fabric-discover Skill

Source

• Creator: microsoft
• Repository: microsoft/fabric-task-flows
• Skill file: .github/skills/fabric-discover/SKILL.md

What it does

Collects intake (project name + problem statement), scaffolds the project, infers architectural signals, and produces a Discovery Brief. This is the DEFAULT first skill — invoke it for ANY new user request that describes a data, analytics, reporting, or integration problem, no matter how it is phrased. The signal mappe

Skill instructions

Fabric Discovery Instructions Step 1: Collect Intake If the problem statement and project name are already provided (e.g., from auto-chain), use them directly — do NOT re-ask. Otherwise, ask the user for: - Project name — short, creative, descriptive. You MAY suggest examples, but MUST NOT proceed until the user explicitly confirms one. - Problem statement — "What problems does your project need to solve?" Step 2: Scaffold and Review Signals bash python shared/scripts/run-pipeline.py start "Project Name" --problem "problem statement text" The start command runs signal-mapper.py as pre-compute — review its output above. Do NOT run signal-mapper.py again manually. Step 2b: Run the Semantic Capability Mapper The lexical signal mapper handles vocabulary; the capability mapper handles intent → required Fabric items. It catches what users mean even when they don't use the literal keywords (e.g., "mountain of data to put in data scientists' hands" → Notebook + Lakehouse). bash python .github/