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 product-health-reviewgit 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/product-health-review)<a href="https://agentmods.dev/skills/uthumany/uthy-legacy-os/product-health-review"><img src="https://agentmods.dev/badge/skills/uthumany/uthy-legacy-os/product-health-review/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/product-health-review"><img src="https://agentmods.dev/badge/skills/uthumany/uthy-legacy-os/product-health-review.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 | $0.00031 | $0.00938 |
| Opus 5.5 | $0.00012 | $0.00375 |
| Sonnet 5.5 | $0.00006 | $0.00188 |
| Haiku 4.5 | $0.00003 | $0.00094 |
Grade A, and why
product-health-review 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 — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Health Review (Weekly, 30 min)
Overview
A weekly product health review keeps you from being surprised by trends that develop over weeks. In 30 minutes, you check metrics, user feedback, support trends, and active projects — then decide what needs attention.
When to Use
- Weekly as a regular product health check
- When you need a quick pulse on product performance
- Before stakeholder status meetings or exec reviews
- After shipping a major feature (increase frequency)
- Don't use for: deep-dive analysis (use individual measuring skills), daily standups (different format)
Instructions
This is a 30-minute weekly ritual. Do it at the same time each week. The format is consistent so the team builds a shared understanding of product health over time. Run each step sequentially. If a step reveals a critical issue, escalate immediately rather than waiting for the end.
Step 1: Metrics Check (5 min)
Load the metrics-framework skill. Check:
- North Star metric: Trending up, down, or flat this week?
- Key input metrics: What's driving the North Star change?
- Counter-metrics: Any unexpected degradation?
- Red flags: Any metric in 🔴 territory?
Look for: Week-over-week changes, not day-to-day noise. A 5% drop for 3 consecutive weeks = trend.
Step 2: User Feedback Scan (5 min)
Load the feedback-analysis skill. Scan:
- Support ticket volume: Up or down? Any new themes?
- App store reviews: Recent ratings, common complaints
- In-app feedback: NPS changes, survey responses
- Social mentions: Are people talking about us? What are they saying?
Look for: New patterns that emerged this week. "3 users mentioned X" = worth noting.
Step 3: Support Trends (5 min)
- Ticket volume vs. baseline: Normal? Spike?
- Top categories: What are most tickets about this week?
- Escalations: Any critical issues?
- Response time: Within SLA?
Look for: Correlation with recent releases or changes.
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 · 104 lines · 31 tokens per session scan A 2bd054e522b8
product-health-review is a skill published in the GitHub repository uthumany/uthy-legacy-os (5 stars, last pushed 5mo ago), licensed MIT. It adds 31 tokens to every session and 938 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.
product-health-review compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| product-health-reviewuthumany/uthy-legacy-os | Skill | 5 | 5mo ago | MIT | A | 31 | 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 |