Discovery phase for blueprint workflow - interview triggers, acceptance criteria, and feature classification
Handles Steps 1-5 of the blueprint workflow: Idea Refinement, Research Decision Signals, Interview decision, Acceptance Criteria gathering, and Feature Classification.
feature_description: string # Raw feature description from user
Quick clarification before deep discovery. Catches misunderstandings early with 1-3 targeted questions.
Trigger when:
feature_description < 100 charactersSkip when:
If triggered:
AskUserQuestion:
question: "Quick check - what's the primary goal?"
header: "Goal"
options:
- label: "Add new capability"
description: "Feature that doesn't exist yet"
- label: "Fix broken behavior"
description: "Something that should work but doesn't"
- label: "Improve existing feature"
description: "Enhancement to current functionality"
- label: "Refactor/cleanup"
description: "Better code without behavior change"
Follow-up (if answer reveals gaps):
If goal == "Add new capability":
AskUserQuestion:
question: "Who will use this and when?"
header: "Context"
options:
- label: "End users in the app"
- label: "Admins/internal team"
- label: "Developers/API consumers"
- label: "Automated systems"
If goal == "Fix broken behavior":
AskUserQuestion:
question: "How does it fail?"
header: "Symptom"
options:
- label: "Error/crash"
- label: "Wrong output"
- label: "Missing data"
- label: "Performance issue"
Max 3 questions total. After refinement:
refined_description = original + goal + context/symptom (if asked)
Output skip offer:
"Got it: {refined_description}. Ready to proceed, or clarify further?"
During refinement, gather signals to inform the research decision in blueprint-research.
Infer from conversation:
| Signal | How to Detect |
|---|---|
user_familiarity | Points to existing code examples? Knows where files live? → high |
user_intent | "Quick fix", "ship today" → speed / "want it right", "research first" → thoroughness |
topic_risk | Keywords: auth, payment, stripe, security, encrypt, API key, webhook → high |
uncertainty_level | "Not sure how", "what's the best way", exploring options → high |
If signals unclear, quick probe:
AskUserQuestion:
question: "What matters more for this task?"
header: "Priority"
options:
- label: "Get it done fast"
description: "Good enough solution, ship quickly"
- label: "Get it done right"
description: "Research best practices first"
Store signals for research phase.
Suggest interview when:
Skip interview for:
If interview suggested:
AskUserQuestion:
question: "This feature could benefit from a requirements interview. Explore in depth first?"
options:
- "Yes, interview me first" → Invoke /majestic:interview with feature_description
- "No, proceed to planning" → Continue
MANDATORY: Ask what "done" means.
AC describes feature behaviors only. Quality gates (tests, lint, review) handled by other agents.
AskUserQuestion:
question: "What behavior must work for this feature to be done?"
header: "Done when"
multiSelect: true
options:
- label: "User can perform action"
description: "Feature enables a specific user action"
- label: "System responds correctly"
description: "API/backend behaves as expected"
- label: "UI displays properly"
description: "Visual elements render correctly"
- label: "Data is persisted"
description: "Changes are saved to database"
Good AC examples:
Bad AC examples (handled elsewhere):
Capture verification method for each criterion:
| Criterion | Verification |
|---|---|
| User can login | curl -X POST /login or manual |
| Form validates | rspec spec/features/signup_spec.rb |
| API returns 404 | curl /api/nonexistent |
| Type | Detection Keywords | Action |
|---|---|---|
| UI | page, component, form, button, modal, design, view, template | Check design system |
| DevOps | terraform, ansible, infrastructure, cloud, docker, deploy, server | Delegate to devops-plan |
| API | endpoint, route, controller, request, response, REST, GraphQL | Standard flow |
| Data | migration, model, schema, database, query | Standard flow |
UI Feature Flow:
/majestic:config design_system_pathdocs/design/design-system.md/majestic:ux-brief firstDevOps Feature Flow:
Skill(skill: "majestic-devops:devops-plan")
When working on an unfamiliar codebase, gather structural context before feature planning.
| Area | What to Check |
|---|---|
| Architecture | ARCHITECTURE.md, README.md, CONTRIBUTING.md, CLAUDE.md, AGENTS.md |
| Issue/PR patterns | .github/PULL_REQUEST_TEMPLATE*, .github/ISSUE_TEMPLATE/ |
| Contribution guidelines | Coding standards, testing requirements, review processes |
| Codebase patterns | Naming conventions, module boundaries, implementation patterns |
ast-grep via Bash for syntax-aware structural matching when text search is insufficient:
ast-grep --pattern 'class $NAME < ApplicationRecord' --lang ruby
## Repository Research Summary
### Architecture & Structure
- Project organization and tech stack
- Key architectural decisions
### Conventions
- Issue/PR formatting and labels
- Coding standards and testing requirements
### Implementation Patterns
- Common code patterns and naming conventions
- Project-specific practices
### Recommendations
- How to align with project conventions
- Areas needing clarification
discovery_result:
refined_description: string # Original + refinement context
refinement_skipped: boolean
interview_conducted: boolean
interview_output: string | null # If interview was run
acceptance_criteria:
- criterion: string
verification: string
feature_type: "ui" | "devops" | "api" | "data" | "general"
design_system_path: string | null # For UI features
# Research decision signals (for blueprint-research)
user_familiarity: high | medium | low
user_intent: speed | thoroughness
topic_risk: high | medium | low
uncertainty_level: high | medium | low
ready_for_research: boolean