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 customer-interviewsgit 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/customer-interviews)<a href="https://agentmods.dev/skills/refoundai/lenny-skills/customer-interviews"><img src="https://agentmods.dev/badge/skills/refoundai/lenny-skills/customer-interviews/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/customer-interviews"><img src="https://agentmods.dev/badge/skills/refoundai/lenny-skills/customer-interviews.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 | $0.00028 | $0.01328 |
| Opus 5 | $0.00014 | $0.00664 |
| Sonnet 5 | $0.00006 | $0.00266 |
| Haiku 4.5 | $0.00003 | $0.00133 |
Grade A, and why
customer-interviews 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 10d 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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mastering Customer Interviews
Uncover deep user pain and behavioral triggers to build products people actually need.
Help the user with mastering customer interviews using insights from 11 guests and posts across Lenny's Podcast and Newsletter.
How to Help
- Define objectives - Identify the specific problem area or user segment you want to explore before recruiting participants.
- Draft the guide - Create open-ended questions that focus on past behaviors and struggling moments rather than hypothetical opinions.
- Synthesize findings - Analyze interview notes to distinguish between polite encouragement and genuine user pull.
- Validate pain - Evaluate whether the identified problems are painful enough to warrant a new solution or behavioral change.
Core Principles
Focus on causal triggers
Bob Moesta: "And so the real heart of the method of Jobs to Be Done is understanding the causation of what pushes people to say, 'Today's the day I got to do something different.'"
Interviews should uncover the specific events and context that led to a change in behavior. Understanding the struggling moment makes seemingly irrational user choices appear rational.
Observe unarticulated pain
Jag Duggal: "You make sure that you focus on customer discovery before you start building. You make sure that that discovery is focused not simply on asking the customer, but on innovating on their behalf."
Effective research goes beyond listening to explicit requests by observing users in their natural environment. This reveals friction points that users may not be able to describe.
Actively seek disproof
Shaun Clowes: "Avoid availability or confirmation bias. Most of the time people go talk to the people they always talk to and they learn nothing particularly new. They don't synthesize the results that they got from that conversation. They don't seek out the counterfactual, they don't seek out the proof that they're wrong."
To avoid confirmation bias, you must intentionally seek out data points that disprove your current assumptions. Learning is maximized when you find counterfactual perspectives.
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.
- 10d ago First seen · 89 lines · 28 tokens per session scan A fc18a53c4051
customer-interviews is a skill published in the GitHub repository RefoundAI/lenny-skills (1,315 stars, last pushed 1mo ago), licensed MIT. It adds 28 tokens to every session and 1,328 once invoked, about $0.0001 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
llama-cpp
Run LLM inference with llama.cpp on CPU, Apple Silicon, AMD/Intel GPUs, or NVIDIA — plus GGUF model conversion and quantization (2–8 bit with K-quants and imatrix). Covers CLI, Python bindings, OpenAI-compatible server, and Ollama/LM Studio integration. Use for edge deployment, M1/M2/M3/M4 Macs, CUDA-less…
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.
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.
notion
Notion API for creating and managing pages, databases, and blocks via curl. Search, create, update, and query Notion workspaces directly from the terminal.