3102 skills
Design Thinking method coaching knowledge across all nine methods including per-method techniques, deep expertise, and industry context (energy, financial services, healthcare, manufacturing, nonprofit and social impact, pharmaceuticals and life sciences, professional services, public sector, retail and CPG)
Design Thinking learning curriculum covering nine progressive modules across the full Problem, Solution, and Implementation Space methods plus a shared manufacturing reference scenario for teaching and practice
Design Thinking coaching foundation knowledge: coach identity and philosophy, quality and fidelity constraints, method sequencing, coaching state schema, and the canonical deck workflow
Repeatable HVE Core demo setup that simulates DT Coach sessions with a customer persona and scaffolds a hi-fi prototype - Brought to you by microsoft/hve-core
Machine learning experimentation reference for model-experimentation conventions, experiment tracking and reproducibility, dataset and model abstractions, ML engagement fundamentals, and model-production readiness. Use when standing up ML experimentation infrastructure or assessing whether a trained model is ready for production.
Author and validate durable data and ML feasibility studies using the Feasibility Study Interchange Profile, constrained YAML authority, UUID URN identity, lifecycle lineage, and evidence traceability. Use when assessing whether available data and technical evidence support a proposed outcome.
Design evaluation datasets and supporting documentation for AI systems and agents, covering the scoping interview, difficulty distribution, dataset contract, sample review, and metric and tooling selection. Use when building or reviewing an evaluation set for a conversational agent, assistant, or retrieval-grounded AI system.
DataOps and DS/MLOps testing reference for data tiering, Bronze-to-Silver validation placement, pipeline invariants, pytest categories, and validation-versus-drift. Use when designing, reviewing, or generating data pipelines, transformation code, data validation, or data-science test suites.
State, resume, reconstruction, job-lifecycle, transition, and flow-state mechanics for the Data Science and Engineering Coach. Loaded by the coach; not a user entry point.
Create and enrich durable data catalogs using the native DS_CATALOG_V1 Markdown contract, declared entity relationships, privacy citation fields, and stable relationship IDs. Use when inventorying engagement data, recording semantic relationships, or preparing a catalog for ERD rendering.
Authoring conventions for exploratory data analysis notebooks and analytical dashboards, covering section sequence, visualization selection, scale thresholds, caching and state, and dashboard validation budgets. Use when composing or reviewing an EDA notebook, an analytical dashboard, or a dashboard test pass.
Foundational Python best practices, idioms, and code quality fundamentals
Create and validate HVE Core agents, prompts, instructions, and skills with current frontmatter, package membership, delegation, tracking, documentation, and validation conventions. Use when authoring a GitHub Copilot customization artifact in this repository.
Review code changes from multiple perspectives with context bootstrap, depth-tier rigor, and structured findings output.
Consolidated accessibility skill entrypoint for WCAG 2.2, ARIA Authoring Practices, cognitive accessibility, Section 508, EN 301 549, design intent verification, and the Accessibility Planner workflow.
Generate and run post-migration tests from the frozen baseline specification.
How team members request infrastructure connection info and handle secrets in team mode
Provides role charters (mission, ownership, core principles, quality bar) for a multi-agent coding team. Each charter defines the role's mission, ownership scope, core principle (boundary constraints), and quality bar. Most roles also include communication rules. Consumed by the coordinator during task decomposition to assign work to the correct role. Triggers: "look up role charter", "what does the architect own", "check role boundaries", "find team roles", "which role handles X", "list agent charters", "role responsibilities". NOT for: task decomposition (use breaking-down-tasks), implementa
How to record project learnings so that later-phase workers and future agent runs can consume them.
Creates or updates the project constitution that defines migration principles, constraints, and conventions. Triggers: "set up constitution", "define migration principles", "create project rules", "establish conventions", "establish migration constitution". NOT for: implementation, implementation planning, task generation.
Runtime validation for migrated applications — covers testing strategy (planning phase) and test execution (validation phase): startup verification, integration testing, and end-to-end flow validation. Use when: (1) designing test strategy during planning phase (teamlead reads Part 1) (2) verifying a migrated app starts and runs correctly (3) writing or executing integration / E2E tests (tester reads Part 2) (4) choosing test tooling and environment setup (5) producing structured test evidence and verdicts Triggers: "runtime validation", "testing strategy", "test strategy", "test design",
Runs quality gate validation at each workflow stage. Supports 4 gate types: spec-quality, spec-to-plan, plan-to-tasks, completeness. Produces gate pass/fail reports with actionable feedback. Triggers: "run quality gate", "validate spec quality", "spec quality", "plan coverage", "check plan coverage", "validate plan to tasks", "check task traceability", "verify task completeness", "run completeness review", "review implementation", "check plan traceability", "check coverage", "completeness quality gate", "final sign-off", "feature parity sign-off", "completeness gate", "feature parity", "sign-o
Zero-dependency shell recon for any code repository — detect languages, count LOC, and report project scale. Pure POSIX find/wc or PowerShell, no Python or third-party tools required. Triggers: "how big is this project", "what languages", "project sizing", "repo recon", "LOC count", "scope check".
Single-source codebase decomposition: scans a project scope, builds the module dependency graph, counts LOC by language, computes skip patterns (caller-supplied ∪ .gitignore ∪ baseline), and (when grouping is required) produces topology groupings with L3 quality validation. One skill owns ProjectProfile JSON, grouping protocols, and quality gates. Triggers: "before generating a workflow plan", "before topology grouping", "project sizing", "LOC counting", "module grouping", "topology splitting rules", "topology consumer rules", "scale-aware splitting", "large codebase decomposition", "module de
