Analyze Azure resource health, diagnose issues from logs and telemetry, and create a remediation plan for identified problems. Use when an Azure resource is unhealthy, slow, or failing and the cause is unknown.
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Manage Azure DevOps resources via CLI including projects, repos, pipelines, builds, pull requests, work items, artifacts, and service endpoints. Use when automating or scripting Azure DevOps from the command line with az devops.
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Validates Azure deployments before they run: Bicep syntax, what-if previews, and permission checks. Use before azd up, azd provision, or az deployment, when preparing or reviewing Bicep files, or to preview what a deployment will change.
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Analyze Azure resources used in the app (IaC files and/or resources in a target rg) and optimize costs - creating GitHub issues for identified optimizations. Use when an Azure bill needs reducing or a resource group needs a cost review.
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Use when raw SaaS numbers need turning into a health verdict — MRR, ARR, churn, CAC, LTV, payback, burn multiple, NRR. Calculates the metrics, benchmarks them against industry standards, and returns prioritized, plain-English advice as a senior SaaS CFO would.
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Instruments a web app to send telemetry to Azure Application Insights: SDK setup, configuration, and telemetry patterns. Use when the user wants to enable monitoring, request tracking, or logging to App Insights for a web application.
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Triggers on keywords M&A, due diligence, post-merger integration, synergy
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Generate a complete TypeSpec declarative agent with instructions, capabilities, and conversation starters for Microsoft 365 Copilot. Use when creating a Microsoft 365 Copilot declarative agent defined in TypeSpec.
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Generates a complete TypeSpec API plugin for Microsoft 365 Copilot that calls external REST APIs, with operations, authentication, and Adaptive Card responses. Use when building a Microsoft 365 Copilot API plugin with TypeSpec.
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Coaches founders and CEOs on their own development: leadership archetype, delegation, blind spots, and the decisions that change as the company scales. Use when a founder is the bottleneck, struggles to delegate, or is outgrowing their current way of leading.
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Add GET, POST, PATCH, and DELETE operations to a TypeSpec API plugin with proper routing, parameters, and adaptive cards. Use when extending an existing Microsoft 365 Copilot TypeSpec API plugin with new REST operations.
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Process media files (video, audio, images, documents) using Transloadit. Use when asked to encode video to HLS/MP4, generate thumbnails, resize or watermark images, extract audio, concatenate clips, add subtitles, OCR documents, or run any media processing pipeline. Covers 86+ processing robots for file transformation at scale.
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Generate or edit images via OpenRouter with the Gemini 3 Pro Image model. Use for prompt-only image generation, image edits, and multi-image compositing; supports 1K/2K/4K output.
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Use when improving, evolving, benchmarking, or maintaining agent skills over time. Treats skills as long-lived structured artifacts: execute tasks, diagnose trajectory evidence, accumulate textual momentum, patch at the correct abstraction layer, test per model and harness, canary changes, and roll back regressions.
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Create, update, refactor, explain, or review Semantic Kernel solutions using shared guidance plus language-specific references for .NET and Python. Use when working on applications, plugins, or function-calling flows built on Semantic Kernel.
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Use when comparing basic, enhanced, GraphRAG, or agentic RAG designs, evaluating domain-specific RAG quality, tuning retrieval components, or deciding whether agentic RAG is worth its cost.
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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`. Use when a domain memory file has accumulated lessons that should become permanent instructions.
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Use when designing evaluation suites for agentic systems, choosing agent benchmarks, measuring multi-agent performance, or critiquing single-score evaluation of agents. Based on arXiv:2605.26112v1. Trigger phrases: "evaluate my agent", "benchmark agent", "measure agent reliability", "pass^k evaluation", "agent metrics beyond success rate", "trajectory quality", "memory hygiene metric", "longitudinal agent eval", "why my agent scores well on benchmarks but fails in production".
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Use when diagnosing agent benchmarks or runtime failures from trajectories instead of aggregate pass rates. Builds shared action-observation decision landscapes, identifies productive cores and trap regions, profiles Access/Trap/Repair behavior, and designs conservative trap-triggered recovery experiments.
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This skill should be used when the user asks to "share memory between agents", "KV cache compaction for multi-agent", "orchestrator worker context", "latent briefing", "reduce worker tokens", "cross-agent memory without summarization", or discusses Attention Matching compaction, recursive language models with workers, or token explosion in hierarchical agents.
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Use when designing long-horizon agents that need subagents, isolated context windows, filesystem-backed work, persistence, human approval, MCP tools, or production tracing.
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Also use for agentic data engineering pipelines, code generation agents, agent-powered CLI tools, MCP server development, or any system where an AI model calls tools, makes decisions, or loops
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Triggers on keywords RAG, GraphRAG, vector database, agentic RAG, semantic search
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Verify supply chain integrity for AI agent plugins, tools, and dependencies. Use this skill when: - Generating SHA-256 integrity manifests for agent plugins or tool packages - Verifying that installed plugins match their published manifests - Detecting tampered, modified, or untracked files in agent tool directories - Auditing dependency pinning and version policies for agent components - Building provenance chains for agent plugin promotion (dev → staging → production) - Any request like "verify plugin integrity", "generate manifest", "check supply chain", or "sign this plugin"
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