAI-compatible endpoint. Use when a user wants the lowest-latency chat, code completion or agent loop, asks how to call the Cerebras API or SDK, needs streaming, tool calling, strict JSON schema output or reasoning control, or hits a "model not found" error from a retired Cerebras model ID.

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。