Practical working skills for enterprise delivery.

Skill Hub transforms professional knowledge and enterprise frameworks into usable work skills. Every page is designed to help someone do real work: diagnose a problem, ask better questions, structure unclear information, produce a useful artifact, review quality, make a decision, or guide an AI agent toward operational output.

This is not a place to read about what data governance is. This is a place to learn how to diagnose missing data ownership and turn it into a governance action plan.

This is not a place to read about event-driven architecture as a concept. This is a place to learn how to decide whether an event should exist, who owns it, what its contract is, and how failures are monitored.

• Enterprise consultants who need structured methods for ambiguous client situations.
• Business analysts who turn vague stakeholder complaints into requirements, assumptions, risks, and acceptance criteria.
• Data consultants who diagnose data quality failures and build governance that sticks.
• Solution architects who map capabilities, review designs, and record decisions with context.
• Integration architects who decide between APIs and events, define contracts, and handle failures.
• SAP AMS consultants who triage incidents, perform root cause analysis, and capture operational knowledge.
• AI agents that need structured instructions to produce useful enterprise artifacts instead of generic explanations.

Atlas explains why a sales order is blocked. Skill Hub explains how to run a stakeholder interview that produces requirements instead of complaints. They complement each other.

1. Pick a skill group that matches your current work situation.
2. Open a skill page and read the "When to use this skill" section.
3. Follow the working method step by step. Use the questions, decision rules, and templates provided.
4. Produce the deliverables listed on the page. Do not stop at understanding.
5. Use the quality checklist to review your output before sharing it.
6. Combine skills when a situation spans multiple domains. For example, a data quality incident may require Data Quality Root Cause + Stakeholder Analysis + Change Impact Analysis.

AI agents should treat Skill Hub as an operational instruction set, not a knowledge base for summarization. See the Agent Usage Guide for detailed instructions.

In short: choose a skill, ask for missing context, separate facts from assumptions, produce artifacts, and avoid generic framework language.

Business Analyst path

1. Stakeholder Analysis
2. Requirements Elicitation
3. Use Case Analysis
4. Business Rules Discovery
5. Process Analysis
6. Assumption and Constraint Mapping
7. Gap Analysis
8. Scope Boundary Definition
9. User Story Refinement
10. Acceptance Criteria

Systems Analyst path

1. State and Lifecycle Analysis
2. Interface Requirement Analysis
3. System Context Mapping
4. API Integration
5. Change Impact Analysis

Decision & Validation path

1. Trade-Off Analysis
2. Option Comparison Matrix
3. Risk and Dependency Mapping
4. Evidence-Based Recommendation
5. Requirements Review Checklist

AI-Assisted Analysis path

1. AI Accountability
2. Convert Notes to Requirements
3. Validate AI-Generated Requirements
4. Business Problem to Backlog

Data Governance / DAMA path

1. Data Governance
2. Data Quality Root Cause
3. Master Data Management
4. Metadata Management
5. Data Lineage

Solution Architect path

1. Capability Mapping
2. System Context Mapping
3. Solution Architecture Review
4. Architecture Decision Record
5. Non-Functional Requirements

Integration Architect path

1. Interface Ownership
2. API Integration
3. Event-Driven Architecture
4. Integration Observability
5. Integration Error Handling

SAP AMS / Operations path

1. Incident Triage
2. Root Cause Analysis
3. Operational Knowledge Capture
4. Change Impact Analysis
5. Recurring Ticket Pattern Analysis

Analyst Delivery Path

1. Requirements Elicitation
2. Scope Boundary Definition
3. Requirements Review Checklist
4. Test Scenario Derivation
5. Test Case Design
6. Handover Note Writing

AI-Assisted Development Path

1. AI Tool Selection for Development
2. Repository Context Packing with Repomix
3. AI Coding Agent Task Design
4. AI-Generated Code Review
5. MCP Development Workflow

AI-Assisted Documentation Path

1. Convert Notes to Requirements
2. AI-Assisted Documentation Review
3. Decision Summary Writing
4. Knowledge Article Writing
5. AI Output Review

Delivery Readiness Path

1. Risk and Dependency Mapping
2. Regression Test Planning
3. Deployment Readiness Checklist
4. QA Review and Sign-Off
5. Status Update Writing

AI Agent path

1. Agent Usage Guide
2. Skill Page Template
3. Artifact Templates
4. Quality Rules
5. Pick any skill page and follow its Agent Instructions section.

• Agent Usage Guide — How AI agents should use Skill Hub.
• Skill Page Template — The standard structure for every skill page.
• Artifact Templates — Reusable templates that skills reference.
• Quality Rules — What makes a Skill Hub page good or bad.
• Framework Map — How major frameworks map to practical work.

Skill Hub is a public working interpretation of enterprise knowledge. It is not official DAMA, BABOK, TOGAF, or SAP documentation. Every skill page includes a verification status and limitations section. Use these skills as structured starting points, not as authoritative framework substitutes.

Found an issue or have a skill suggestion? Open an issue on the repository.