Workshop Analysis Flow

For converting discovery workshop materials into structured, Jira-ready epics and user stories, use the Workshop Analysis workflow. This takes raw workshop outputs (transcripts, designs, notes) and produces a validated backlog ready for team refinement.

Command Sequence

1️⃣ /tsh-analyze-materials <workshop materials>
   ↳ 📝 Agent processes transcript — cleans, structures, extracts decisions
   ↳ 📖 Review cleaned transcript for accuracy
   ↳ 🔍 Agent analyzes Figma designs and codebase context
   ↳ 📋 Agent extracts epics and user stories

2️⃣ Gate 1 — Task Review
   ↳ 📖 Review extracted tasks — check epic/story breakdown
   ↳ ✅ Approve, or request splits/merges/removals

3️⃣ Gate 1.5 — Quality Review (automatic)
   ↳ 🔍 Agent runs 10 analysis passes for gaps and edge cases
   ↳ 📖 Review each suggestion — accept or reject individually
   ↳ ✅ Agent applies accepted suggestions to the task list

4️⃣ Gate 2 — Jira Push Approval
   ↳ 📖 Review final formatted tasks
   ↳ ✅ Confirm target Jira project and approve push
   ↳ 🚀 Agent creates/updates issues in Jira

Workflow Diagram

┌─────────────────────────────┐
│  Raw Workshop Materials     │
│  (transcript, Figma, notes) │
└──────────┬──────────────────┘
           ▼
┌─────────────────────────────┐
│  Transcript Processing      │
│  → cleaned-transcript.md    │
└──────────┬──────────────────┘
           ▼
┌─────────────────────────────┐
│  Task Extraction            │
│  → extracted-tasks.md       │
└──────────┬──────────────────┘
           ▼
┌─────────────────────────────┐
│  ★ Gate 1: User Review      │
└──────────┬──────────────────┘
           ▼
┌─────────────────────────────┐
│  Quality Review (10 passes) │
│  → quality-review.md        │
└──────────┬──────────────────┘
           ▼
┌─────────────────────────────┐
│  ★ Gate 1.5: Accept/Reject  │
└──────────┬──────────────────┘
           ▼
┌─────────────────────────────┐
│  Jira Formatting            │
│  → jira-tasks.md            │
└──────────┬──────────────────┘
           ▼
┌─────────────────────────────┐
│  ★ Gate 2: Push Approval    │
└──────────┬──────────────────┘
           ▼
┌─────────────────────────────┐
│  Push to Jira               │
│  (create epics → stories)   │
└─────────────────────────────┘

Quality Review Passes

The quality review step runs 10 domain-agnostic analysis passes against the approved task list:

Pass	Category	What It Checks
A	Entity Lifecycle	CRUD completeness for every business entity
B	Cross-Feature State	State validation when features consume shared entities
C	Bulk Operations	Idempotency and partial failure handling for batch operations
D	Actor Dashboards	Metrics, configuration, and history for management interfaces
E	Precondition Guards	Feature dependencies and prerequisite enforcement
F	Third-Party Boundaries	External system integration clarity and failure modes
G	Platform Operations	Admin/operator tooling and monitoring capabilities
H	Error States	Failure, empty, and boundary condition coverage
I	Notifications	Communication gaps when state changes affect other actors
J	Domain Research	Industry-specific patterns and compliance requirements

Import Mode

To iterate on an existing Jira backlog instead of workshop materials:

/tsh-analyze-materials PROJ-123

The agent fetches existing issues from Jira, converts them into the local format, then runs quality review and formatting. Changes can be pushed back to Jira individually or in batch.

Connecting to the Standard Flow

After workshop analysis, individual tasks can flow into the standard delivery workflow:

/tsh-analyze-materials  →  /tsh-research PROJ-123  →  /tsh-plan PROJ-123  →  /tsh-implement  →  /tsh-review

Use the Deep-dive Research per Task handoff to transition a specific task to the Context Engineer for detailed requirements gathering, or the Prepare Implementation Plan handoff to send it to the Architect.

Important

Each gate requires your review and approval. The Business Analyst produces business-oriented outputs — validate that the extracted tasks accurately reflect workshop discussions and that no critical topics were missed. AI assistance does not replace stakeholder judgment.