Set up a machine for Dataverse development — install tools and authenticate. USE WHEN: "install PAC CLI", "install tools", "command not found", "authenticate", "pac auth", "az login", "gh auth", "winget install", "setup machine", "missing tools", "new machine setup". DO NOT USE WHEN: initializing a workspace/repo (use dataverse-init).
Create or modify Dataverse tables, columns, relationships, forms, and views. USE WHEN: "add column", "create table", "add relationship", "lookup column", "create form", "create view", "modify form", "FormXml", "SavedQuery", "option set", "picklist", "MetadataService", "EntityDefinitions". DO NOT USE WHEN: reading/writing data records (use dataverse-python-sdk), exporting solutions (use dataverse-solution).
Identifies accounts showing warning signs of churn by analyzing activity trends, support cases, and engagement signals. Scores risk and prioritizes intervention targets. Use when user asks "which accounts are at risk", "churn risk analysis", "find accounts that might leave", "customer health check", "at-risk customers", "retention warning signs", or "account health score".
Generates a weighted sales forecast from Dataverse opportunity data. Calculates committed, best-case, and pipeline views by rep and team; compares to quota; flags risks and upside. Use when user asks "what's my forecast", "quarterly forecast", "pipeline forecast", "where's my number", "forecast report", "am I going to hit quota", "sales projection", or "revenue forecast".
Create, export, unpack, pack, import, and validate Dataverse solutions. USE WHEN: "export solution", "import solution", "pack solution", "unpack solution", "create solution", "pull from environment", "push to environment", "validate import", "check import errors", "check if table exists", "check if form is published", "verify deployment". DO NOT USE WHEN: creating tables/columns/forms/views (use dataverse-metadata).
ALWAYS LOAD THIS SKILL FIRST for any Dataverse task. Contains hard rules that override all other skills. USE WHEN: ANY request involving Dataverse, Dynamics 365, Power Platform, tables, columns, solutions, records, queries, CRM, metadata, plugins, SDK, Web API, PAC CLI, or environment operations. Also use for: "how do I", "what tool", "which skill", "where do I start", "help with Dataverse", "create table", "create column", "build solution", "query data", "bulk import", "sample data", "support agent", "customer table", "ticket table". This skill MUST be loaded before any other Dataverse skill. Read the Hard Rules section first.
Generates customized sales assets including one-pagers, proposals, executive summaries, ROI summaries, and mutual action plans from Dataverse context. Use when user says "create a one-pager", "draft a proposal", "generate executive summary", "build ROI summary", "create mutual action plan", "sales asset for [account]", "proposal outline", or "customer-facing document".
Configure an MCP server for GitHub Copilot or Claude with your Dataverse environment. USE WHEN: "configure MCP", "set up MCP server", "MCP not working", "connect MCP to Dataverse", "add Dataverse to Copilot", "add Dataverse to Claude", "connect via MCP", "use MCP", "MCP tools not available", "no MCP tools", "MCP not configured". DO NOT USE WHEN: workspace not initialized (use dataverse-init first), installing tools (use dataverse-setup).
Submit a feature suggestion conversationally — Claude gathers details, previews, and creates a GitHub issue via gh CLI.
Reviews opportunities in the sales pipeline to identify stuck deals, missing next steps, weak qualification, and unbalanced stages. Use when user asks "how is my pipeline looking", "analyze pipeline health", "which deals are stuck", "pipeline review", "find at-risk deals", "identify stalled opportunities", or "audit my open deals".
Generate reports from brief.json on demand — without running a build. Four report types for different audiences: brief (design state), build (status + deviations), customer (simplified, zero jargon), deployment (checklists + env mapping).
Generates personalized outreach messages by pulling context from Dataverse records. Creates tailored emails for new prospects, re-engagement, follow-ups, or cross-sell. Use when user says "draft an email to [contact]", "write outreach for", "help me reach out to", "compose email", "re-engage this contact", "follow-up email", "prospecting email", or "outreach message for".
Browse, analyze, and contribute to the team's SharePoint solution library. Uses agent teams for intelligent tagging and pattern extraction.
Post-deployment fix: analyze eval set failures, classify root causes, apply targeted fixes, and re-evaluate. For initial build iteration, use /mcs-build (which has an internal fix loop). This skill handles post-deployment edge cases and regressions.
Analyzes closed opportunities to identify patterns between won and lost deals. Compares sales cycles, activities, stakeholder engagement, and deal characteristics for actionable playbook insights. Use when user asks "why are we losing deals", "win loss analysis", "what makes deals win", "analyze lost opportunities", "sales pattern analysis", "compare won vs lost deals", or "improve win rate".
Guides sales reps through structured lead qualification using BANT+ methodology. Evaluates leads, suggests discovery questions, scores quality, and recommends next steps. Use when user says "qualify this lead", "help me qualify", "BANT analysis", "score this lead", "should I convert this lead", "lead qualification questions", or "assess lead quality".
Run evaluation tests using eval sets. Two-mode execution: Direct Line API (auto) or MCS Native Eval via Gateway API upload + run (manual). Results written per-test to evalSets[].tests[].lastResult.
Build agent(s) in Copilot Studio using the fully API-native build stack with user-guided manual steps for OAuth connections. Reads brief.json for architecture mode (single/multi-agent).
Generates meeting briefings by aggregating account info, contacts, opportunities, cases, and activity history into structured prep documents with talking points and discovery questions. Use when user says "prep me for my call", "brief me on this account", "meeting prep", "I have a meeting with [company]", "account briefing", "customer briefing", or "prepare for customer meeting".
Use the official Microsoft Dataverse Python SDK for data operations. USE WHEN: "use the SDK", "query records", "create records", "bulk operations", "upsert", "Python script for Dataverse", "read data", "write data", "upload file", "bulk import", "CSV import", "load data", "data profiling", "data quality", "analyze data", "Jupyter notebook", "pandas", "notebook". DO NOT USE WHEN: creating forms/views (use dataverse-metadata with Web API), exporting solutions (use dataverse-solution with PAC CLI).