Greenfield Planning Skill

SkillSecurity

Parallel persona planning for new projects. Research agent runs first to build domain context, then Architect, PM, and Security agents run in parallel. Synthesis agent combines all perspectives into a detailed GSD-style PLAN.md with Tensions section.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Greenfield Planning Skill skill

What this skill tells your AI

The instructions your AI receives, as published by wednesday-solutions/ai-agent-skills in skills/greenfield/SKILL.md and read by ahel’s review.

Trigger

Run once per project: ws-skills plan

Reads BRIEF.md from the project root (or prompts for one). Asks 5 clarifying questions before planning.

Flow

Brief + Q&A
    ↓
Research agent (sequential)   ← domain landscape, ecosystem, hidden complexity
    ↓
┌─────────────────────────────────────┐
│ Architect │ PM │ Security (parallel)│  ← spawn 3 subagents simultaneously
└─────────────────────────────────────┘
    ↓
Synthesis             ← combines all into PLAN.md

Agents

1. Research (sequential — runs first)

Builds domain context that all other agents receive. Covers:

  • Existing solutions and their weaknesses
  • Standard and emerging tech stacks for this domain
  • Technologies to avoid and why
  • Non-obvious domain challenges
  • Integration landscape (auth, payments, comms, etc.)
  • Regulatory and compliance context
  • Realistic timeline based on similar projects
  • Hidden complexity — things that take 3x longer than expected
  • Success patterns from the best products in this space

Output: research.md

2–4. Architect, PM, Security (parallel subagents)

Spawn all three simultaneously using the Agent tool. Each receives the full brief, Q&A, and research output as context.

Agent 1 — Architect
Agent 2 — PM           ← launch all three in a single message, do not wait
Agent 3 — Security

Wait for all three to complete before running Synthesis.

Architect output: architect.md

  • System design overview
  • Tech stack with rationale per layer
  • Module boundaries and interfaces
  • Infrastructure and CI/CD
  • Scaling strategy
  • Technical risks

PM output: pm.md

  • Phases with tasks and acceptance criteria
  • Success metrics
  • Out of scope items
  • Assumptions

Security output: security.md

  • Threat model (likelihood + impact)
  • Data classification
  • Auth strategy recommendation
  • Compliance flags
  • Concrete security tasks
  • Urgent flags

5. Synthesis

Combines research + all three persona outputs into a single PLAN.md covering:

  • Overview
  • Clarifications table
  • Tech stack
  • Architecture
  • Phases with tasks and acceptance criteria
  • Security plan
  • Success metrics
  • Risks
  • Tensions (unresolved disagreements between personas)
  • Assumptions
  • Out of scope
  • Branch naming (GIT-OS format)

Output: PLAN.md

Tools

ActionTool
Read BRIEF.mdRead
Write persona output files (architect.md, pm.md, etc.)Write
Spawn Architect, PM, Security personas in parallelAgent (3 calls in one message)
Search the brief for keywordsGrep

Output Location

All files written to .wednesday/plans/ in the target directory:

.wednesday/plans/
├── research.md    ← domain context
├── architect.md   ← technical design
├── pm.md          ← phases and metrics
├── security.md    ← threat model
└── PLAN.md        ← combined PRD (primary output)

Failure Handling

Each agent fails independently. If one fails, the others continue and synthesis runs with whatever data is available. Failed agents show [partial fallback] in the progress display.

Rules

  • Branch naming in PLAN.md must follow GIT-OS format
  • Never generate CODEBASE.md for greenfield projects — it doesn't exist yet
  • Cost target: under $0.20 per run

Signals

GitHub stars
168
Forks
21
Last commit
May 2026
Advanced
Catalog kind
skill
Gateway key
greenfield
Source
github.com/wednesday-solutions/ai-agent-skills