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 liqiongyu/lenny_skills_plus --skill product-taste-intuitiongit clone --depth 1 https://github.com/liqiongyu/lenny_skills_plusWrote 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/liqiongyu/lenny_skills_plus/product-taste-intuition)<a href="https://agentmods.dev/skills/liqiongyu/lenny_skills_plus/product-taste-intuition"><img src="https://agentmods.dev/badge/skills/liqiongyu/lenny_skills_plus/product-taste-intuition/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/liqiongyu/lenny_skills_plus/product-taste-intuition"><img src="https://agentmods.dev/badge/skills/liqiongyu/lenny_skills_plus/product-taste-intuition.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00024 | $0.02045 |
| Opus 5 | $0.00012 | $0.01022 |
| Sonnet 5 | $0.00005 | $0.00409 |
| Haiku 4.5 | $0.00002 | $0.00204 |
Grade A, and why
product-taste-intuition 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 9d 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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Taste & Intuition
Scope
Covers
- Developing product taste (what "good" looks like) through deliberate exposure, observation, and critique
- Using intuition as a hypothesis generator (turning "gut feel" into testable hypotheses)
- Building a repeatable practice loop (exposure hours → analysis → validation → updated taste rules)
When to use
- "Help me improve my product taste / product sense."
- "Calibrate what ‘good onboarding’ looks like for our product category."
- "Turn my intuition about this flow into testable hypotheses."
- "Create a structured way to study great products and extract patterns."
When NOT to use
- You need to decide what to build (use
problem-definition,prioritizing-roadmap, ordefining-product-vision). - You need user evidence first (use
conducting-user-interviewsorusability-testing). - You want aesthetic critique only (this is product experience: value, UX, clarity, trust, speed--not just visuals).
- You can’t name any target user, use case, or the "taste domain" you want to improve (we’ll narrow first).
- You want to run a structured design review of your own product’s UI/UX (use
running-design-reviews). - You want to dogfood your own product and capture feedback (use
dogfooding). - You want to develop a PM’s skills through coaching conversations (use
coaching-pms). - You need a competitive landscape analysis or market positioning (use
competitive-analysis).
Inputs
Minimum required
- Taste domain to improve (pick 1): onboarding, activation, navigation/IA, editor/workflow, pricing/packaging UX, notifications, retention loops, trust/safety, performance/latency feel, copy/voice
- Target user + top job-to-be-done for that domain
- 3–10 benchmark products/experiences to study (or "unknown—please propose")
- Time box (e.g., 60–120 min sprint; or a 2–4 week practice plan)
- Constraints (platform, geography, accessibility, compliance, brand voice, etc.)
Missing-info strategy
- Ask up to 5 questions from references/INTAKE.md.
- If inputs remain missing, proceed with explicit assumptions and provide 2 scope options (narrow vs broad).
What ships with it
13 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.
- eval/eval_config.json 1.7 KB
- eval/SHOWCASE.md 5.2 KB
- eval/with_skill.md 45 KB
- eval/without_skill.md 17 KB
- README.md 1.7 KB
- references/CHECKLISTS.md 1.7 KB
- references/EXAMPLES.md 1.5 KB
- references/INTAKE.md 1.5 KB
- references/RUBRIC.md 3.2 KB
- references/SOURCE_SUMMARY.md 1.4 KB
- references/TEMPLATES.md 2.7 KB
- references/WORKFLOW.md 1.8 KB
- skillpack.json 393 B
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.
- 9d ago First seen · 135 lines · 24 tokens per session scan A aa0d0d7b3d41
product-taste-intuition is a skill published in the GitHub repository liqiongyu/lenny_skills_plus (52 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 24 tokens to every session and 2,045 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 2026-09-03.
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