Mouad Jaouhari

Official GSAP — ScrollTrigger — scroll-linked animations, pinning, scrub, triggers

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Official GSAP skill for gsap.utils — clamp, mapRange, normalize, interpolate, random, snap, toArray, wrap, pipe. Use when the user asks about gsap.utils, clamp, mapRange, random, snap, toArray, wrap, or helper utilities in GSAP.

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Debugs OpenAI Codex CLI and app behavior by navigating the codex-rs codebase (core, tui, exec, cli, app-server): config parsing, tool invocations, prompts, and MCP wiring. Use when Codex behaves unexpectedly or a Codex runtime bug needs tracing to source.

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Creates distinctive, production-grade frontend interfaces by committing to a bold aesthetic direction (purpose, tone, typography, color, motion) before coding. Use when building web pages, components, or apps where the result should not look generic or templated.

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Applies opinionated anti-AI-slop design rules so generated UIs look made, not generated: greenfield pages, audits, redesigns, and design extraction from URLs or screenshots. Use when designing or reviewing a web UI that must avoid templated, generic AI aesthetics.

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Expert-level Windows batch file (.bat/.cmd) skill for writing, debugging, and maintaining CMD scripts. Use when asked to "create a batch file", "write a .bat script", "automate a Windows task", "CMD scripting", "batch automation", "scheduled task script", "Windows shell script", or when working with .bat/.cmd files in the workspace. Covers cmd.exe syntax, environment variables, control flow, string processing, error handling, and integration with system tools.

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Skill for using the command-line tool pdftk (PDFtk Server) for working with PDF files. Use when asked to merge PDFs, split PDFs, rotate pages, encrypt or decrypt PDFs, fill PDF forms, apply watermarks, stamp overlays, extract metadata, burst documents into pages, repair corrupted PDFs, attach or extract files, or perform any PDF manipulation from the command line.

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Creates an integration testing plan for .NET data access artifacts during Oracle-to-PostgreSQL database migrations. Analyzes a single project to identify repositories, DAOs, and service layers that interact with the database, then produces a structured testing plan. Use when planning integration test coverage for a migrated project, identifying which data access methods need tests, or preparing for Oracle-to-PostgreSQL migration validation.

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Runs an 11-step data cleaning and variable screening pipeline for pre-loan credit risk models: sample analysis, OOS split, missing-rate, IV, PSI, and correlation filters. Use when preparing raw credit data for scorecard or default-prediction modeling.

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Explains and designs Microsoft Fabric Lakehouse solutions: Delta tables, the SQL analytics endpoint, shortcuts, and AI functions. Use when building, optimizing, or documenting a Fabric Lakehouse.

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Audits Python + BigQuery pipelines for cost safety, idempotency, and production readiness. Returns a structured report with exact patch locations. Use before deploying or after a cost spike in a Python pipeline that queries BigQuery.

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Use when working with Entity Framework Core — modeling entities and relationships, migrations, LINQ query performance, change tracking, N+1 problems, and connection and transaction handling.

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Generates ideas with named methods from creative practice (SCAMPER, lateral provocations, constraints, pataphysics, and more), routed to the user's situation. Use for open-ended generative or selective requests: "I want to make or start something", "I'm stuck", "inspire me", "make this weirder", "help me pick", or inventing a research question.

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Step-by-step guide for capturing key application requirements for NoSQL use-case and produce Azure Cosmos DB Data NoSQL Model design using best practices and common patterns, artifacts_produced: "cosmosdb_requirements.md" file and "cosmosdb_data_model.md" file. Use when designing a new Azure Cosmos DB for NoSQL data model or reviewing partition keys and document shapes.

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Use when turning GitHub issues or bug reports into reproducible coding-agent repair loops with sandboxed execution, focused tests, patch generation, and regression verification.

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Use when designing or auditing long-term memory for persistent AI agents. Stores immutable source evidence before canonical facts, links beliefs to provenance, applies novelty-aware ADD/UPDATE/NOOP write gating, keeps uncertain merges explicit, separates retrieval from answer generation, supports deletion, and evaluates memory failures layer by layer.

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Writes and reviews dbt projects targeting Snowflake: models, schema.yml metadata, sources, tests, macros, and project structure. Use when building or reviewing dbt models, generating dbt YAML, or applying dbt best practices.

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Generate flat, minimal light/dark-aware SVG diagrams as standalone HTML files, using a unified educational visual language with 9 semantic color ramps, sentence-case typography, and automatic dark mode. Best suited for educational and non-software visuals — physics setups, chemistry mechanisms, math curves, physical objects (aircraft, turbines, smartphones, mechanical watches), anatomy, floor plans, cross-sections, narrative journeys (lifecycle of X, process of Y), hub-spoke system integrations (smart city, IoT), and exploded layer views. If a more specialized skill exists for the subject (dedicated software/cloud architecture, hand-drawn sketches, animated explainers, etc.), prefer that — otherwise this skill can also serve as a general-purpose SVG diagram fallback with a clean educational look. Ships with 15 example diagrams.

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Discovers all projects in a .NET solution, classifies each for Oracle-to-PostgreSQL migration eligibility, and produces a persistent master migration plan. Use at the start of an Oracle-to-PostgreSQL migration of a multi-project .NET solution.

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This skill should be used when the user asks to "offload context to files", "implement dynamic context discovery", "use filesystem for agent memory", "reduce context window bloat", or mentions file-based context management, tool output persistence, agent scratch pads, or just-in-time context loading.

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A persistent, compounding knowledge base combining Karpathy's LLM Wiki pattern with a structured knowledge graph. Ingest documents once — the LLM writes wiki pages, extracts entities/relations into the graph, and stores raw content for evidence retrieval. Knowledge accumulates and cross-references; it is never re-derived from scratch. Use when building a knowledge base from many documents that should accumulate and cross-reference over time instead of being re-read each session.

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Use when designing a new relational schema or auditing an existing one — normalization, keys and constraints, indexing strategy, and spotting modeling problems before they reach production.

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Use when the user asks for deep or academic research — a literature review, PRISMA systematic review or meta-analysis, fact-check, evidence synthesis, APA 7 research report, or Socratic guidance to sharpen a vague research question. Runs a 13-agent pipeline with full, quick, review, lit-review, fact-check, socratic, and systematic-review modes.

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Visual whiteboard collaboration for Copilot CLI. Creates an interactive whiteboard that opens in your browser — draw, sketch, add sticky notes, then share everything back with Copilot. Copilot sees your drawings and text, and responds with analysis, suggestions, and ideas. Use in Copilot CLI when an idea is easier to sketch than to describe in text.

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