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 giving-feedbackgit 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/giving-feedback)<a href="https://agentmods.dev/skills/refoundai/lenny-skills/giving-feedback"><img src="https://agentmods.dev/badge/skills/refoundai/lenny-skills/giving-feedback/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/giving-feedback"><img src="https://agentmods.dev/badge/skills/refoundai/lenny-skills/giving-feedback.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 | $0.00031 | $0.01753 |
| Opus 5 | $0.00015 | $0.00877 |
| Sonnet 5 | $0.00006 | $0.00351 |
| Haiku 4.5 | $0.00003 | $0.00175 |
Grade A, and why
giving-feedback 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 11d 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 — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Giving Effective Feedback
Transform difficult conversations into catalysts for growth and high performance.
Help the user with giving effective feedback using insights from 30 guests and posts across Lenny's Podcast and Newsletter.
How to Help
- Preparation - Help the user structure their thoughts using the GAIN framework to ensure feedback is goal-oriented and evidence-based.
- Roleplay - Use the AI Voice Mode prompt to simulate the conversation and practice responding to potential defensiveness.
- Refinement - Review a draft of the feedback to remove judgmental labels and ensure the user is 'staying on their side of the net.'
- Debrief - Analyze the results of a feedback session and plan for necessary follow-up actions and commitments.
Core Principles
Care personally and challenge directly
Kim Scott: "Radical Candor is just what happens when you care personally and challenge directly at the same time. And I think it's probably best understood by what it's not because we all fail on one of those two dimensions or both of them multiple times a day."
Effective constructive feedback requires balancing a genuine personal connection with the courage to be direct about what needs to change.
Stay on your side of the net
Carole Robin: "We don't understand that we are only privy to two out of the three, so I know what's going on for me and I know what I did. I have no idea what happened on your end."
Acknowledge that you only have access to your own intent and the other person's behavior. Speak only to the impact that behavior had on you.
Frame feedback as a joint effort
Alisa Cohn: "You know, Matilda, I want to chat with you about the way you're interacting with your peers. So what I'm hearing from them is that you're missing deadlines on a regular basis and not letting them know you're missing the deadlines, and that also you're not fully keeping your team up to speed. And so they're kind of confused running around. Now, we both know that the most important way you can be successful here and also achieve your goals is to make sure that you are working with your peers in a way that's consistent and that they can count on you and you can count on them."
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.
- 11d ago First seen · 101 lines · 31 tokens per session scan A 175a9734b183
giving-feedback is a skill published in the GitHub repository RefoundAI/lenny-skills (1,318 stars, last pushed 1mo ago), licensed MIT. It adds 31 tokens to every session and 1,753 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
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.
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.