Use after implementing features - verifies each acceptance criterion with structured testing and posts verification reports to the GitHub issue
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Use after implementing features - verifies each acceptance criterion with structured testing and posts verification reports to the GitHub issue
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Transform academic course assignment PDFs into structured, actionable markdown checklists with dates, unique IDs, and custom tags. Asks when the user will start, assigns tasks only to weekdays (Monday-Friday), respects weekends automatically, and calculates forum deadlines 3 days before due date. Use this skill when the user uploads academic PDFs or asks to create a task plan from course assignments.
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Generates Architecture Decision Records (ADR) for PHP projects. Creates structured decision documentation with context, decision, and consequences.
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When the user needs to set up multiple academic courses in a learning management system (Canvas/LMS) from structured data sources. This skill automates the entire workflow extracting course schedules from emails/attachments, matching instructors from CSV files, creating courses, enrolling teachers, publishing announcements with class details, uploading syllabi, enabling resource sharing for instructors teaching multiple courses, and publishing all courses. Triggers include course schedule setup, Canvas/LMS administration, academic term preparation, instructor assignment, syllabus distribution, and multi-course management.
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When the user requests to create or customize an academic personal website from a GitHub template repository. This skill handles the complete workflow of forking academic template repositories (like academicpages.github.io), extracting structured personal information from memory or provided data, and systematically updating configuration files (_config.yml), navigation menus (_data/navigation.yml), content pages (_pages/about.md), and publication listings (_publications/). It specifically handles academic profiles including personal details, education background, research experience, publications, skills, and contact information. Triggers include requests to 'fork and customize academic homepage', 'build personal academic website', 'create research portfolio', or 'set up GitHub pages with academic template'.
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After-Action Review—structured debrief asking what was expected, what happened, why the difference, and what next. Use after projects, launches, presentations, or any significant event.
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Structured guide for setting up A/B tests with mandatory gates for hypothesis, metrics, and execution readiness.
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Generates a structured skill template based on provided specifications.
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[01] META. Сканирует доступные skills, создает план выполнения и идет шаг за шагом с подтверждением каждого этапа. Triggers on complex tasks, multi-step work, or when structured execution is needed.
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[21] UNDERSTAND. Deep research workflow for this project using 150% scope (100% core + 50% boundary), evidence-based reasoning, and structured investigation notes. Use when the task requires investigation, root-cause analysis, or mapping unknown areas. Always maintain a research log file that captures findings, hypotheses, and next branches; use web.run when external verification is needed.
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Use when you need to apply Java concurrency best practices — including thread safety fundamentals, ExecutorService thread pool management, concurrent design patterns like Producer-Consumer, asynchronous programming with CompletableFuture, immutability and safe publication, deadlock avoidance, virtual threads and structured concurrency, scoped values, backpressure, cancellation discipline, and observability for concurrent systems. Part of the skills-for-java project
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Kotlin Coroutines and Flow patterns for Android and KMP — structured concurrency, Flow operators, StateFlow, error handling, and testing.
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Extract structured domain knowledge from AI models in-session or from local open-source models via Ollama. No API key needed.
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Extract text, tables, and structured data from documents using prebuilt and custom models.
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Azure AI Document Intelligence SDK for .NET. Extract text, tables, and structured data from documents using prebuilt and custom models.
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Actorization converts existing software into reusable serverless applications compatible with the Apify platform. Actors are programs packaged as Docker images that accept well-defined JSON input, perform an action, and optionally produce structured JSON output.
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Fetch any X/Twitter post as clean LLM-friendly JSON. Converts x.com, twitter.com, or adhx.com links into structured data with full article content, author info, and engagement metrics. No scraping or browser required.
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Design spec with 98 rules for building CLI tools that AI agents can safely use. Covers structured JSON output, error handling, input contracts, safety guardrails, exit codes, and agent self-description.
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Structured guide for setting up A/B tests with mandatory gates for hypothesis, metrics, and execution readiness.
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Convert human-written CLAUDE.md into AI-native structured-label format. Battle-tested across 4 models. Same rules, fewer tokens, higher compliance.
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Use this skill for internal maintenance and feature work in the nuxt-ui-tools repository. It explains the repository operating model, exact placement rules, how runtime domains relate, how features should be structured and extended, how consumer skills must be maintained, and what to keep in sync when changing the library.
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Start a new OpenSpec change using the experimental artifact workflow. Use when the user wants to create a new feature, fix, or modification with a structured step-by-step approach.
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Expert AI art prompt engineer for Midjourney and Stable Diffusion. Generates high-quality prompts including unified batch illustrations, marketing designs, interactive compositions, and structured framework prompts with translations.
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Systematically explore and test a web application to find bugs, UX issues, and other problems. Use when asked to "dogfood", "QA", "exploratory test", "find issues", "bug hunt", "test this app/site/platform", or review the quality of a web application. Produces a structured report with full reproduction evidence -- step-by-step screenshots, repro videos, and detailed repro steps for every issue -- so findings can be handed directly to the responsible teams.
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