976 skills · sorted by relevance
Unity NPC behavior design-to-code translation. Perception system architecture, decision layer patterns, action execution pipeline, faction & relationship systems, NPC memory & forgetting, crowd & squad coordination. DESIGN INTENT format: INTENT/WRONG/RIGHT/SCAFFOLD/DESIGN HOOK. Based on Unity 6.3 LTS.
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Unity level design-to-code translation. Trigger & event architecture, encounter design contracts, checkpoint & respawn, cinematic & scripted sequences, environmental storytelling hooks, level streaming & loading seams. DESIGN INTENT format: INTENT/WRONG/RIGHT/SCAFFOLD/ DESIGN HOOK. Based on Unity 6.3 LTS.
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Unity game loop and progression design-to-code translation. Core loop scaffolding, session lifecycle, win/lose condition architecture, meta loop hooks, tunable difficulty, pacing & encounter timing. DESIGN INTENT format: INTENT/WRONG/RIGHT/SCAFFOLD/DESIGN HOOK. Based on Unity 6.3 LTS.
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Creates accurate frontend implementations from visual references while maintaining design consistency. Use when user provides Figma URLs, screenshots, design images, requests visual implementation from reference, or asks to build UI matching a design. Automatically checks existing design intent patterns before implementation.
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Diagnose search-experience and intent mismatches using SERP page types, user stories, and persona scoring. Use when ranking problems appear intent- or layout-driven.
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**WORKFLOW SKILL** — Understand before implementing. USE FOR: any task where the agent might rush to code — forces understanding WHY/WHAT FOR/FOR WHOM before defining a solution, activates planning and reasoning discipline, prevents technical debt from shallow requests. Use to validate intent, plan before coding, reason before acting, challenge assumptions, prevent premature implementation. DO NOT USE FOR: deep multi-technology analysis (use contextação), persisting decisions across tasks (use task-map).
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Drafts a U.S. asset purchase letter of intent (LOI) separating binding from non-binding terms and capturing deal points, diligence, exclusivity, and closing path. Trigger on "letter of intent", "LOI", "asset purchase", "M&A LOI", "no-shop", "exclusivity", "purchase price", "due diligence".
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Manages intent — features, enhancements, bugs and the reasoning behind them — recorded as prose in the knowledge base with a lifecycle. Use when capturing new work, moving work through backlog, refinement or implementation, releasing or cancelling work, or asking what is pending, in flight, or no longer valid.
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Design AgentSpeak(L)-style BDI agents with context-guarded plans, selection functions, and intention stacks. Use for interruptible autonomy, agent policy, and multi-agent orchestration in dynamic environments. NOT for simple rule engines, static planners, or centralized workflows.
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Run a one-shot buying-intent lead scan across Reddit, Twitter/X, Instagram, and TikTok using Xpoz. Finds fresh posts from people actively looking for what a product does or frustrated with its competitors, classifies and prioritizes them, and reports where to engage and who to reach. Use when asked to "find leads", "who is asking for a tool like mine", "find people complaining about [COMPETITOR]", "buying-intent scan", or "social selling opportunities".
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Auto-invoked 7-phase workflow for complex-feature intent. Includes fasttrack mode for pre-approved specs. NOT for explicit user-invoked single tasks (see mk:cook); NOT for green-field autonomous builds (see mk:autobuild); NOT for simple bug fixes (see mk:fix).
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Automatically detect user intent and route to appropriate agent
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Orchestrates `impeccable` for every design task inside a workflow phase. Captures intent in natural language, classifies it (design / development / copy), translates design intents into a sequence of impeccable subcommand invocations, runs them in main context with state persistence at `.claude/state/design/<slug>.json`, and returns a structured report. ALWAYS invokes `impeccable` under the hood for the underlying design move; never picks aesthetic direction itself; never writes product code directly. Per CLAUDE.md Article X.2, all design tasks in workflow phases route through this skill.
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Improves typography by fixing font choices, hierarchy, sizing, weight, and readability so text feels intentional. Use when the user mentions fonts, type, readability, text hierarchy, sizing looks off, or wants more polished, intentional typography.
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Enforce traceability from natural-language intent to machine predicates, final observables, evidence, and owner-readable acceptance. Use when conducting any audit, review, QA pass, parity or compliance check, security assessment, code or architecture review, visual or behavioral comparison, data validation, system verification, completion gate, or claim that an implementation satisfies a human request.
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ユーザーが言語化できない「何を入力し、何をどう出力してほしいか」を深掘って intent_contract と 5 軸ヒアリングシートを再現性高く埋めたいとき、run-skill-intake から phase 4 として呼ばれて sheet.md/sheet.json/interview.json を生成したいときに使う。
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Use before build, fix, debug, review, or docs implementation; converts prompts into structured intent JSON with goal, constraints, and routing.
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Improves typography by fixing font choices, hierarchy, sizing, weight, and readability so text feels intentional. Use when the user mentions fonts, type, readability, text hierarchy, sizing looks off, or wants more polished, intentional typography.
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Improves typography by fixing font choices, hierarchy, sizing, weight, and readability so text feels intentional. Use when the user mentions fonts, type, readability, text hierarchy, sizing looks off, or wants more polished, intentional typography.
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Stripe CLI の `stripe fixtures` コマンドで実行可能な fixture JSON を、対話的に整理しながら生成・検証する。test_clock を使った時間進行、サブスクのライフサイクル、失敗カードでの payment_intent 失敗、Connect 配下の Destination charge、bulk 件数のテスト顧客作成など、複数ステップの API リクエスト連鎖を扱う。「Stripe の fixture を書いて」「fixtures.json を作って」「このシナリオを fixture 化」「テストデータを大量に作りたい」「サブスクの月次失敗をテストしたい」「stripe trigger と fixture どっち使う」のような依頼で起動する。"fixture" という単語が無くても、複数ステップの Stripe テストデータ準備、 test clock を使った時間進行、 bulk なテスト顧客作成、 失敗パターンの再現といった意図が見えたら起動する。単発 API 呼び出しが目的なら起動せずに `stripe trigger` か API 1コールを案内する。
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ヒアリング駆動でデザイン仕様書（DESIGN.md）を作るスキル。 「コーポレートサイト作りたい」「LP のデザイン考えて」「ポートフォリオの世界観決めたい」 「ファンタジーゲームみたいな公式サイト作りたい」など、用途・雰囲気・世界観の相談時に使用。 静的 HTML クイズで意図を抽出し、Intent / Colors / Typography / Animations を含む DESIGN.md を生成。 既存 DESIGN.md からの HTML モック生成や、URL からの抽出には使用しない（後者は design-extractor の役割）。
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Given the product and the existing page inventory, identify missing blog topics and generate new blog posts that capture search/AI intent using the query-fanout pattern. Use this skill whenever the user asks to "spawn blogs", "generate blog posts", "expand the blog", "build out a content cluster", "write blog ideas", "cover more search intents", "query fanout for blogs", or wants new long-form content that supports existing pillars. Output is one new post per topic in the project's existing post format (markdown, MDX, component, or CMS migration note), with frontmatter shape mirrored from an existing post.
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Account-based marketing for B2B SaaS. Use this skill to build a target account list, tier it 1:1 / 1:few / 1:many, size it against sales capacity, turn intent and engagement signals into plays, write the multi-channel orchestration contract each tier runs on, and measure the program in account coverage, penetration and pipeline instead of MQLs. Also triggers on: ABM, account-based marketing, target account list, TAL, named accounts, account tiering, 1:1 ABM, one-to-few, programmatic ABM, account selection, ideal customer profile fit, intent data, buying signals, 6sense, Bombora, Demandbase, account penetration, account coverage, sales and marketing alignment on accounts, enterprise account program.
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River Review のメインエントリポイント。 レビュー依頼の intent classification → 専門 skill 選択 → 実行 → finding verification → feedback classification → fixture / reference / suppression への還元までを束ねる improvement-loop orchestrator。
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