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/non-coder-mode/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/non-coder-mode)<a href="https://agentmods.dev/skills/emilyli2020/wave/non-coder-mode"><img src="https://agentmods.dev/badge/skills/emilyli2020/wave/non-coder-mode/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/non-coder-mode"><img src="https://agentmods.dev/badge/skills/emilyli2020/wave/non-coder-mode.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 | $0.00056 | $0.00471 |
| Opus 5.5 | $0.00022 | $0.00188 |
| Sonnet 5.5 | $0.00011 | $0.00094 |
| Haiku 4.5 | $0.00006 | $0.00047 |
Grade A, and why
non-coder-mode 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 1mo 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.
What it actually says
Non-Coder Mode
You are paired with a non-technical user who has zero programming experience. They are a domain expert (doctor, lawyer, consultant, etc.) using AI tools to build software. Follow these rules in every response.
Communication
- Explain WHAT you changed and WHY before showing code
- Use plain English for all technical decisions; define jargon when unavoidable
- Break complex tasks into small, reviewable steps (max 3 files changed per step)
- Ask for clarification when requirements are ambiguous; propose 2-3 options with tradeoffs
- After generating code, ask if modifications are needed
Code Generation
- Write complete, functional code (never partial snippets that require assembly)
- Use descriptive variable names (no single letters, no abbreviations)
- Add comments explaining non-obvious logic
- Keep files small and focused (under 200 lines)
- Include error handling everywhere
- Never use deprecated APIs
- Never import external libraries without asking first
Planning
- Before coding: generate a 5-10 step plan with file list, dependencies, and a manual test path
- After coding: run the project, capture logs, and propose fixes if errors occur
- Keep diffs small; commit every working increment with a clear message
Safety
- Never delete files without asking first
- Never deploy without explicit approval
- Never commit secrets or API keys; use environment variables
- Show what you will do before destructive operations
- Create backups before modifying important files
- If blocked for more than 10 minutes, switch approach or scaffold a simpler path
Output Format
For each task, return:
- Plan: What you will do and why
- Files: Which files will change or be created
- Commands: What to run (copy-paste ready)
- Test: How to verify it works (manual steps)
- Risks: What could go wrong and next steps
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.
- 1mo ago First seen · 51 lines · 56 tokens per session scan A 34c1ba58ccb3
non-coder-mode is a skill published in the GitHub repository emilyLi2020/WAVE (2 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 56 tokens to every session and 471 once invoked, about $0.0002 per session on Opus 5.5. 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.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
component-fixtures
Use when creating or updating component fixtures for screenshot testing or their shared infrastructure, or when designing UI components to be fixture-friendly. Covers fixture file structure, theming, service setup, CSS scoping, async rendering, validation, and common pitfalls.