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 uthumany/uthy-legacy-os --skill adoption-funnelgit clone --depth 1 https://github.com/uthumany/uthy-legacy-osWrote 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/uthumany/uthy-legacy-os/adoption-funnel)<a href="https://agentmods.dev/skills/uthumany/uthy-legacy-os/adoption-funnel"><img src="https://agentmods.dev/badge/skills/uthumany/uthy-legacy-os/adoption-funnel/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/uthumany/uthy-legacy-os/adoption-funnel"><img src="https://agentmods.dev/badge/skills/uthumany/uthy-legacy-os/adoption-funnel.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 | $0.00028 | $0.01087 |
| Opus 5.5 | $0.00011 | $0.00435 |
| Sonnet 5.5 | $0.00006 | $0.00217 |
| Haiku 4.5 | $0.00003 | $0.00109 |
Grade A, and why
adoption-funnel 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 2mo 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Adoption Funnel
Overview
You shipped it, but nobody's using it. Feature adoption analysis helps you understand why — is it discoverability, comprehension, motivation, or the wrong feature? This skill covers funnel analysis, activation metrics, and adoption improvement tactics.
When to Use
- A shipped feature has < expected usage
- You need to understand where users drop off in the adoption journey
- Designing activation flows for new features
- You want to improve feature engagement systematically
- Don't use for: core product adoption (broader analysis needed), one-day-old features (too early to measure)
Instructions
1. Define the Adoption Funnel
Map the user's journey from awareness to ongoing use:
- Awareness: User knows the feature exists
- Discovery: User finds the feature
- Understanding: User knows what it does and why to use it
- First use: User tries the feature for the first time
- Value realization: User gets value from the feature
- Continued use: User comes back and uses it again
2. Measure Each Stage
For each stage, instrument and measure:
- Awareness: % of users who saw the announcement/in-app notification
- Discovery: % who navigated to the feature's location
- Understanding: % who clicked/opened the feature
- First use: % who completed the primary action
- Value realization: % who reached a success milestone
- Continued use: % who used it again within 7 days
3. Identify the Drop-off
Where do most users disappear?
- 🔴 Awareness → Discovery: Visibility problem (need better placement/announcement)
- 🔴 Discovery → Understanding: Comprehension problem (need better labeling/onboarding)
- 🔴 Understanding → First use: Motivation problem (need better value prop or lower friction)
- 🔴 First use → Value realization: UX problem (feature is hard to use)
- 🔴 Value → Continued use: Retention problem (feature doesn't deliver ongoing value)
4. Design Improvements
Based on the drop-off:
- Visibility: In-app announcement, badge/tooltip, email campaign
- Comprehension: Better copy, short video, tooltip on first hover
- Motivation: Value prop showcase, "users who do X get Y% better results"
- UX: Reduce steps, add defaults, improve feedback
- Retention: Email reminders, progress tracking, social proof
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.
- 2mo ago First seen · 110 lines · 28 tokens per session scan A 8afab01287e7
adoption-funnel is a skill published in the GitHub repository uthumany/uthy-legacy-os (5 stars, last pushed 5mo ago), licensed MIT. It adds 28 tokens to every session and 1,087 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-31.
adoption-funnel compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| adoption-funneluthumany/uthy-legacy-os | Skill | 5 | 5mo ago | MIT | A | 28 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | today | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 99k | today | Apache-2.0 | A | 19 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 314k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| chat-pet-sprite-creationmicrosoft/vscode | Skill | 195k | today | MIT | A | 53 | Claude Code, Codex |