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Artificial Intelligence

Artificial Intelligence skills

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Machine Learning Generative AI Computer Vision MLOps Language & Speech AI Agents Responsible AI Robotics

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556 skills

grab-my-files

Bundle every file the agent produced in this session into a single timestamped .zip and hand it back as a download. Use when the user asks to "export all produced files", "zip my files", "package everything you made", "bundle my files", "give me all the files", or similar. Files are read from /app/created/. Do NOT use to fetch a single named file the user can already download on its own, to create or convert a file, or to save/persist files to SharePoint, OneDrive, or Dataverse — those are separate flows, not a local zip-and-download.

enterprise-agent-design-authority

Use this skill whenever the user asks to review, assess, validate, improve, govern, or prepare a Microsoft Copilot Studio agent, multi-agent solution, or enterprise AI architecture before implementation. Apply an enterprise architecture assessment before proposing implementation or design changes.

create-copilot-adoption-dashboard

Turns the four Microsoft admin center (MAC) Copilot activity exports into a populated, single-file HTML adoption dashboard using the Copilot Adoption Analysis framework (Pillars A–E and the KPI scorecard). Triggered by the `create-copilot-adoption-dashboard` command. Use when the user asks to "create a Copilot adoption dashboard", "populate the adoption dashboard template", "build my MAC report dashboard", "generate a Copilot usage dashboard", "turn my Copilot exports into a dashboard", or "make an adoption at-a-glance report". It first explains the process, then collects a company name (requi

copilot-studio-topic-blueprint

Use this skill whenever the user describes a Copilot Studio agent in a sentence or two and wants a build-ready blueprint, or asks how to design, scope, or structure an agent (its type, topics, tools, knowledge, or welcome experience). Trigger on requests like "design a Copilot Studio agent that…", "turn this use case into an agent", "how should I structure this agent", or a pasted one-line use case. Do NOT trigger for testing an existing agent (that is the test-planner skill) or for generic Power Platform flows unrelated to an agent.

copilot-studio-harness-picker

Assess business, experience, channel, identity, orchestration, governance, maturity, and cost requirements to recommend the right Microsoft Copilot Studio harness: GitHub Copilot, standard, or Copilot chat. Use when asked which harness to choose, what to build something with, agent versus workflow, classic versus new experience, whether to migrate or rebuild an existing agent, multi-channel architecture, licensing or Copilot Credit estimates, or whether a Microsoft platform outside Copilot Studio fits better. Supports Quick and Detailed modes and produces an evidence-labelled Harness Decision

copilot-studio-agent-test

Test Microsoft Copilot Studio agents programmatically against a set of question/answer pairs, without driving a browser. Use when the user wants to evaluate, test, validate, benchmark or regression-test a Copilot Studio agent; run an eval set or test set against an agent; check whether an agent answers correctly from its knowledge bases; verify agent grounding or citations; or ask a Copilot Studio agent a question from the command line. Triggers include 'test my Copilot Studio agent', 'run an eval against the agent', 'validate agent answers', 'check the agent knowledge base', 'ask the agent',

copilot-agent-advisor

Recommends which Microsoft 365 / Copilot Studio agent option fits a described scenario — using Microsoft 365 Copilot as-is, building a standard (declarative) agent, or building a custom (custom engine) agent — and which Copilot Studio harness to build on (GitHub Copilot, standard, or Copilot chat). Use when the user asks "which agent type should I build", "declarative vs custom engine agent", "standard agent or custom agent", "should I use Copilot Studio or Microsoft 365 Copilot", "which Copilot Studio harness", "help me choose a Copilot agent", or describes an agent scenario and wants a recom

clipchamp-video

Create narrated demo/explainer videos of a live web app or agent, with real screen-flow footage under an AI (Ava neural) voiceover. Use whenever the user wants to "make a video", "record a demo", "create a walkthrough", "screen record an agent/app and narrate it", "build a Clipchamp video", "produce a product demo", or turn a Copilot Studio / web-app flow into a narrated MP4. FIRST ask the user which assembly method to use: (A) headless ffmpeg + edge-tts Ava — fast, scripted, produces a finished MP4 directly — or (B) the Clipchamp web UI — slower, but leaves an editable Clipchamp project for h

ai-usecase-assessment

Use this skill whenever the user says "assess this use case", "score my AI use case", "prioritise these agent ideas", "generate a use case assessment report", or "update my AI use case report" — or when they attach a use-case document, SDR, or prior `*_AI_UseCase_Assessment_Report_*.html` and ask you to assess, strengthen, score, or refresh it. Invoke BEFORE writing any assessment content and BEFORE generating any report.

agent-red-team

Run an adversarial assurance review of a Microsoft Copilot Studio agent you own — generate and execute test cases for indirect prompt injection, oversharing and authorization bypass, data leakage, scope escape and tool misuse — then score the findings and map each one to a concrete Copilot Studio control. Use when someone asks to red team, pen test, adversarially test, jailbreak-test or security-review an agent, wants a prompt injection or data leakage assessment before go-live, or needs security sign-off and a risk report for an agent handling sensitive data.

agent-performance-triage

Diagnose a live Microsoft Copilot Studio agent from its analytics and transcripts, find why it is underperforming, and produce a prioritized improvement backlog tied to specific topics, knowledge sources and tools. Use when an agent is already in production and someone asks why resolution or engagement is low, why users escalate or abandon, what the top unanswered questions are, how to improve an agent's containment or CSAT, or wants a post-launch review, health check or optimization sprint for a deployed agent.

agent-harness-explorer

Use this skill whenever the user wants to inspect, understand, snapshot, compare, or document the capabilities of the current agent harness — for example "what can this harness do?", "which Python libraries are installed?", "what should I use to create Word documents?", "capture/remember a snapshot", "compare with my baseline", or "what changed since last week?". Prefer this skill BEFORE guessing what the runtime supports.

agent-evaluation-designer

Use this skill whenever the user wants to evaluate, test, or validate an AI agent, decide whether an agent is ready to ship or go live, choose how to grade an agent's answers (exact match, similarity, meaning, keywords, quality, or custom), design a test set of questions and expected answers, or interpret evaluation results into a go/no-go decision. Invoke it before the user hand-builds tests or declares an agent "done."

my-great-skill

The AGENT-facing description. This is what the model reads to decide WHEN to invoke the skill, so describe the trigger precisely (e.g. "Use this skill whenever the user asks to … BEFORE calling …"). Keep it action-oriented.

microsoft-build

Your companion for Microsoft Build 2026. Helps you find sessions relevant to your project, discover what's new for your tech stack, scaffold projects from sessions, and plan your event schedule. Activate when users mention sessions, schedule, what's new, Build, Ignite, AI Tour, Microsoft event, conference, or reference a session code (BRK, DEM, LAB, KEY). Also supports Ignite 2025 and Build 2025 session catalogs. Uses the msevents CLI for fast local search and Learn MCP Server for docs.

azuresql-db-rag

Builds local vector search, RAG, embeddings, and semantic search on the Azure SQL Database container using the native VECTOR type and VECTOR_DISTANCE. Use when you need to store embeddings, do similarity search, top-k nearest neighbor, cosine distance, retrieval-augmented generation, "find similar documents", chatbot memory, or semantic lookup against a local SQL database. Use this instead of pgvector, FAISS, Chroma, Pinecone, or a separate vector store when the data already lives in (or can live in) Azure SQL. Covers the VECTOR(n) column type, inserting embeddings with CAST(CAST(? AS NVARCHAR

LLM Applications

finetuning

Fine-tune models on Microsoft Foundry using SFT (supervised), DPO (preference), or RFT (reinforcement with graders). Covers dataset preparation, training job submission, deployment, and evaluation. USE FOR: fine-tune, SFT, DPO, RFT, training data, grader, distillation, fine-tuned model, training job, large file upload, calibrate grader, deploy fine-tuned model, evaluate fine-tuned model. DO NOT USE FOR: general model deployment without fine-tuning (use deploy-model), agent creation (use agents), prompt optimization without training (use prompt-optimizer).

Model Adaptation

vscode-extension

Use when investigating, developing, debugging, testing, or reviewing Aspire VS Code extension behavior under extension/, including extension UI, command, debugger, RPC, DCP, MCP, and CLI-integration issues or features.

connection-properties

Specialized agent for creating and improving Connection Properties in Aspire resource and README files

shepherd-driver

Use only as the composed drive-to-merge stage of an APM batch orchestrator (batch-bug-shepherd, apm-issue-autopilot) that has already selected ONE open pull request in microsoft/apm. Do NOT use for user-facing requests to triage issues, sweep a queue, or open PRs -- the parent orchestrator owns those. Spawn one shepherd-driver subagent per PR: it classifies copilot-pull-request-reviewer[bot] inline review, runs the apm-review-panel, folds (by default) every recommendation inside the PR's stated scope, pushes to the head branch or a superseding PR that preserves authorship via commit trailers,

pr-description-skill

Use this skill to write the PR description (PR body) for any pull request opened against microsoft/apm. Produces one self-sufficient GitHub-Flavored Markdown artifact: TL;DR, Problem (WHY), Approach (WHAT), Implementation (HOW), 1-3 validated mermaid diagrams, explicit trade-offs, validation evidence, and a How-to-test section -- with every WHY-claim backed by a verbatim quote from PROSE or Agent Skills. Activate when the user asks to "write a PR description", "draft a PR body", "open a PR", "fill in the PR template", or any equivalent.

apm-usage

Activate when the user asks about APM (Agent Package Manager): installing, configuring, authoring, or troubleshooting AI-agent packages, dependencies, compilation, MCP servers, policy, or any `apm` CLI command.

docs-impact-classifier

Use this skill to classify the documentation impact of a pull request diff, returning one of three verdicts -- no-change, in-place edit, or structural change -- with bounded LLM cost. Activate as a sibling skill of docs-sync; the orchestrator calls this first, before any panel spawn, to keep cost floor at 1 LLM call when no docs work is needed. Reads .apm/docs-index.yml as the corpus map; never reads the full corpus.

docs-corpus-audit

Use this skill to run a holistic regrounding pass on the entire microsoft/apm documentation corpus against current source code, page-by-page, and emit surgical fixes for stale claims. Activate when the maintainer wants a WHOLE-CORPUS audit (not per-PR review) -- typical triggers include "audit the docs", "reground the corpus", "check every page against code", "pre-release docs sweep", "the docs have drifted everywhere", or "we just reshaped the TOC, find dead links". Wave-batched and S7-verified; scales to the full ~112-page corpus in ~10 minutes wall-time. This is a SIBLING to docs-sync, not

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