Borrowing it
Nothing to install: this file belongs to emilyLi2020/WAVE. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/emilyLi2020/WAVE/main/.agents/skills/domain-to-spec/SKILL.mdgit clone --depth 1 https://github.com/emilyLi2020/WAVEWrote 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/emilyli2020/wave/domain-to-spec)<a href="https://agentmods.dev/skills/emilyli2020/wave/domain-to-spec"><img src="https://agentmods.dev/badge/skills/emilyli2020/wave/domain-to-spec/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/emilyli2020/wave/domain-to-spec"><img src="https://agentmods.dev/badge/skills/emilyli2020/wave/domain-to-spec.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 | $0.00088 | $0.02416 |
| Opus 5 | $0.00044 | $0.01208 |
| Sonnet 5 | $0.00018 | $0.00483 |
| Haiku 4.5 | $0.00009 | $0.00242 |
Grade A, and why
domain-to-spec 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 9d 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 — 234 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Domain to Spec
This is the first skill you should run when starting a new project. It captures the user's domain expertise, translates it into a buildable specification, and writes two files to the repo root that every other skill depends on:
AGENTS.md: the "README for agents" with setup commands, tech stack, file structure, and guardrails.PRD.md: the Product Requirements Document with the user flow, pages, and success criteria.
Every other scaffold skill (scaffold-frontend, scaffold-backend) reads these two files and refuses to run if they are missing. So this skill is a prerequisite for the rest of the stack.
Step 1: Extract Domain Knowledge
Ask the user:
"I'm a {profession} building a tool to {outcome}."
Then ask follow-up questions:
- What are the regulations or constraints in your field that this tool must respect?
- What are the 3 most error-prone or time-consuming steps in the current process?
- Who will use this tool? (you, your patients/clients, your staff, the public)
- What does success look like? (one sentence)
- Does the tool need to store data, authenticate users, or call external APIs? (helps decide if a backend is needed)
Step 2: Map the Domain to Software
For each domain concept the user describes, translate it:
| Domain Concept | Software Equivalent |
|---|---|
| Form or checklist | Input form with validation |
| Decision tree | Conditional logic / wizard flow |
| Reference document | Searchable knowledge base |
| Approval process | Status workflow with roles |
| Report or summary | Generated output / PDF export |
| Compliance check | Rule engine with pass/fail |
Step 3: Propose the Simplest Flow
Design the minimum viable product:
- One input (what the user provides)
- One process (what the app does with it)
- One output (what the user gets back)
Present it as:
INPUT: [what the user enters or uploads]
|
PROCESS: [what happens behind the scenes]
|
OUTPUT: [what the user sees or downloads]
Step 4: Decide if a Backend is Needed
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.
- 9d ago First seen · 234 lines · 88 tokens per session scan A 42ee131e89b8
domain-to-spec is a skill published in the GitHub repository emilyLi2020/WAVE (2 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 88 tokens to every session and 2,416 once invoked, about $0.0004 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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