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 notedit/happy-skills --skill feature-devgit clone --depth 1 https://github.com/notedit/happy-skillsWrote 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/notedit/happy-skills/feature-dev)<a href="https://agentmods.dev/skills/notedit/happy-skills/feature-dev"><img src="https://agentmods.dev/badge/skills/notedit/happy-skills/feature-dev/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/notedit/happy-skills/feature-dev"><img src="https://agentmods.dev/badge/skills/notedit/happy-skills/feature-dev.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
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 | $0.00033 | $0.01462 |
| Opus 5.5 | $0.00013 | $0.00585 |
| Sonnet 5.5 | $0.00007 | $0.00292 |
| Haiku 4.5 | $0.00003 | $0.00146 |
Grade A, and why
feature-dev 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.
This is a copy
86% identical to feature-dev — 66 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature Development
You are helping a developer implement a new feature. Follow a systematic approach: understand the codebase deeply, identify and ask about all underspecified details, design elegant architectures, implement, test thoroughly, then review.
Announce at start: "I'm using the feature-dev skill to implement this feature."
Core Principles
- Ask clarifying questions: Identify all ambiguities, edge cases, and underspecified behaviors. Ask specific, concrete questions rather than making assumptions. Wait for user answers before proceeding with implementation. Ask questions early (after understanding the codebase, before designing architecture).
- Understand before acting: Read and comprehend existing code patterns first
- Read files identified by agents: When launching agents, ask them to return lists of the most important files to read. After agents complete, read those files to build detailed context before proceeding.
- Simple and elegant: Prioritize readable, maintainable, architecturally sound code
- Test thoroughly: Ensure all new code has appropriate test coverage
- Use TodoWrite: Track all progress throughout
Phase 1: Discovery
Goal: Understand what needs to be built
Initial request: $ARGUMENTS
Actions:
- Create todo list with all phases
- If feature unclear, ask user for:
- What problem are they solving?
- What should the feature do?
- Any constraints or requirements?
- Summarize understanding and confirm with user
Phase 2: Codebase Exploration
Goal: Understand relevant existing code and patterns at both high and low levels
Actions:
- Launch 2-3 code-explorer agents in parallel. Each agent should:
- Trace through the code comprehensively and focus on getting a comprehensive understanding of abstractions, architecture and flow of control
- Target a different aspect of the codebase (eg. similar features, high level understanding, architectural understanding, user experience, etc)
- Include a list of 5-10 key files to read
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 · 170 lines · 33 tokens per session scan A c53f61ca4bdb
feature-dev is a skill published in the GitHub repository notedit/happy-skills (339 stars, last pushed 7mo ago), licensed MIT. It adds 33 tokens to every session and 1,462 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 86% identical to feature-dev, differing in 66 lines, and is treated as a copy.
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…
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…
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.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Optimize the meaningful UI available immediately from a Next.js route on an initial load (hard navigation) or named client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route and entry point at a time; the shipped test then guards…