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 wdavidturner/product-skills --skill hierarchy-of-engagementgit clone --depth 1 https://github.com/wdavidturner/product-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/wdavidturner/product-skills/hierarchy-of-engagement)<a href="https://agentmods.dev/skills/wdavidturner/product-skills/hierarchy-of-engagement"><img src="https://agentmods.dev/badge/skills/wdavidturner/product-skills/hierarchy-of-engagement/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/wdavidturner/product-skills/hierarchy-of-engagement"><img src="https://agentmods.dev/badge/skills/wdavidturner/product-skills/hierarchy-of-engagement.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 | $0.00084 | $0.01095 |
| Opus 5 | $0.00042 | $0.00548 |
| Sonnet 5 | $0.00017 | $0.00219 |
| Haiku 4.5 | $0.00008 | $0.00110 |
Grade A, and why
hierarchy-of-engagement 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hierarchy of Engagement
What It Is
The Hierarchy of Engagement is a three-level framework for building consumer products that retain users and create defensibility. The core insight: retention comes from making the product better the more you use it, so users have more to lose by leaving.
Most consumer products fail not because they lack users, but because they lack retention. Getting someone to sign up is one thing; getting them to stay is everything. This framework provides a systematic approach to building products where engagement compounds over time.
The key shift: Move from asking "How do we get more users?" to asking "How do we make each user's experience improve the more they use us?"
Response Posture
- Apply the framework directly to the user's product.
- Never mention the repository, skills, SKILL.md, patterns, or references.
- Do not run tools or read files; answer from the framework.
- Avoid process/meta commentary; respond as a retention-focused product operator.
When to Use It
Use the Hierarchy of Engagement when you need to:
- Define your North Star metric (what action matters most?)
- Improve retention in a consumer or social product
- Build product stickiness beyond features alone
- Create switching costs that protect against competitors
- Design your onboarding/activation flow
- Evaluate product-market fit through engagement quality
- Prioritize features that drive compounding value
When Not to Use It
Don't apply this framework when:
- Building B2B enterprise software (different retention dynamics)
- The product is transactional by nature (one-time purchase)
- There's no meaningful "use over time" pattern
- You're optimizing for viral acquisition before proving retention
- Your product has no user-generated content or personalization opportunity
Patterns
Detailed examples showing how to apply the Hierarchy of Engagement correctly. Each pattern shows a common mistake and the correct approach.
What ships with it
15 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.
- patterns/_template.md 460 B
- patterns/activation-without-education.md 1.9 KB
- patterns/anonymous-users.md 1.9 KB
- patterns/benefit-doesnt-accrue.md 1.8 KB
- patterns/comparing-to-mature-products.md 1.9 KB
- patterns/evernote-trap.md 2.0 KB
- patterns/forcing-level-three.md 2.0 KB
- patterns/geographic-spray.md 1.8 KB
- patterns/no-mounting-loss.md 1.9 KB
- patterns/pinterest-pinning.md 2.2 KB
- patterns/skipping-level-one.md 1.9 KB
- patterns/vanity-engagement.md 1.8 KB
- patterns/wrong-core-action.md 1.7 KB
- patterns/youtube-subscribe-example.md 1.8 KB
- references/hierarchy-of-engagement-playbook.md 9.8 KB
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 · 96 lines · 84 tokens per session scan A fcb6a1a261d9
hierarchy-of-engagement is a skill published in the GitHub repository wdavidturner/product-skills (20 stars, last pushed 7mo ago), licensed MIT. It adds 84 tokens to every session and 1,095 once invoked, about $0.0004 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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