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The interview primitive for putting open decisions to an owner. Use on 'grill me', 'stress-test this', or 'what do you need from me before you build this', and whenever a plan, scope, spec, vision, or question ledger needs owner rulings. NOT for steps only a human can perform (use a guided session).
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This skill should be used when the user wants to "synthesize two competing solutions without averaging", "resolve a design/value disagreement by lifting to a higher frame", "止揚 / アウフヘーベン", "矛盾を止揚", "独立案を統合", "平均化せず統合", "contradiction lift", "sublate competing designs", or has two good-but-divergent answers to the same question and wants a higher-order resolution (a selection mechanism) or an honest aporia — not a compromise. NOTE: Use this when two independent solutions diverge and you want to PRESERVE both truth-moments while lifting to a higher frame. Use devils-advocate to stress-test ONE proposal with an assigned opponent, strong-inference to find an unknown cause, and dialectic-loop to validate a claim against a real corpus.
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Gives coding agents temporal awareness by reading the session transcript the host already writes, so the agent stops guessing about time and stops repeating commands that just failed. Activates whenever an agent reasons about recency, elapsed time, retry windows, deploy cooldowns, memory or file staleness, idle detection, or any "when / how long ago / how long did that take" question. Required for autonomous, parallel, or long-running agents.
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Find and answer from saved Knowledge vault pages with source citations. Use for questions about stored documents, meetings, people, or projects; not for recalling conversation history or searching the web.
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Resolve and enrich Knowledge people, companies, projects, and concepts during an authorized ingestion or entity update, with sourced State, timelines, and back-links. Read-only identity questions do not authorize writes.
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Researches a question to something usable — a verdict with a flip condition, a versioned playbook or a graded report — every claim tagged by evidence. Trigger on which X should I pick (even from pasted pages), is Y worth it, compare A vs B, go/no-go, research this, deep research, fact-check a doc, write or merge a reference guide or playbook, grade a research report, read a bot-blocking source (Reddit, YouTube, X), or map an unfamiliar repo before contributing (entry points, flows, where to change X); or say researchscribe (verdict, playbook, research, verify, sources, map, refresh). Code review is engineering tooling's; fiction canon is lorescribe's; messages commscribe's; prompt model picks promptwright's; skill niches skillwright's; config rigwright's; brands brandscribe's.
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Answers plain-word questions from a repo's CSV, JSON, Parquet and YAML files, or a .duckdb file, with DuckDB, and shows the SQL it ran. Read-only. Trigger to query, count, join, filter or summarise data files, including analytics CSVs exported from a video platform; to build a Parquet or DuckDB cache; to check no .duckdb, .wal or .parquet cache is committed or stale; when a query hits a locked database file; or say duckrunner (ask, cache, check, refresh). Needs the user-installed duckdb Python package; never a database server. DuckDB docs, S3 and MotherDuck are the duckdb-skills plugin's; outside research researchscribe's.
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Vets third-party skills, plugins, MCP servers, GitHub Actions and model weights before install, with a verdict (PASS, CONDITIONAL, HOLD, FAIL) and install terms. Trigger on any should-I-install question, even with its files or hooks pasted in or a scan already clean; is this skill safe, vet this MCP server, check this GitHub Action, is this checkpoint safe or commercially usable, what does this installer write, a licence check before a fold-in, what changed in a plugin update; or say trustwarden (vet, revet, terms, refresh). Uses skillspector, zizmor, pinact and Scorecard when present; lists files no scanner read. Runtime permissions are gatewarden's; secrets shieldwarden's; your own skills skillwright's; sandboxing a download hypervrunner's.
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Library of accessibility personas representing people with various disabilities, impairments, and situational limitations. Use this skill when users ask about disability types, accessibility personas, user needs for specific conditions, how people with disabilities use technology, assistive technology users, or designing for accessibility. Triggers on requests about blindness, deafness, cognitive disabilities, motor impairments, low vision, screen readers, sign language, autism, ADHD, temporary disabilities, or any question about "how would a person with X use this".
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Skill for generating 1C:Enterprise (BSL) code with mandatory validation through MCP tools to prevent hallucinations. Use when generating, editing, or validating 1C BSL code, working with 1C metadata, or answering questions about 1C platform API.
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Executive coaching skill that helps you plan your 2026 using research-backed process goals. Guides you through discovery questions, creates outcome goals, converts them to daily behaviors, and sets up accountability systems. Use when you want to plan your year, set goals, or need a coach to help you stay focused.
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ユーザーが考えを整理するための「壁打ち」相手としてClaudeを振る舞わせるスキル。ユーザーが `/kabeuchi` と入力したとき、または「壁打ち相手になって」「壁打ちして」「思考を整理する相手になって」と明示的に依頼したときに起動する。前回の壁打ちの引き継ぎメモを添えて `/kabeuchi` が入力された場合も、このスキルで続きの壁打ちを始める。答えや解決策を先回りして提示せず、傾聴・反射・開かれた問いを通じてユーザー自身が考え抜けるように伴走する。思考がクリアになってきた段階では、次の議題への移行を提案し、新しいチャットで続けるための短い引き継ぎメモとコピペ用の開始プロンプトを一緒に作る。自動起動はしない。
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Clarify requirements before implementing. Use when serious doubts arise.
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Every product will be AI-powered. The question is whether you'll build it right or ship a demo that falls apart in production.
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Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
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Translates or rewrites Chinese text into English using a 'critical dialogue' tone, characterized by engaging questions, analytical commentary, and a conversational flow while preserving citations and facts.
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Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions
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Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
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自动从知乎热榜选题、调用 AI 生成原创回答并保存为草稿，支持自定义话题关键词、写作风格和批量生成。 Draft Zhihu answers automatically: picks hot questions, generates original answers via AI, and saves them as drafts — with custom topic filters, writing style, and batch support. Never publishes.
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Strategic advisor for Evvo Labs business decisions. Use when Vince asks for strategic advice, business opinions, market entry decisions, pricing strategy, product prioritization, resource allocation, partnership evaluation, competitive positioning, or any question about what Evvo should do next. Applies 5 frameworks: VRIO (competitive advantage), Value Stick (pricing/margin), Blue Ocean (market positioning), McKinsey Horizons (resource allocation), Strategy Diamond (initiative planning). Always read references/evvo-strategy.md before advising.
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股票投资调研执行引擎，执行8阶段投资尽调流程。接收stock-question-refiner生成的结构化调研指令，部署多智能体并行研究，生成带引用的投资尽调报告。覆盖：公司事实底座、行业周期、业务拆解、财务质量、股权治理、市场分歧、估值护城河、综合报告。当用户需要进行股票投资研究、基本面分析、投资尽调时使用此技能。
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Tactical negotiation framework based on Chris Voss's "Never Split the Difference." Use when preparing for negotiations, during live negotiation scenarios, analyzing counterpart behavior, crafting responses to difficult conversations, handling objections, salary/contract negotiations, or when asked about negotiation techniques like mirroring, labeling, calibrated questions, or the Ackerman method.
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Breaks down trading ideas into component parts for systematic Pine Script implementation. Use when analyzing trading concepts, decomposing strategies, planning indicator features, or extracting ideas from YouTube videos. Triggers on conceptual questions, "how would I build", YouTube URLs, or video analysis requests.
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Answer a question from the structured wiki before searching the web — "query the wiki", "what do we know about", synthesis request, cross-project research. Returns cited synthesis with wikilinks and counter-arguments.
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