NeetuAggarwal-AI

BA AI Skills — AI skill for Claude Code

AI community

Reusable AI skills for Business Analysis & Product Ownership — for BAs, POs, and any developer, tester, architect or engineer wearing the BA/PO hat: requirements discovery, workshop analysis, user sto.

How to install BA AI Skills

This entry records only its repository, not the path inside it, so there is no exact command to give. Open NeetuAggarwal-AI/BA-AI-Skills and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What BA AI Skills does

Reusable AI skills for Business Analysis & Product Ownership — for BAs, POs, and any developer, tester, architect or engineer wearing the BA/PO hat: requirements discovery, workshop analysis, user stories, Gherkin, API & integration analysis, source-to-target mapping, process modelling, backlog quality, and specification workflows.

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README

BA-AI-Skills

📖 **How to use →** https://neetuaggarwal-ai.github.io/BA-AI-Skills/

**Reusable AI Agent Skills for Business Analysis & Product Ownership** — for BAs, POs, and any developer, tester, architect or engineer wearing the BA/PO hat.

These are packaged, reusable skills that encode *experienced* BA thinking — not just output formatting. They help you do real analysis work: turn raw requirements into well-formed epics and user stories, write solid acceptance criteria, map dependencies, and keep everything traceable — while surfacing assumptions, gaps and open questions instead of inventing detail.

Each skill is an [Agent Skill](https://docs.claude.com): a `SKILL.md` file of instructions plus supporting references, templates and examples, designed to be used by an AI assistant that supports skills.


Why this exists

Most AI "story generators" happily invent requirements to look complete. That's the opposite of good BA practice. Every skill here is built on a set of guardrails:

  • Never invent requirements — missing detail becomes a labelled assumption or an open question.
  • Identify actors, business rules, source-of-truth systems, dependencies and integration impacts.
  • Separate business requirements from system behaviour.
  • Cover edge cases and failure scenarios, not just the happy path.
  • Preserve the organisation's own terminology.
  • Keep full traceability from source requirement → epic → story → acceptance criteria.

The result is output you can actually take into a refinement session, not a first draft you have to unpick.


The vision

The long-term goal is a set of skills that chain together into a full specification pipeline:

Workshop transcript
   → Workshop analysis
   → Requirements extraction
   → Gap analysis
   → Business rules
   → Open questions
   → Epics / Features
   → User stories
   → Gherkin acceptance criteria
   → API / integration requirements
   → Process models
   → Specification / BRD
   → Jira / ADO backlog
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