Lenny Skills is a collection of product-management and engineering workflows for Claude Code and other AI agents, covering areas such as strategy, research, planning, shipping, growth, and hiring. Each skill gives an agent specialized guidance, frameworks, checklists, or templates for product work, and the catalogue contains many of these skills.
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 RefoundAI/lenny-skills --skill ai-assisted-prototypinggit clone --depth 1 https://github.com/RefoundAI/lenny-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/refoundai/lenny-skills/ai-assisted-prototyping)<a href="https://agentmods.dev/skills/refoundai/lenny-skills/ai-assisted-prototyping"><img src="https://agentmods.dev/badge/skills/refoundai/lenny-skills/ai-assisted-prototyping/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/refoundai/lenny-skills/ai-assisted-prototyping"><img src="https://agentmods.dev/badge/skills/refoundai/lenny-skills/ai-assisted-prototyping.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector 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 | $0.00043 | $0.00944 |
| Opus 5 | $0.00022 | $0.00472 |
| Sonnet 5 | $0.00009 | $0.00189 |
| Haiku 4.5 | $0.00004 | $0.00094 |
Grade A, and why
ai-assisted-prototyping 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 12d 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI-Assisted Prototyping
Transform abstract product concepts into functional, interactive software using natural language and AI tools.
Help the user with ai-assisted prototyping using insights from 15 guests and posts across Lenny's Podcast and Newsletter.
How to Help
- Identify the goal - Determine if the objective is a visual exploration, a functional internal tool, or a production-grade feature validation.
- Select the tool - Choose between web-based visual builders like v0 or Lovable and local development environments like Cursor based on project complexity.
- Prompt and iterate - Use detailed descriptions, PRDs, or screenshots to generate the initial version and refine it through granular, sequential feedback.
- Validate and hand off - Use the interactive prototype to gather user feedback or provide engineering with high-fidelity reference code for implementation.
Core Principles
Taste-Making through Functional Builds
Aparna Chennapragada: "If you're not prototyping and building to see what you want to build, I think you're doing it wrong. It becomes even more important to have that territorial and taste-making at the heart of it because, otherwise, you just have a Frankenstein product."
Build functional prototypes immediately to develop product taste. Visualizing the vision before committing to full-scale development helps avoid building incoherent features that fail to solve core user problems.
Real-World Feature Validation
Eric Simons: "And it's not just building a static site, or something like that, but you can actually build full stack, real software with databases, and hosting and et cetera, just from prompting. And in a ridiculously short period of time, it's not like you're spending hours and hours or days, putting this together. You can get results in like, a minute."
Move beyond static mockups to validate complex features like databases and hosting. Text-to-app tools allow for the testing of full-stack versions of features rather than just static UIs.
What ships with it
2 files 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.
- 12d ago First seen · 67 lines · 43 tokens per session scan A 1e9d3a15da2c
ai-assisted-prototyping is a skill published in the GitHub repository RefoundAI/lenny-skills (1,321 stars, last pushed 1mo ago), licensed MIT. It adds 43 tokens to every session and 944 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 2026-08-30.
Other skills, from other repositories
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systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior. 4-phase root cause investigation — NO fixes without understanding the problem first.
github-auth
Set up GitHub authentication for the agent using git (universally available) or the gh CLI. Covers HTTPS tokens, SSH keys, credential helpers, and gh auth — with a detection flow to pick the right method automatically.
ideation
Generate project ideas through creative constraints. Use when the user says 'I want to build something', 'give me a project idea', 'I'm bored', 'what should I make', 'inspire me', or any variant of 'I have tools but no direction'. Works for code, art, hardware, writing, tools, and anything that can be made.
notion
Notion API for creating and managing pages, databases, and blocks via curl. Search, create, update, and query Notion workspaces directly from the terminal.
ocr-and-documents
Extract text from PDFs and scanned documents. Use webextract for remote URLs, pymupdf for local text-based PDFs, marker-pdf for OCR/scanned docs. For DOCX use python-docx, for PPTX see the powerpoint skill.