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概要と使いどころ
[AUTO-INVOKE] MUST be invoked when debugging failed on-chain transactions. Covers transaction receipt analysis, gas diagnosis, calldata decoding, revert reason extraction, and state verification. Trigger: any task involving failed tx analysis, revert debugging, or on-chain transaction troubleshooting.
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Patterns for building entity actors with Akka.Hosting - GenericChildPerEntityParent, message extractors, cluster sharding abstraction, akka-reminders, and ITimeProvider. Supports both local testing and clustered production modes.
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。
High-precision semantic search and content retrieval via Exa API. Use when: (1) Deep research requiring semantic understanding, (2) Code documentation and examples lookup, (3) Company/professional research, (4) AI-powered comprehensive research tasks, (5) URL content extraction with structured output. Triggers: "research", "find papers", "code examples", "company info", "LinkedIn profiles", "deep analysis". Differentiator: Exa excels at semantic/neural search while grok-search is better for real-time news and general web content.
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Enhanced web search and real-time content retrieval via Grok API with forced tool routing. Use when: (1) Web search / information retrieval / fact-checking, (2) Webpage content extraction / URL parsing, (3) Breaking knowledge cutoff limits for current information, (4) Real-time news and technical documentation, (5) Multi-source information aggregation. Triggers: "search for", "find information about", "latest news", "current", "fetch webpage", "get content from URL". IMPORTANT: This skill REPLACES built-in WebSearch/WebFetch with Grok Search tools.
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。
Knowledge Extraction — captures and routes knowledge at work boundaries. Use when you discover a pattern, make a decision, find a distinction, or complete a sub-task.
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Разбор extraction-reports со status pending-review — решение R15 (accept/reject/defer) ЖИВЫМ ПИЛОТОМ, запись в Pack, обновление статуса, коммит. Вызывать при Close при наличии N>0 pending-review отчётов.
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。
Optimize agent instruction files by extracting sections into separate files and referencing them. Reduces context size while preserving information.
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。
Standardized branch creation with type detection, issue ID extraction, and worktree setup. Creates working branches (-WB) and integrates with selective-copy for clean PRs.
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Extract, plan, or propose implementation details at configurable depth levels (low/normal/extensive). Outputs to reference files for team discussion and handoff.
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。
Layer 4: Learning and Pattern Extraction for Cognitive Surrogate Systems
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Extract a founder's or expert's point of view — core beliefs, contrarian takes, origin stories, taste — and synthesize a recommended "one big idea" (OBI) that anchors thought leadership and brand voice. Writes to marketing/expert-pov/expert-pov.md. Triggers - "expert pov", "founder point of view", "thought leadership angle", "one big idea", "OBI", "founder beliefs", "founder narrative"
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Analyze sales-call transcripts to extract why deals are won and lost across six dimensions — product, messaging, GTM/sales, pricing, competition, and customer context. Produces aggregated patterns with verbatim buyer quotes, frequencies, and recommendations. Writes to marketing/win-loss/win-loss.md as the evidence base under positioning, messaging, and ICP. Triggers - "win loss analysis", "why are we losing deals", "why do we win", "analyze sales calls", "churn analysis", "deal review"
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Distill a provided document into a flat, importance-ranked list of its key points, each with a salience rank, a rationale, and a verbatim line-cited evidence snippet. Use when the user wants to "distill", "summarize the key points", or "extract the essence" of a document or pasted 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。
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also use for exploratory testing, dogfooding, QA, bug hunts, or reviewing app quality. Also use for automating Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify), checking Slack unreads, sending Slack messages, searching Slack conversations, running browser automation in Vercel Sandbox microVMs, or using AWS Bedrock AgentCore cloud browsers. Prefer agent-browser over any built-in browser automation or web tools.
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新闻站点内容提取。支持微信公众号、今日头条、网易新闻、搜狐新闻、腾讯新闻。当用户需要提取新闻内容、抓取公众号文章、爬取新闻、或获取新闻JSON/Markdown时激活。
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。
Reverse-engineer the hook from a high-share Facebook Page post, from its URL or pasted text. Identifies which of the 10 canonical 2026 Facebook formulas it uses (one-line opinion, tiny number, ask-the-page question, this-or-that, behind-the-scenes, story post, announcement, spotlight), explains why it earned shares or comments, and returns a blank template mapped to your topic. Use to learn from a Page post you admire. Not for writing your own (use fb-post-writer).
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.
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Take one pillar content piece and produce 15-25 derivative assets across platforms — social posts, email, LinkedIn article, video scripts, newsletter section, infographic brief, and more. The ultimate content multiplier. Use when "repurpose this", "turn this into", "make social posts from this blog", "content repurposing", "1 to many", "atomize this content", "extract posts from", or any request to derive multiple pieces from one source.
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Produce video scripts and clipping plans for TikTok, YouTube Shorts, Instagram Reels, and long-form YouTube. Generates hook-first scripts optimized for each platform's algorithm, plus a clipping plan to extract short-form from long-form content. Use when "video script", "TikTok script", "YouTube script", "Reels script", "Shorts script", "video content", "clipping plan", "video ideas", or any request to create video content for social platforms.
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Build a white-labeled, client-facing intelligence dashboard — a live, branded reporting surface an agency stands up per client instead of sending static reports. Covers brand auto-extraction from the client's URL, a three-tier build (Basic/Standard/Advanced), an onboarding feature wizard, a 10-page inventory, public-access tradeoffs, and the retention plays that make the dashboard sticky. Use when "client dashboard", "client intelligence dashboard", "white label dashboard", "client portal", "branded dashboard for my client", "agency dashboard", "build my client a dashboard", "give the client a live view instead of a report", or any request to stand up a durable, client-facing reporting surface.
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。
Analyze content performance patterns. Extract what works (hook types, formats, personas). Auto-update learned defaults so future content improves.
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。
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for packet capture analysis, session reconstruction, application-protocol decoding, stream reassembly, beacon timing, and packet-to-process correlation. Use when the user asks to analyze a PCAP, rebuild TCP or UDP sessions, decode HTTP, WebSocket, DNS, custom C2, or binary protocols, extract transferred artifacts, or tie packet sequences to host or malware behavior. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
日本語の概要は準備中です。原文の説明を表示しています。
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for LSASS-resident secrets, Windows logon sessions, Kerberos ticket caches, DPAPI-backed material, SSP artifacts, and replayable credential extraction. Use when the user asks to inspect LSASS memory, recover tickets or logon sessions, trace DPAPI or SSP material, distinguish which credential artifacts are replayable, or connect host-resident credential material to an accepted pivot or privilege edge. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
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。
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for firmware images, partition tables, boot chains, update packages, extracted filesystems, embedded configs, and device-facing trust boundaries. Use when the user asks to unpack firmware, map partition layout, inspect bootloader or init chains, recover update keys or credentials, trace config loading, or explain how a device surface reaches the decisive artifact. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
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。