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 behavioral-product-designgit 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/behavioral-product-design)<a href="https://agentmods.dev/skills/liqiongyu/lenny_skills_plus/behavioral-product-design"><img src="https://agentmods.dev/badge/skills/liqiongyu/lenny_skills_plus/behavioral-product-design/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/behavioral-product-design"><img src="https://agentmods.dev/badge/skills/liqiongyu/lenny_skills_plus/behavioral-product-design.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 | $0.00021 | $0.02144 |
| Opus 5 | $0.00010 | $0.01072 |
| Sonnet 5 | $0.00004 | $0.00429 |
| Haiku 4.5 | $0.00002 | $0.00214 |
Grade A, and why
behavioral-product-design 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 — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Behavioral Product Design
Scope
Covers
- Turning a desired user behavior into an executable design + experiment plan
- Diagnosing behavior using barriers/drivers (motivation, ability/friction, uncertainty, habit, context)
- Designing behavioral interventions (e.g., defaults, commitment devices, loss aversion/progress, reducing uncertainty) with ethical guardrails
- Producing decision-ready artifacts a PM/Design/Eng team can build and test
When to use
- “Help me apply behavioral science / behavioral economics to this flow.”
- “We need to improve retention / activation / onboarding completion.”
- “Design a streak / habit loop / reminder system (without being spammy).”
- “Users procrastinate (present bias). How do we get them to do the thing?”
- “People stick with the status quo. How do we drive switching/adoption?”
- “Users are uncertain / anxious. How do we reduce uncertainty and move them forward?”
When NOT to use
- You need upstream strategy first (vision, positioning, roadmap). Use
defining-product-vision/prioritizing-roadmap. - You can’t name the target user + target behavior + success metric (this becomes generic advice).
- The goal is to create dark patterns (deception, coercion, addiction, hidden costs). Don’t do this.
- The domain is regulated/high-stakes (medical, financial advice, minors). Require domain/legal review and tighter safeguards.
- You need to design an onboarding flow without a behavioral science lens -> use
user-onboarding. - You need to analyze retention/engagement metrics and cohort data, not design interventions -> use
retention-engagement. - You need to design a survey or research study to collect user data -> use
designing-surveys. - You need to test an existing design with real users -> use
usability-testing.
Inputs
Minimum required
- Product context + target user segment
- The target behavior (what user action you want more of, in what context)
- Baseline funnel/retention metrics (even rough) + where the drop happens
- Constraints: platform (web/mobile), notification channels, brand/tone, time box
- Existing evidence: user research notes, support tickets, analytics, session replays (if any)
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 537 B
- eval/SHOWCASE.md 4.2 KB
- eval/with_skill.md 37 KB
- eval/without_skill.md 13 KB
- README.md 1.7 KB
- references/CHECKLISTS.md 1.9 KB
- references/EXAMPLES.md 1.5 KB
- references/INTAKE.md 1.5 KB
- references/RUBRIC.md 2.9 KB
- references/SOURCE_SUMMARY.md 1.2 KB
- references/TEMPLATES.md 2.7 KB
- references/WORKFLOW.md 2.9 KB
- skillpack.json 399 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.
- 12d ago First seen · 140 lines · 21 tokens per session scan A 95c52f3662ec
behavioral-product-design is a skill published in the GitHub repository liqiongyu/lenny_skills_plus (52 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 21 tokens to every session and 2,144 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.
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