“threads”的搜索结果

YouTube transcripts to summaries, threads, blogs.

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Azure AI Agents Persistent SDK for .NET. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools.

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Azure AI Agents Persistent SDK for Java. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools.

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Enterprise-specific view across CopilotKit + AG-UI. "Enterprise" here = CopilotKit's COMMERCIAL surfaces (Premium / CopilotKit Enterprise / Intelligence Platform / paid tiers), NOT CopilotKit running inside a big company. Tracks the commercial product surfaces (from product-surface-scan — Enterprise Intelligence, Cloud, self-host license, threads/persistence tier, Inspector, premium UI/Angular SDK, analytics, security bundle, Slack/Teams), applies the free-vs-paid classifier to decide if an issue belongs here, surfaces cross-page product contradictions, and tracks enterprise questions/complaints, community-sourced prospects (with a sales owner), and enterprise reporters with prior-week trend. Elevated to the top of the weekly report. Runs standalone ("who's at enterprise this week") or invoked by weekly-report. Triggers on "enterprise report", "enterprise signals", "enterprise status", "who at enterprise this week".

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Use when extracting Voice-of-Customer themes from existing artefacts — GH issues, PR threads, Sentry patterns. Triggers on 'what are users saying', 'recurring complaints', 'top themes'.

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Systematically find and fix performance problems in applications, frontend and backend, by measuring first. Use this skill whenever the user reports slow endpoints, high latency, poor throughput, memory leaks, large bundles, or slow page loads; wants to profile with cProfile, py-spy, Chrome DevTools, Node --cpu-prof, or perf; run load tests with locust or k6; set performance budgets or SLOs; optimize database queries (EXPLAIN, indexes, N+1); add caching (Redis); improve frontend performance (code splitting, lazy loading, image optimization, memoization, virtualization); or tune the network (CDNs, gzip/br, HTTP/2/3). Also trigger for p50/p95/p99 latency, throughput, error rate, connection pooling, async vs threads, GIL, and memory leak investigations.

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Gmail CLI for searching emails, reading threads, sending messages, managing drafts, and handling labels/attachments. Triggers: Gmail, send email, search email, read email, email thread, email draft, email labels, gmcli.

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Use when the user wants a ready-to-paste social post kit for an app, tool, or project launch or update — "make social posts", "launch posts", "post kit", "prep socials", "promote this". Produces one Markdown file with finished posts for X, Reddit, Instagram, LinkedIn, Threads, and short-form video, plus a pre-post checklist. Pull real facts from the project (repo, release, what it does, OS, links).

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Fetch any URL and convert to markdown using baoyu-fetch CLI (Chrome CDP with site-specific adapters). Built-in adapters for X/Twitter, YouTube transcripts, Hacker News threads, and generic pages via Defuddle. Handles login/CAPTCHA via interaction wait modes. Use when user wants to save a webpage as markdown.

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Comprehensive design skill: brand identity, design tokens, UI styling, logo generation (55 styles, Gemini, Atlas Cloud, or MuAPI AI), corporate identity program (50 deliverables, CIP mockups), HTML presentations (Chart.js), banner design (22 styles, social/ads/web/print), icon design (15 styles, SVG, Gemini 3.1 Pro), social photos (HTML→screenshot, multi-platform). Actions: design logo, create CIP, generate mockups, build slides, design banner, generate icon, create social photos, social media images, brand identity, design system. Platforms: Facebook, Twitter, LinkedIn, YouTube, Instagram, Pinterest, TikTok, Threads, Google Ads. Use for brand, logo, icon, banner, slide, or social-image design work.

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Build real-time chat applications with Azure Communication Services Chat Java SDK. Use when implementing chat threads, messaging, participants, read receipts, typing notifications, or real-time chat features.

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Build Azure AI Foundry agents using the Microsoft Agent Framework Python SDK (agent-framework-azure-ai). Use when creating persistent agents with AzureAIAgentsProvider, using hosted tools (code interpreter, file search, web search), integrating MCP servers, managing conversation threads, or imple...

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Turns a set of questions (form exports, helpdesk logs, meeting Q and A, chat threads, a plain list) plus the source documents the user supplies into a DRAFT FAQ grouped by theme: every answer quoted or paraphrased from a named source with a reference, verbatim quotes for dates, figures, eligibility and obligations, UNKNOWN where the sources are silent, a source register with precedence, a conflicts table and a routing list of unanswered questions to owners. Use when the user asks to "build an FAQ from these documents", "answer these questions from the policy", "turn the Q and A into an FAQ page", "group these questions and answer them from the guide" or "what do our documents say about these questions". Do not use for the manager FAQ of a changed HR policy, use policy-change-briefing instead; for checking whether a document's own claims are evidenced, use claims-evidence-map. Drafts for human review; never approves, authorises or signs off.

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Drafts an architecture or design decision record (ADR) from the discussion notes, design review minutes, chat threads and diagram descriptions the user provides: context, decision drivers, options considered with arguments as stated, the decision as the group worded it, consequences and a review date, with every factual claim tagged evidenced, asserted or UNKNOWN so unsupported claims are marked for the author to substantiate. Use when the user asks to "write an ADR", "document the architecture decision", "record why we chose this design", "turn these design review notes into a decision record" or "draft the design decision log entry". Do not use for a business or governance decision with no technical design, use decision-memo-builder instead; for the change ticket that implements the decision, use change-request-pack. Drafts for human review; never approves, authorises or signs off.

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Единый вход публикации контент-фабрики на все живые площадки: Facebook, X, Telegram-каналы, Threads, Instagram. Публикую САМ. Триггеры: /social-daily, /autopost, /postall, постить везде, разгреби очередь постинга, прогони автопостинг, постим следующий, поставь в отложку, что в очереди постинга, next social post. НЕ путать: /fb-post /x-post /tg-post = точечная дверь под один пост.

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Find live third-party GitHub issues and discussions on topics where you have real hands-on experience and artifacts, then reply with that experience to build reputation. Use when asked to answer people about your work, find threads matching your expertise, or reply with evidence from your own setup.

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Turn a fix you made for a whole class of bugs into help for others: reverse-search GitHub for people hitting the same symptom, pick the 3-5 best live threads and post one tailored answer or gist each, no copy-paste fan-out. Use after a verified class fix. Triggers: /share-fix, /sf, share the fix.

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Answer reviewers on your own pull requests in other people's repos: find threads where the ball is on your side, tell humans from bots, do exactly what was asked and reply with evidence. Use at the start of any GitHub session or on a new-review alert. Triggers: /pr-reply, /prr, answer the reviewers, who is waiting on us.

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After shipping a repo, release or feature, find who on GitHub actually needs it: search issues, discussions and catalogs for the symptom, rank live threads and draft one precise reply per consumer. Use right after any artifact goes public. Triggers: /consumer-hunt, /ch, find consumers, where to submit.

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Analyze email threads to extract current status, pending actions, timeline of events, and identify stale/outdated information. Use when asked to summarize email conversations, find outstanding action items in email chains, or detect when a thread summary is out of date.

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Capture volatile session state into a structured handoff document before context is lost. Use when ending a session, switching threads, approaching context limits, or at any juncture the user chooses.

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YouTube transcripts to summaries, threads, blogs.

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F16 on BitNet-embedding-270M prefill (8 threads) Supports I2_S conversion with optimized kernels on x86 CPUs Lossless inference with 2 bits per weight

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Knowledge base from the DoD M&Q BoK (the Manufacturing and Quality Engineering Body of Knowledge), v3.0 of July 2025, published by OUSD(R&E). Use for the manufacturing-and-quality view of the defense acquisition life cycle: what M&Q engineers do across the Adaptive Acquisition Framework phases (Pre-MDD, Materiel Solution Analysis, Technology Maturation and Risk Reduction, Engineering and Manufacturing Development, Production and Deployment, Operations and Support); the twelve M&Q threads (A–L) built on the '5 Ms'; manufacturing feasibility and producibility; Manufacturing Readiness Levels and assessments; Key/Critical Characteristics and process capability (Cp/Cpk, SPC); the standards stack (AS6500, AS9100/ISO 9001, AS9103, AS9145); technical reviews (ASR/PDR/CDR/PRR) and milestone gates; DCMA surveillance; industrial base and supply chain; and sustainment (LCSP, IPS, ILA, ISR). Scope is DoD acquisition M&Q practice on the Major Capability Acquisition path — it is a best-practice compilation, not policy, and is thin on detailed shop-floor process engineering, contract law, and the full text of the cited industry standards (which it names but does not reproduce).

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