Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add d-mariano/spicyclaude --skill greenfield-designgit clone --depth 1 https://github.com/d-mariano/spicyclaudeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/d-mariano/spicyclaude/greenfield-design)<a href="https://agentmods.dev/skills/d-mariano/spicyclaude/greenfield-design"><img src="https://agentmods.dev/badge/skills/d-mariano/spicyclaude/greenfield-design/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/d-mariano/spicyclaude/greenfield-design"><img src="https://agentmods.dev/badge/skills/d-mariano/spicyclaude/greenfield-design.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00048 | $0.02229 |
| Opus 5 | $0.00024 | $0.01115 |
| Sonnet 5 | $0.00010 | $0.00446 |
| Haiku 4.5 | $0.00005 | $0.00223 |
Grade A, and why
greenfield-design scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 217 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Greenfield Design Workflow
You are executing a multi-phase technical design workflow for a new system being built from scratch. The hard problem is making good architectural choices under maximum freedom.
Before You Start
Read the example output at .claude/skills/greenfield-design/examples/notification-system.md to calibrate the expected depth, format, and level of concreteness. Your output should match this quality bar.
If the user's task involves replacing or migrating from an existing system, also read .claude/skills/refactor-modifier/SKILL.md and apply its additions at each phase (look for "Phase 1 Addition", "Phase 2 Addition", etc.).
Critical Rules
- Pause after every phase. Present your output, then ask the user to review, correct, and answer unknowns before proceeding.
- Do not skip the Unknowns section. It is the most valuable output of Phase 1. A design that papers over ambiguity is worse than no design.
- Name things concretely. Every type, interface, function, and file must have a real name. "SomeService", "DataProcessor", and "handleData" are banned.
- Skip sections that don't apply. Not every system needs DTOs. Not every design needs cross-cutting concerns. When you skip a section, add one line explaining why.
- The output file must stand alone. A downstream planner or engineer should be able to read it cold with no conversation context.
- Save intermediate outputs. Write Phase 1 and Phase 2 reports to
docs/design/<task-slug>/phase-1-discovery.mdanddocs/design/<task-slug>/phase-2-constraints.mdrespectively. The final design goes todocs/design/<task-slug>/design.md.
Phase 1: Landscape & Tradeoff Analysis
Goal: Understand the problem space, survey solutions, evaluate architectural approaches. Arrive at Phase 2 with a justified direction, not a default one.
Produce a structured report covering:
1. Problem Framing
- Core problem in one sentence
- Users/consumers of this system (humans, services, or both)
- Top 3-5 primary use cases by importance
- Non-functional requirements (throughput, latency, availability, consistency, data volume, compliance)
- Expected scale at launch vs. 12 months (be specific: requests/sec, data volume, concurrent users)
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 217 lines · 48 tokens per session scan A 9554e69527f1
greenfield-design is a skill published in the GitHub repository d-mariano/spicyclaude (5 stars, last pushed 1mo ago), licensed MIT. It adds 48 tokens to every session and 2,229 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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