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Um coach de busca de empregos que identifica e classifica transparentemente vagas que realmente se encaixam no candidato, salvando buscas recorrentes para novas correspondências. Ele transfere para coaching dedicado para elaboração de candidaturas, preparação de entrevistas e acompanhamento de resultados, sendo invocado para encontrar vagas, monitorar encaixes ou verificar o painel de busca de empregos.

要件やスペックから「あるべきソフトウェア設計」を言語化する。新機能の設計着手時、既存機能の再設計時、仕様の解像度を上げたいときに使う。画面デザイン（UI/UX）は対象外。

Comprehensive reference for LINE Login (OAuth 2.1) — authorization code flow, PKCE, token management, ID token JWT verification, user profiles, bot linking, and login button design. This skill should be used when the user asks to "implement LINE Login", "add Log in with LINE", "set up OAuth authorization flow", "verify an ID token", "refresh an access token", "link a bot to login", "design a login

Research a technical topic and persist findings to the knowledge base

Aplica princípios comprovados de web design para criticar, auditar, melhorar ou construir UI e UX de websites. Ative esta skill sempre que um usuário pedir feedback de design, revisão de UX, crítica de landing page ou ajuda para projetar qualquer interface web.

Consumer audience research and insights using GWI (Global Web Index) data via the gwi_spark_ai MCP server. Use when the user asks about audience demographics, consumer behaviors, media consumption, social media usage, purchase drivers, brand perception, market sizing, audience profiling, competitive audience analysis, trend identification, or any consumer/market research question that can be answe

根據結構化的 AI coding 實作文件（.md）逐步實作程式碼。讀取 prompt.md 大綱， 依序參考技術規格、後端實作指示、前端實作指示，逐步確認後實作後端與前端程式碼。 使用時機：當使用者要求根據已產出的實作文件開始寫程式、實作功能、按照文件 coding、 依文件實作、開始開發時觸發。關鍵字：md to code、根據文件實作、開始寫程式、 按文件 coding、依文件開發、實作程式碼、開始實作、to code、toCode、implement, implementation, 寫程式, coding, 依規格實作, 按規格開發, 從文件產生程式碼, generate code, code generation, 開始開發。

Synthesize user interviews, JTBD analysis, and qualitative data into actionable product insights. Use this skill when a team has raw qualitative data and needs structured insights.

Develop product positioning and messaging that resonates with target segments. Use this skill when a team needs to define how to talk about the product to specific audiences.

Schema.org structured data audit and generation optimized for AI discoverability — detect, validate, and generate JSON-LD markup

Use when writing, reviewing, or modifying property-based tests, such as those using `fast-check`, or when asked to add test coverage.

Use this skill whenever the user wants to build, train, evaluate, or iterate on a supervised machine learning or deep learning model. Triggers include: any mention of training or fitting a model with labeled data, dataset preparation, hyperparameter tuning, cross-validation, model checkpointing, experiment tracking, overfitting, loss curves, metrics, or prediction visualization. Also trigger when