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Build a competitive or casual trading card game deck. Covers archetype selection, mana/energy curve analysis, win condition identification, meta-game positioning, and sideboard construction for Pokemon TCG, Magic: The Gathering, Flesh and Blood, and other TCGs. Use when building a new deck for a tournament format or casual play, adapting an existing deck to a changed meta-game, evaluating whether a new set warrants a deck change, or converting a deck concept into a tournament-ready list.

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Select an OCR/HTR engine by benchmarking candidates on the same labelled samples — source ground truth from open datasets (e.g. Hugging Face PAGE-XML corpora) or hand-transcription, wrap every engine behind a transcribe(image_path) -> str adapter (vision-LLMs via any OpenAI-compatible endpoint, dedicated HTR REST APIs, cloud OCR), and score with zero-dependency raw CER, lenient CER, WER, and a critical name/date token diff. Use when choosing an engine for handwriting or historical-document transcription, when published accuracy claims need honest verification on your own material, or when a records workflow must surface confident-but-wrong names and dates that a low aggregate CER hides.

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AI relational calibration — reading and adapting to the specific person you are working with. Goes beyond user-intent alignment (solving the right problem) to genuine attunement (meeting the person where they are). Maps communication style, expertise depth, emotional register, and implicit preferences from conversational evidence. Use at the start of a new session, when communication feels mismatched, after receiving unexpected feedback, or when transitioning between very different users or contexts.

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Issue Greek invoices through AADE's timologio, get the MARK, keep one JSON per invoice, push it into the ERP (SAP Business One today; other adapters welcome) and email the PDF. Trigger on: τιμολόγιο, τιμολόγησε, έκδοση τιμολογίου, invoice, myDATA, timologio, MARK, ΤΠΥ, πελάτης ΑΦΜ, προεπισκόπηση τιμολογίου.

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Use when writing, reviewing, or refactoring Rust code. Routes the task to handbook chapters on idioms, lints, errors, testing, generics, and pointers under the edition 2024 and current-stable pins.

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Use when onboarding to a repository, capturing costly conventions, constraints, or rationale, or improving AGENTS.md. Not for remote, credential, publish, deploy, or irreversible changes.

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Transfer reusable prevention lessons from another AI Factory project into the current project's skill-context through $aif-evolve. Use when building a similar project and you want to avoid problems already captured in another project's patches without copying or revealing that project's identity, paths, or identifiers.

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Implement or revise one governed Proto UI Host Capability connecting a semantic Module to a bounded host responsibility. Use when capability identity, portable need, public shape, availability, failure, replacement, cleanup, fidelity, Adapter realization, and evidence are fixed by current authority.

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Implement or extend one governed Proto UI Module semantic slice. Use when Module ownership, facade and port boundary, dependencies, resource lifetime, Host Capability plan, Runtime registration, Adapter evidence, and validation scope are fixed by current authority. Do not use to admit a new Module or decide ownership.

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Investigate a bounded Proto UI Contract, Prototype, Module, Host Capability, Adapter, schema, or ownership question and turn a genuinely unresolved direction into one semantic decision packet. Use for spec brainstorming, admission questions, competing semantic models, uncataloged behavior, or unresolved cross-layer boundaries.

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Route ordinary Proto UI development through a minimal composition of repository skills. Use when starting, continuing, or handing off feature, fix, spec, contract, Module, Host Capability, Adapter, Prototype, component, test, documentation, review, or release-preparation work. Do not use for autonomous-maintenance runs; use pui-maintain.

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Create or revise a governed Proto UI spec entity after identity, ownership, lifecycle intent, semantic scope, relations, and evidence plan are fixed by current authority. Use for Contract, Prototype, Module, Adapter profile, Decision, Host Capability, Test, Version, or Knowledge entity work. Do not use to decide an unresolved admission or lifecycle promotion.

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Reproduce and repair a bounded Proto UI regression whose expected behavior and owning layer are already governed. Use this before domain implementation skills whenever work starts from a reproducible failure, including bug fixes, drift repairs, broken exports, Runtime failures, Adapter parity defects, Prototype defects, or public-projection regressions. Do not use when expected semantics or ownership is unresolved.

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Use when concrete Odylith failure evidence needs a Casebook bug with grounded repro details.

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Enter explore mode to investigate ideas, systems, problems, and requirements before planning. Use explicit ultra mode when the user wants a durable adaptive research bundle with an index and only the justified C4, ADR, or dependency artifacts.

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Diagnose React + Three.js (or any browser canvas) frame stutter by capturing a CDP CPU profile via Playwright instead of guessing from `[perf]` console logs. Use when: (1) frame time is bad but `[perf]` instrumentation doesn't pinpoint the offender, (2) you've spent more than ~30 minutes "fixing" suspects without measuring, (3) hot paths involve animation systems, allocation bursts, or invisible scene-graph traversal, (4) you need self-time per function with line numbers, not aggregate "render slow". The `console.warn` pattern is good for monitoring; CDP is needed for diagnosis. Covers script template, sourcemap setup so minified function names are decoded, and interactive variant where the user drives the interaction and signals stop via `touch /tmp/<flag>`.

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This skill should be used when the user asks to "explore the app", "/qa", "auto-test the app", "find bugs in my app", "猴子测试", "自动探索", "随便点一下看看", "测一下全 app 看有没有崩", "smoke explore", or wants autonomous exploration of an Android or iOS app to surface crashes / ANRs / unexpected states. Drives the app via ui-mcp + mobile-mcp, tracks visited pages and clicked elements via report-mcp's state graph, captures crashes via log-mcp, and produces a Markdown report with bug list + coverage stats.

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。

This skill should be used when the user asks to "test what I just changed", "/devtest", "smoke test my change", "verify my latest commit", "测一下我刚改的", "看看刚改的功能能不能跑", "跑一下登录看看", or similar requests to verify a recent code change against a running Android or iOS device. The skill reads the git diff, infers the affected UI surface, generates a focused test plan, drives the app via ui-mcp + mobile-mcp, captures logs via log-mcp, and produces a Markdown report via report-mcp.

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。

Create polished audio content and save to Spotify. Produces episodes with TTS narration, a rich timeline (chapters plus in-player images, external links, and Spotify entity cards), and a cover image. Also use for raw media saves, show/episode management, and timeline navigation.

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Use when researching Claude Code or Codex upstream releases, selecting adaptations, or preparing Harness upgrades. Local-only; not for distribution.

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Before any multi-step work with a stated goal — a feature, a bugfix spanning multiple files, a QA sweep, a doc draft + iterations, a multi-day investigation — create an ATO Mission instead of doing it via bare `ato dispatch` calls. A Mission persists the goal + the verifiable success criteria, lets the coordinator tick drive the work across days, captures every event in a structured audit trail (SQLite + markdown narrative), and integrates parallel agents' work via merge strategies. Complement to `ato-warroom` (the cross-family decision before you start) and `ato-review` (the post-code-diff review). Missions is where multi-step work LIVES; war-rooms are where decisions ABOUT it get made; reviews are where the resulting commits get vetted. Fires when: the work has more than one decision point, a verifiable end state, or runs across more than one session. Use it for any ATO development that doesn't fit in a single dispatch.

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改修後の動作確認を、AIが自分で環境を立てて最後まで進めるための検証スキル。CLI（curl / php evo / DB）を優先し、画面操作でしか判定できないときだけ Playwright（既定はヘッドレス）に切り替える。Docker の検証環境の起動、インストール、テスト用ユーザー作成、mailpit でのメール確認、main との比較、後片付けまでを扱う。「動作確認」「自走で確認」「実環境で確かめる」「ブラウザで確認」「再現を確認」「Playwright」と依頼されたとき、または修正のあとに実機での裏付けが必要なときに使う。

Map a confirmed platform-neutral website Design System to a local Elementor Site Settings and Widget inheritance contract. Use for a new or rebuilt Elementor site that needs Global Style setup guidance, or an existing site that must preserve its current visual system. Do not redesign the site, implement Widgets, or modify WordPress, Elementor, themes, or remote data.

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Create branded 试界TryWorld AI-knowledge videos in the fixed "Paper Algorithm" (纸上算法) style with HyperFrames. Input is a Chinese voiceover script and optional images; output is a 16:9 horizontal video with Azure YunxiNeural (真·云希) voiceover, word-synced captions, ink/paper animations and unified transitions, an always-visible anti-counterfeit red seal, plus horizontal (4:3) and vertical (3:4) cover images and platform-optimized titles for Bilibili/Douyin/Xiaohongshu. Brand values are theme-driven (themes/paper-algorithm.json by default; custom brand themes supported — see references/theme-guide.md). Use when the user provides an AI 科普/教程/内容解读/知识分享 script and wants a TryWorld/试界 branded video, asks for the 纸上算法/Paper Algorithm style, wants a consistent script-to-video pipeline with covers and titles, or wants this pipeline with their own brand theme.

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。