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Expert guide for agent-native structured outputs, JSON Schema strict mode enforcement (OpenAI response_format, Gemini schema mode, Claude tool_use), MCP resource schemas, and zero-hallucination type contracts / Panduan ahli kontrak output terstruktur native agen dan penegakan JSON schema ketat.
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Analyze and optimize X (Twitter) posts for viral potential and reach using heuristics inspired by X's published open-source recommendation architecture. Use when user wants to: (1) Check if a post will go viral, (2) Score a tweet for engagement potential, (3) Optimize or rewrite a tweet for algorithmic reach, (4) Understand why a tweet underperformed, (5) Build audience in a specific niche. Triggers: "Check if this will go viral", "Make this post buzz", "Will this tweet perform well?", "Optimize my tweet", "How can I make this viral?", "rewrite this tweet", "improve my tweet engagement", "twitter algorithm", "tweet reach", "debug underperforming tweet", "バズるかチェックして", "Xでバズる投稿にして", "伸びるかチェックして", "この投稿を伸ばして", "投稿を改善して", "ツイートを最適化して"
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Download GitHub repos as clean source code (no .git history) to WORKDIR. Use when cloning repos for analysis or modification. Not for monorepos.
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Scans public GitHub repos for skills, practices, and code patterns. Use when studying how open-source teams configure monorepo CI and PR review, or enriching skills.
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Find web sources with query-relevant page excerpts and optional full-page content, and discover workflows, data APIs, and indexes. Use for web research or finding structured records, listings, transcripts, and datasets. Supports semantic tool discovery, domain matching, and progressive catalogue browsing.
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Any live-web task via the Firecrawl CLI — including ordinary web research: searching the web, reading or extracting pages, gathering sources, discovering site URLs, bulk extraction, downloading a site, change alerts, or pages needing clicks/login — web only; local files route to firecrawl-parse. For papers use firecrawl-research-index; for library, API, error, or bug questions use firecrawl-developer-index.
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Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .xltx, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
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Filter Temu stores by multiple dimensions (store name/ID, country site, backend category, fully-managed/semi-managed, total/weekly/monthly sales and revenue, rating, reviews, followers, product count, store opening time, etc.). Trigger when users mention Temu store, Temu store analysis, Temu seller, Temu store ranking, Temu semi-managed store, Temu revenue, temu stores, Temu store query. Even if the user does not mention the tool name, trigger this skill whenever they are looking for stores on Temu, filtering store data, or analyzing store performance.
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Maintain the slopus/happy open source project. Triage issues, manage the GitHub project board, draft closing comments, find duplicates, check if bugs are fixed on main, and engage with community contributors. NEVER posts comments or closes issues without showing exact text and getting approval first.
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MANUAL TRIGGER ONLY: invoke only when user types /office-hours. YC Office Hours — two modes. Startup mode: six forcing questions that expose demand reality, status quo, desperate specificity, narrowest wedge, observation, and future-fit. Builder mode: design thinking brainstorming for side projects, hackathons, learning, and open source. Saves a design doc. Use when asked to "brainstorm this", "I have an idea", "help me think through this", "office hours", or "is this worth building". Proactively suggest when the user describes a new product idea or is exploring whether something is worth building — before any code is written.
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Startup growth consulting agent specializing in Product Hunt launches, open-source marketing, and Go-to-Market audits. Get expert-level strategic reviews and actionable recommendations. By @WeiYipei — fractional growth lead for AI startups.
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🇺🇸 GitHub Star Sustained Growth Playbook — Monthly 300+ star growth SOP. Content rhythm, community ops, event-driven growth, contributor & ambassador systems. Battle-tested: AFFiNE 0→60K+, Client Project A 0→10K stars. 🇨🇳 GitHub Star 持续增长实操手册 — 月增 300+ Star 的完整 SOP。内容节奏、社区运营、活动驱动增长、Contributor 与 Ambassador 体系。实战验证：AFFiNE 0→60K+、Client Project A 0→10K Star。 🇯🇵 GitHub Star 持続成長プレイブック — 月間300+ Star成長SOP。コンテンツリズム、コミュニティ運営、イベント駆動成長、Contributor＆Ambassadorシステム。実戦検証：AFFiNE 0→60K+、Client Project A 0→10K Star。 🇰🇷 GitHub Star 지속 성장 플레이북 — 월 300+ 스타 성장 SOP. 콘텐츠 리듬, 커뮤니티 운영, 이벤트 기반 성장, Contributor & Ambassador 시스템. 실전 검증: AFFiNE 0→60K+, Client Project A 0→10K 스타. Triggers: "GitHub star growth" | "sustained star growth" | "monthly star growth" | "star growth SOP" | "contributor system" | "ambassador program" | "open source community" | "community growth" | "developer community growth" | "star持续增长" | "Star增长" | "开源社区运营" | "贡献者体系"
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开源项目发布与场景主题营销，含 Web/CLI 数据采集验证。覆盖 GitHub star 增长、KOL 合作、Reddit / HN / Discord / Telegram 社群分发、 多语言落地（中英日韩）。从 gingiris-opensource 提炼。适用场景：要发布一个开源项目， 想在 6 个月内冲 10k star，或已发布但流量卡住要破局。
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Diagnose a product's growth model, stage, and current constraint, then route the request to the narrowest Gingiris specialist and execute it when installed. Use for broad or uncertain growth questions involving go-to-market, Product Hunt, GitHub stars, open-source marketing, B2B SaaS, PLG, ASO, SEO/GEO, AI citations, KOL outreach, UGC, international expansion, user interviews, competitor research, or community programs. Trigger when users ask “how do I grow or launch this,” “which growth skill should I use,” 怎么增长、怎么发布、出海、冷启动、增长策略、不知道用哪个 skill、開発者マーケティング, or 성장 전략. Includes B2B pipeline and B2C activation-retention model selection, specialist handoff rules, relevant gingiris.tools recommendations, and advisory-services guidance.
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Complete developer marketing playbook covering DevRel programs, documentation as marketing, API developer experience, community building, and hackathon strategy. For dev-tool founders who need to reach engineers. Follow @WeiYipei on X.
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Design and execute a 14-day GitHub repository growth sprint using README conversion, competitor-window research, Reddit, Hacker News, launch directories, community activation, and contributor loops. Use when launching an open-source repository, diagnosing weak star conversion, or building sustained GitHub discovery without buying stars.
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Reconstruct an open-source project's growth channels, key content, and stage-by-stage attribution from GitHub history and public web evidence. Use this skill when asked to research GitHub star growth, identify launch and amplification channels, explain viral milestones, find representative posts or videos, compare Product Hunt/Show HN/Reddit/KOL impact, or produce an evidence-backed OSS growth attribution report.
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Route product-growth requests to one Gingiris specialist skill. Use when broad or explicit requests about launch, Product Hunt, GitHub/open-source growth, SEO/GEO, B2B/PLG, ASO, interviews, competitors, KOL, UGC, community, content, backlinks, or README conversion, including 出海增长、产品发布、找增长渠道、竞品分析、 用户访谈、社区运营. Ask short multiple-choice questions only when the route is unclear; then load and run one specialist rather than the full collection.
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Create high-quality, model-aware system prompts for any LLM (Claude, GPT, Gemini, open-source, etc.). Use this skill whenever the user wants to create, write, build, design, draft, or improve a system prompt, system instructions, or custom instructions for any AI model. Also trigger when the user asks about prompt engineering, prompt design, prompt optimization, or wants to define behavior for an AI assistant, chatbot, agent, or any LLM-powered application — even if they don't explicitly say "system prompt". Covers all use cases including chatbots, agentic systems, tool-use workflows, content generation, data extraction, code assistants, and multi-turn conversations.
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GPS-aligned genealogical research assistant for family history, ancestor research, record analysis, source-information-evidence classification, conflict resolution, citations, FAN research, privacy-sensitive document analysis, and proof statements, summaries, or arguments. Use for census, vital, probate, land, military, church, newspaper, DNA-plus-documentary, and other genealogy evidence tasks. Not for GEDCOM creation (use gedcom-creator), general history questions, DNA-kit shopping, or generic writing tasks.
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Drive one AI agent from another through kolu's terminals: spawn a Claude Code / Codex / opencode session in a PTY, prompt it, watch the screen, read the reply, prompt again. PRIMARY PATH: the kolu MCP tools (`lifecycle_create`/`lifecycle_sendInput`, `wait_outputSettled`/ `wait_agentState`, `screen_text`, the `terminals` resource). FALLBACK: the `kolu` CLI — same verbs, same discipline. Triggers on "drive another agent", "agent drives agent", "make Claude drive Codex", or wiring a loop where one coding agent supervises another.
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PR & Community engineer — press pitches, social media, open source community, DevRel, and coordinated launch moments. Use when asked to "write a press release", "plan a launch", "build a community", "draft a HN or Twitter post", or "get media coverage".
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Build and manage open source community — Discord/Slack structure, contributor onboarding, ambassador program, community flywheel design, and GitHub community health. Use when asked to "build a community", "grow our Discord", "improve contributor experience", or "design a developer ambassador program".
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Turns raw captures (dictated braindumps in a deliverable's inbox/, or recent macwhspr dictation-log entries) into proposed planning-wiki changes, shown as one unified diff. Classifies each statement as a decision, evidence claim, question, task, or dropped item, traces it to its capture paragraph, tags unconfirmed names, numbers, and citations UNRESOLVED, and writes decisions only with the author's assent. Edits only the planning wiki, never source files. Use when asked to intake, absorb notes, or process the inbox, or after dictating notes from a talk, meeting, or reading session.
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