Taste
affaan-m/ECC
Creative-direction layer for music videos and short-form edits in the angelcore / cloud-trance / hyperpop family — a named-genre aesthetic vocabulary, mood + color + light system, beat-synced…
Help users build a professional eye for quality, articulate the reasoning behind successful product paradigms, and develop the conviction to make high-stakes decisions before data is available.
$ npx skills add RefoundAI/lenny-skills --skill product-taste -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install RefoundAI/lenny-skills product-taste --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/RefoundAI/lenny-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/product-taste .claude/skills/product-taste && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "product-taste" agent skill from https://github.com/RefoundAI/lenny-skills/tree/main/skills/product-taste into .claude/skills/product-taste/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-taste", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/RefoundAI/lenny-skills/tree/main/skills/product-tasteType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add RefoundAI/lenny-skills --skill product-taste -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install RefoundAI/lenny-skills product-taste --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/RefoundAI/lenny-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/product-taste .agents/skills/product-taste && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "product-taste" agent skill from https://github.com/RefoundAI/lenny-skills/tree/main/skills/product-taste into .agents/skills/product-taste/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-taste", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add RefoundAI/lenny-skills --skill product-taste -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install RefoundAI/lenny-skills product-taste --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/RefoundAI/lenny-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/product-taste .cursor/skills/product-taste && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "product-taste" agent skill from https://github.com/RefoundAI/lenny-skills/tree/main/skills/product-taste into .cursor/skills/product-taste/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-taste", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/RefoundAI/lenny-skills.git --path skills/product-taste--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add RefoundAI/lenny-skills --skill product-taste -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install RefoundAI/lenny-skills product-taste --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/RefoundAI/lenny-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/product-taste .gemini/skills/product-taste && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "product-taste" agent skill from https://github.com/RefoundAI/lenny-skills/tree/main/skills/product-taste into .gemini/skills/product-taste/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-taste", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install RefoundAI/lenny-skills product-tasteInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add RefoundAI/lenny-skills --skill product-taste -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/RefoundAI/lenny-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/product-taste .github/skills/product-taste && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "product-taste" agent skill from https://github.com/RefoundAI/lenny-skills/tree/main/skills/product-taste into .github/skills/product-taste/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-taste", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add RefoundAI/lenny-skills --skill product-taste -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install RefoundAI/lenny-skills product-taste --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/RefoundAI/lenny-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/product-taste .opencode/skills/product-taste && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "product-taste" agent skill from https://github.com/RefoundAI/lenny-skills/tree/main/skills/product-taste into .opencode/skills/product-taste/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "product-taste", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
product-tasteHelp users build a professional eye for quality, articulate the reasoning behind successful product paradigms, and develop the conviction to make high-stakes decisions before data is available.
Product Taste is an agent skill from RefoundAI/lenny-skills. Help users build a professional eye for quality, articulate the reasoning behind successful product paradigms, and develop the conviction to make high-stakes decisions before data is available.
Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/artifacts.md` and `references/guest-insights.md`).
The repository describes itself as: 86 product management skills from Lenny's Podcast for Claude Code and AI agents. Hiring, user research, strategy, shipping, and more. The licence is MIT.
4 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 13598cc. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Product Taste loads about 2k tokens when it runs, and up to ~26k if it reads all its reference files. Until then it costs about 52 tokens; SKILL.md has 1,208 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from RefoundAI/lenny-skills at commit 13598cc, republished under its MIT licence (© RefoundAI). 1,208 words, ~2,017 tokens.
.claude/skills/product-taste/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.Develop a reliable internal compass to recognize and build world-class products.
Help the user with product taste and intuition using insights from 35 guests and posts across Lenny's Podcast and Newsletter.
Howie Liu: "I think to really understand the solution space of what's possible, you have to be in the details. I mean, literally, you can't just look at screenshots or a pre-recorded video of a new product feature. AI is something you have to play with, and ideally you're playing with both the packaged up app or solution that you've built with it, but you're also playing around directly with the underlying primitives who are using the models either via API or via a chat interface."
True intuition is built by playing directly with the underlying technology and APIs rather than observing demos. Understanding the raw boundaries of your ingredients allows you to imagine new possibilities.
Jessica Hische: "Most people are better at understanding the feelings and sensations that typography and logos give us than they give themselves credit for, because what we are as people are endless absorbers of patterns, and information, and all this kind of stuff as we move throughout the world. We don't take time to sit and digest it, but it's still coming in and getting logged, and so even as a non-designer, I think you can look at examples of logos where something's not quite right and be like, 'Something's not right here, I just don't know how to name it.'"
Develop a professional eye by explicitly naming the feelings triggered by specific design elements. Practice identifying broken patterns to understand what makes a visual work.
Josh Miller: "What we do at The Browser Company is we talk about optimizing feelings. How do we want to make someone feel on the other end of our software? Do we want to make them feel joy? Do we want to make them feel fast?"
Focus development on evoking specific human feelings like joy or speed rather than just moving quantitative metrics. Treat metrics as secondary tools to measure the success of an emotional experience.
Judd Antin: "One of my big mantras was, "We don't validate, we falsify. We are looking to be wrong." Many PMs, many designers are not in that place. They do not want to be wrong. They're looking to validate, and that's user-centered performance."
Use research to stress-test your internal beliefs and look for ways you might be wrong. Avoid research that merely validates existing decisions without the potential to change them.
Katie Dill: "I know there's this saying of it's growth versus quality, but quality is growth. And if you think about how you can make your product easier to use and more understandable, that will of course drive people to use it, and use more of it, and have a better experience with it that they'll want to talk about with others."
Superior aesthetics and usability are not just for show; they drive user activation and word-of-mouth. High-quality details make a product feel more approachable and trustworthy.
Karri Saarinen: "We actually believe that when you start building the thing you actually start realizing more how it should work and how it should be better. A lot of times with the teams we tell them, "Just put it there in, I don't know, the first week almost. After you have some designs in place or some design ideas, just put it into the app and ship it to production." It's only visible to us so we internally can test it out."
Ship early to internal teams and co-create with select customers to find real usage patterns. High quality is reached through constant iteration before final polishing.
See references/artifacts.md for the full list with details.
For all 36 sourced insights from 35 guests, see references/guest-insights.md
© RefoundAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 2 other files (references) in skills/product-taste of RefoundAI/lenny-skills.
Open the folder on GitHubat commit 13598cc
Product Taste next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Product Taste this skillRefoundAI/lenny-skills | 1.4k | — | ~2k | Automated safety check: Pass | MIT | |
| Tasteaffaan-m/ECC | 277k | 1 repos | ~3.8k | Automated safety check: Pass | MIT | |
| Tasteasgeirtj/system_prompts_leaks | 69k | — | ~506 | Automated safety check: Pass | CC0-1.0 | |
| Deepseek Reasonruvnet/ruflo | 74k | — | ~626 | Automated safety check: Notes | MIT | |
| Taste Distillationaffaan-m/ECC | 277k | — | ~2.3k | Automated safety check: Pass | MIT | |
| Taste Application Video Pipelineaffaan-m/ECC | 277k | — | ~4.9k | Automated safety check: Pass | MIT |
affaan-m/ECC
Creative-direction layer for music videos and short-form edits in the angelcore / cloud-trance / hyperpop family — a named-genre aesthetic vocabulary, mood + color + light system, beat-synced…
asgeirtj/system_prompts_leaks
Mandatory preflight for web frontend visual design. An agent skill from asgeirtj/system_prompts_leaks.
ruvnet/ruflo
Reasoning-mode completion against DeepSeek's deepseek-reasoner model (R1) via /v1/chat/completions.
affaan-m/ECC
Measure a set of reference videos into a reusable style pack - colour grade as a 3D LUT, cut rhythm as a shot-length distribution, hero stills, screen-blend overlay plates, and a text spec for a…
affaan-m/ECC
Generates video clips against a distilled style pack and cuts them into a finished edit, with grading, overlays, 3D props and numeric checks of the result.
sickn33/agentic-awesome-skills
MCP server exposing four cognitive harness modes (reasoning, code, anti-deception, memory).
RefoundAI/lenny-skills
Help users conduct high-impact customer interviews that move beyond surface-level feature requests to identify root emotional frustrations and specific causal triggers.
RefoundAI/lenny-skills
Help users master their personal output by shifting from reactive scheduling to intentional energy management, internal trigger mastery, and proactive boundary setting.
RefoundAI/lenny-skills
Help users reach their first moment of core value by optimizing the first-run experience, removing friction, and aligning product design with psychological triggers.
RefoundAI/lenny-skills
Help users identify unique distribution advantages and master the lifecycle of acquisition channels to build a sustainable engine for growth and retention.
RefoundAI/lenny-skills
Help users build functional product prototypes from natural language or visual mocks using AI coding tools.
RefoundAI/lenny-skills
Help users build robust infrastructure for measuring, monitoring, and iterating on AI product performance using human, code-based, and LLM-as-a-judge methodologies.
Help users build a professional eye for quality, articulate the reasoning behind successful product paradigms, and develop the conviction to make high-stakes decisions before data is available. Product Taste is an agent skill from RefoundAI/lenny-skills. Help users build a professional eye for quality, articulate the reasoning behind successful product paradigms, and develop the conviction to make high-stakes decisions before data is available.
Run `npx skills add RefoundAI/lenny-skills --skill product-taste -a claude-code`. Or copy the skill folder (skills/product-taste in RefoundAI/lenny-skills) into .claude/skills/product-taste in your project. Claude Code loads it when a task matches its description.
Run `npx skills add RefoundAI/lenny-skills --skill product-taste -a codex`. Or copy the skill folder (skills/product-taste in RefoundAI/lenny-skills) into .agents/skills/product-taste in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add RefoundAI/lenny-skills --skill product-taste -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/product-taste, .gemini/skills/product-taste, .github/skills/product-taste and .opencode/skills/product-taste in your project.
SKILL.md names no scripts, command-line tools or credentials: Product Taste is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Product Taste is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2k tokens (SKILL.md is roughly 8.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 24k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Product Taste: Taste (affaan-m/ECC, 277k stars), Taste (asgeirtj/system_prompts_leaks, 69k stars), Deepseek Reason (ruvnet/ruflo, 74k stars) and Taste Distillation (affaan-m/ECC, 277k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
RefoundAI (a GitHub organization) maintains it in RefoundAI/lenny-skills, which has 1,382 GitHub stars. The repository holds 76 skills in this directory. The repository was last updated on July 16, 2026.
Source: RefoundAI/lenny-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.