AI & Agents Agent Skills

Turn any rough prompt, half-formed idea, or task description into a finished, ready-to-send prompt optimized for any LLM model inside a chat interface — NOT the API. Use this skill whenever the user wants to write, rewrite, optimize, improve, sharpen, or polish a prompt for chat. Trigger phrases include "rewrite this prompt", "make this a better prompt", "optimize this prompt", "turn this into a prompt", "help me prompt this", "draft a prompt that...", "I want to ask...", or whenever the user pastes a draft prompt and asks for improvements. Also trigger when the user describes a task they plan to send to an LLM model and clearly wants a reusable, well-structured prompt rather than a direct answer. The output is always a single, copy-pasteable prompt in a code block that the user sends as-is — never a template with placeholders.

Build production RAG pipelines and persistent agent memory using Pinecone as the vector database backend. ALWAYS USE THIS SKILL when the user mentions Pinecone, wants to index documents for semantic search, build a retrieval-augmented generation system, store agent memory across sessions, implement hybrid search, or connect an LLM to a searchable knowledge base — even if they don't say "Pinecone" explicitly. Also use when the user asks about vector databases for RAG, namespace isolation for multi-tenant agents, embedding pipelines, or scaling a knowledge base beyond what local storage can handle. DO NOT use for local-only vector stores (Chroma, FAISS, pgvector) or pure keyword search with no semantic component.

Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.

Interactive training for the GitHub Copilot CLI. Guided lessons, quizzes, scenario challenges, and a full reference covering slash commands, shortcuts, modes, agents, skills, MCP, and configuration. Say "cliexpert" to start.

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 this skill any time a .pptx file is involved in any way — as input, output, or both. This includes: creating slide decks, pitch decks, or presentations; reading, parsing, or extracting text from any .pptx file (even if the extracted content will be used elsewhere, like in an email or summary); editing, modifying, or updating existing presentations; combining or splitting slide files; working with templates, layouts, speaker notes, or comments. Trigger whenever the user mentions "deck," "slides," "presentation," or references a .pptx filename, regardless of what they plan to do with the content afterward. If a .pptx file needs to be opened, created, or touched, use this skill.

Draft performance reviews, self-assessments, peer reviews, and upward feedback in your own voice. Analyzes your contributions, emails, and meeting history via WorkIQ, then produces honest, impact-focused drafts using the STAR format. USE FOR: write my performance review, draft self-assessment, peer review, 360 feedback, annual review, mid-year review, upward feedback, write review for colleague, performance appraisal.

OpenInference semantic conventions and instrumentation for Phoenix AI observability. Use when implementing LLM tracing, creating custom spans, or deploying to production.

Systematic Power BI performance troubleshooting prompt for identifying, diagnosing, and resolving performance issues in Power BI models, reports, and queries.

Comprehensive AI prompt engineering safety review and improvement prompt. Analyzes prompts for safety, bias, security vulnerabilities, and effectiveness while providing detailed improvement recommendations with extensive frameworks, testing methodologies, and educational content.

Comprehensive technology-agnostic prompt generator for documenting end-to-end application workflows. Automatically detects project architecture patterns, technology stacks, and data flow patterns to generate detailed implementation blueprints covering entry points, service layers, data access, error handling, and testing approaches across multiple technologies including .NET, Java/Spring, React, and microservices architectures.

Fetches real-time Azure retail pricing using the Azure Retail Prices API (prices.azure.com) and estimates Copilot Studio agent credit consumption. Use when the user asks about the cost of any Azure service, wants to compare SKU prices, needs pricing data for a cost estimate, mentions Azure pricing, Azure costs, Azure billing, or asks about Copilot Studio pricing, Copilot Credits, or agent usage estimation. Covers compute, storage, networking, databases, AI, Copilot Studio, and all other Azure service families.

Workflow for building and modifying content management systems across WordPress, Shopify, Wix, Squarespace, Drupal, WooCommerce, Joomla, HubSpot CMS Hub, Webflow, Adobe Experience Manager, and similar platforms. Use when working on CMS themes, plugins, apps, modules, admin panels, media uploads, content models, editors, markdown pipelines, or static export workflows.

Shuffle repetitive JSON objects safely by validating schema consistency before randomising entries.

Generate a complete Model Context Protocol server project in Swift using the official MCP Swift SDK package.

Draft and review professional emails that match your personal writing style. Analyzes your sent emails for tone, greeting, structure, and sign-off patterns via WorkIQ, then generates context-aware drafts for any recipient. USE FOR: draft email, write email, compose email, reply email, follow-up email, analyze email tone, email style.

Improve AI application with evaluation-driven development. Define eval criteria, instrument the application, build golden datasets, observe and evaluate application runs, analyze results, and produce a concrete action plan for improvements. ALWAYS USE THIS SKILL when the user asks to set up QA, add tests, add evals, evaluate, benchmark, fix wrong behaviors, improve quality, or do quality assurance for any Python project that calls an LLM model.

Finalize prompt file using the role of an AI agent to polish the prompt for the end user.

Merges mature lessons from a domain memory file into its instruction file. Syntax: `/memory-merger >domain [scope]` where scope is `global` (default), `user`, `workspace`, or `ws`.

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.

Route gh-aw workflow design/create/debug/upgrade requests to the right prompts.

When user is asking for guidance for which role to assign to an identity given desired permissions, this agent helps them understand the role that will meet the requirements with least privilege access and how to apply that role.

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

A micro-prompt that reminds the agent that it is an interactive programmer. Works great in Clojure when Copilot has access to the REPL (probably via Backseat Driver). Will work with any system that has a live REPL that the agent can use. Adapt the prompt with any specific reminders in your workflow and/or workspace.