Greenfield

Quick Summary

Goal: Guide greenfield project inception from raw idea to an approved, implementable project plan using a full waterfall process.

Workflow (16 steps):

1. Discovery (/​idea) — Interview user about problem, vision, constraints, team skills, scale. DO NOT ask about tech stack — keep business-focused.
2. Market Research (/​web-research) — WebSearch for competitors, market landscape, existing solutions
3. Deep Research (/​deep-research) — WebFetch top sources, extract key findings
4. Business Evaluation (/​business-evaluation) — Viability assessment, risk matrix, value proposition
5. Domain Analysis & ERD (/​domain-analysis) — Bounded contexts, aggregates, entities, ERD diagram, domain events. Validate every context boundary with user.
6. Tech Stack Research (/​tech-stack-research) — Derive technical requirements from business + domain analysis. Research top 3 options per stack layer (backend, frontend, database, messaging, infra). Detailed pros/​cons matrix, team-fit scoring, market analysis. Present comparison report for user to decide.
7. Architecture Design (/​architecture-design) — Research and compare top 3 architecture styles (Clean, Hexagonal, Vertical Slice, etc.). Evaluate design patterns (CQRS, Repository, Mediator). Audit against SOLID, DRY, KISS, YAGNI. Validate scalability, maintainability, IoC, technical agnosticism. Present comparison with recommendation. Harness output required: produce a "Scaffold Handoff — Harness Plan" table in the architecture report: (a) feedforward guides to create (AGENTS.md sections, skill activation rules, pattern catalog), (b) computational feedback sensors to install (linter, formatter, pre-commit, CI), (c) inferential feedback sensors to configure (review skills, AI gates). This table feeds /​scaffold → /​linter-setup → /​harness-setup.
8. Implementation Plan (/​plan) — Create phased plan using confirmed tech stack + architecture + domain model
9. Security Audit (/​security-review) — Review plan for OWASP Top 10, auth patterns, data protection concerns
10. Performance Audit (/​performance-review) — Review plan for performance bottlenecks, scalability, query optimization
11. Plan Review (/​plan-review) — Full plan review, risk assessment, approval
12. Refine to PBI (/​refine) — Transform idea + reviewed plan into actionable PBI with acceptance criteria
13. User Stories (/​story) — Break PBI into implementable user stories
14. Plan Validation (/​plan-validate) — Interview user with critical questions to validate plan + stories
15. Test Strategy (/​spec [mode=tests]) — Test pyramid, frameworks, spec outline
16. Workflow End (/​workflow-end) — Clean up, announce completion

Key Rules:

• PLANNING ONLY: never implement code
• Every stage saves artifacts to plan directory
• MANDATORY IMPORTANT MUST ATTENTION every stage requires AskUserQuestion validation before proceeding
• Delegate architecture decisions to solution-architect agent
• Present 2-4 options for every major decision with confidence %
• Business-First Protocol: Tech stack is NEVER asked upfront. Business analysis (steps 1-5) + domain modeling (step 6) must complete first. Tech stack is derived from requirements through research and presented as a comparison report with options.
• MANDATORY IMPORTANT MUST ATTENTION architecture design MUST produce a "Scaffold Handoff — Harness Plan" table covering: feedforward guides, computational sensors (/​linter-setup handles install), and inferential sensors (/​harness-setup configures). The scaffold + linter-setup + harness-setup triad are NON-SKIPPABLE infrastructure — code without a harness accumulates technical debt from day one.

Entry Point

This skill is the explicit entry point for the workflow-greenfield-init workflow.

When invoked:

1. Activate the workflow-greenfield-init workflow via /​start-workflow workflow-greenfield-init
2. The workflow handles step sequencing, task creation, and progress tracking
3. Each step delegates to the appropriate skill (idea, web-research, domain-analysis, tech-stack-research, etc.)
4. The solution-architect agent provides architecture guidance throughout

When to Use

• Starting a brand-new project from scratch
• No existing codebase (empty project directory)
• Planning a new application before writing any code
• Want structured waterfall inception with user collaboration at every step

When NOT to Use

• Existing codebase with code (use /​plan or /​start-workflow workflow-feature instead)
• Bug fixes, refactoring, or feature implementation
• Quick prototyping (use /​cook instead)

Output

All artifacts saved to plan directory:

plans/​{id}/
  research/
    discovery-interview.md
    market-research.md
    deep-research.md
    business-evaluation.md
    domain-analysis.md
    tech-stack-comparison.md
    architecture-design.md
  phase-01-domain-model.md
  phase-02-tech-stack.md
  phase-02b-architecture.md
  phase-03-project-structure.md
  phase-04-test-strategy.md
  phase-05-backlog.md
  plan.md (master plan with YAML frontmatter)

After completion, recommend next step: /​cook to scaffold the project structure.

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

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MANDATORY IMPORTANT MUST ATTENTION break work into small todo tasks — one per workflow step. MANDATORY IMPORTANT MUST ATTENTION validate with user at EVERY step — never auto-decide. MANDATORY IMPORTANT MUST ATTENTION add a final review todo task to verify work quality and identify fixes/​enhancements.

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MANDATORY IMPORTANT MUST ATTENTION use TaskCreate to break ALL work into small tasks BEFORE starting. MANDATORY IMPORTANT MUST ATTENTION use AskUserQuestion at EVERY stage — validate decisions before proceeding. MANDATORY IMPORTANT MUST ATTENTION NEVER ask tech stack upfront — business analysis and domain modeling first.

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AI Mistake Prevention — Failure modes to avoid on every task:

Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal. Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing. Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain. Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path. When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site. Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code. Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks. Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis. Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly. Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path. Keep domain concepts out of generic/​shared/​infrastructure layers. A reusable layer (shared library, framework, infra module) must reference NO consumer-specific domain concept — tenant/​customer/​product IDs, business entities, feature rules. The leak compiles and runs, so it passes review silently while coupling the "reusable" layer to one consumer. Push domain fields/​logic down into the consumer via subclass or composition.

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Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.

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MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.

<!-- /​SYNC:critical-thinking-mindset:reminder --> <!-- SYNC:ai-mistake-prevention:reminder -->

MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.

<!-- /​SYNC:ai-mistake-prevention:reminder -->

Closing Reminders

• MANDATORY IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting
• MANDATORY IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code
• MANDATORY IMPORTANT MUST ATTENTION cite file:line evidence for every claim (confidence >80% to act)
• MANDATORY IMPORTANT MUST ATTENTION add a final review todo task to verify work quality

[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using TaskCreate.