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Validate that a story file is implementation-ready. Checks for embedded GDD requirements, ADR references, engine notes, clear acceptance criteria, and no open design questions. Produces READY / NEEDS WORK / BLOCKED verdict with specific gaps. Use when user says 'is this story ready', 'can I start on this story', 'is story X ready to implement'.

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Verifying YAGNI, cutting scope, and proposing complexity reductions. A 'subtraction' agent questioning the justification for every feature, dependency, doc, and config. Does not write code.

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Product AI Visibility & Ranking — evaluate how AI search engines (ChatGPT, Claude, Gemini, DeepSeek) recommend your product when shoppers ask buying questions. Triggers: AI visibility, product AI ranking, AI recommend, AI search, does AI mention my product.

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Analyze and extract information from images using multimodal AI recognition. Triggered when users want to analyze, describe, or extract information from an image URL — image recognition, image analysis, image description, visual content understanding, OCR text recognition, or visual Q&A. When a user provides an image URL and asks questions about its visual content, this skill should be triggered even if they do not explicitly say "image recognition."

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Design a practitioner inquiry cycle from research question through data collection to evidence-informed action. Use when starting action research, teacher-led investigation, or professional inquiry.

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The learner teaches the concept to the AI, which plays a curious novice peer and identifies gaps through authentic questions. Use when the learner wants to test their understanding — teaching forces a different kind of organisation than studying.

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Design a complete lesson study cycle from research question through collaborative planning to research lesson. Use when planning jugyou kenkyuu or collaborative teacher inquiry into practice.

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Generate retrieval practice questions at varied difficulty levels for a topic or concept. Use when creating quiz starters, revision activities, or low-stakes testing materials.

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Design a sequence where students compare AI's handling of the same question across disciplines, developing a mental model of where AI is reliable vs. distorting based on knowledge type.

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Design a document set for a document-based lesson — selecting and sequencing sources for analytical tension around a central question. Use when assembling sources for a new lesson or when an existing set produces flat responses.

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Generate a coaching conversation guide with questions, protocols, and follow-up actions for a teaching focus. Use when preparing for coaching sessions, mentoring, or peer feedback conversations.

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Generate argument structure scaffolds using Toulmin, PEEL, or CER frameworks for a specific claim or question. Use when teaching argumentative or analytical writing across any subject.

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Check an educational practice or task for cultural bias, WEIRD assumptions, and cross-cultural validity. Use when adapting resources for diverse contexts or questioning universal claims.

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Design a checking-for-understanding protocol with specific techniques for each lesson stage. Use when planning systematic comprehension checks during explicit or direct instruction.

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Forces the laziest solution that actually works, simplest, shortest, most minimal. Channels a senior dev who has seen everything: question whether the task needs to exist at all (YAGNI), reach for the standard library before custom code, native platform features before dependencies, one line before fifty. Supports intensity levels: lite, full (default), ultra. Use whenever the user says "ponytail", "be lazy", "lazy mode", "simplest solution", "minimal solution", "yagni", "do less", or "shortest path", and whenever they complain about over-engineering, bloat, boilerplate, or unnecessary dependencies.

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Extracts what the user actually wants instead of what they think they should want. Achieves this through one-question-at-a-time interview until ~95% confidence about the underlying intent. Use when an ask is underspecified ("build me X" without "for whom" or "why now"), when the user explicitly invokes ("interview me", "grill me", "are we sure?", "stress-test my thinking"), or when you catch yourself silently filling in ambiguous requirements before any plan, spec, or code exists.

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Smithy the Toolsmith builds, converts, reviews, packages, validates and migrates BMad skills, agents and modules. Use when the user wants a skill, agent, persona, command or module made, changed, reviewed or packaged; a prompt or rule from another tool turned into a skill; a skill mined from session logs; an old module migrated; or asks for Smithy. Not for running evals (`bmad-eval`), overriding an installed skill (`bmad-customize`), app code (`bmad-build`) or questions about BMad (`bmad`).

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Answers BMad questions and recommends the next skill from what is installed. Use when the user asks bmad for help, what to do next or where to start; to set up, update, repair, doctor, migrate or check the status of the installation, or add modules; or to see or change the active initiative.

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Test a product concept with Amazon's Working Backwards method: write the press release for the finished product first, then answer hard customer and stakeholder questions, ending in a complete PRFAQ document. Use when the user requests to 'create a PRFAQ', 'work backwards', or 'run the PRFAQ challenge'

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Test a half-formed idea in a questioning conversation, with different personas probing its weak points, until the user can act on it or drop it with confidence. Optionally writes a short brief for planning skills to build on. Use when the user says 'forge an idea', 'pressure-test this idea', 'stress-test my thinking', or 'harden this idea'

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Multi-source research with citations using You.com. Use for questions that need several sources compared and synthesized, such as library or framework comparisons, tool and vendor evaluations, market research, or deep-dive reports. Routes between a cost-conscious agentic search loop and the one-shot `you-research` MCP tool.

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Answer finance and market-data questions with the You.com `you-finance` MCP tool: stock prices, tickers, earnings, company financials, and market trends, with payment-aware fallbacks for keyless hosts.

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Orchestrate evidence-first engineering for WeChat and other mini programs from a vague idea or existing repository through project discovery, product specification, architecture, implementation, debugging, device adaptation, verification, and release readiness. Use when users ask to build a mini program from zero to one, take over an existing mini-program project, deliver a cross-stage feature, diagnose project status, coordinate development and testing, or judge whether a mini program is ready to upload or release. Enforces fact discovery, change boundaries, stage gates, evidence-calibrated status, sensitive-information redaction, and continuity after side questions.

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Analyzes current state and user query to answer BMad questions or recommend the next skill(s) to use. Use when user asks for help, bmad help, what to do next, or what to start with in BMad.

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。