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 cnfeat/top-pm-skills --skill metrics-frameworkgit clone --depth 1 https://github.com/cnfeat/top-pm-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/cnfeat/top-pm-skills/metrics-framework)<a href="https://agentmods.dev/skills/cnfeat/top-pm-skills/metrics-framework"><img src="https://agentmods.dev/badge/skills/cnfeat/top-pm-skills/metrics-framework/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/cnfeat/top-pm-skills/metrics-framework"><img src="https://agentmods.dev/badge/skills/cnfeat/top-pm-skills/metrics-framework.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 | $0.00062 | $0.01147 |
| Opus 5 | $0.00031 | $0.00574 |
| Sonnet 5 | $0.00012 | $0.00229 |
| Haiku 4.5 | $0.00006 | $0.00115 |
Grade A, and why
metrics-framework 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 6d 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 — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Metrics Framework Skill
This skill builds a complete metrics framework tailored to a product or business. It connects the North Star metric to actionable leading indicators, making it clear which metrics to track, which to optimise, and how they relate to each other.
Required Inputs
Ask the user for these if not provided:
- Product or business description (one paragraph is enough)
- Business model (SaaS / Marketplace / E-commerce / Consumer app / B2B / Other)
- Stage (Pre-PMF / Growth / Scale / Mature)
- Framework preference (if they have one): North Star + Metric Tree / AARRR / HEART / OKRs / Custom
- Primary goal this quarter (e.g. grow activation, reduce churn, increase revenue)
If no framework preference is given, recommend the best fit based on stage and business model.
Output Structure
1. Framework Recommendation (if not specified)
Explain in 2–3 sentences why you're recommending this framework for their context.
2. North Star Metric
[Metric Name]: [Definition — exactly what is measured and how]
Why this is the right North Star for this business: [2–3 sentences. It should reflect customer value delivered, not just revenue or activity. Explain what behaviour it captures and why maximising it correlates with long-term business health.]
How to measure it: [Formula or data source] Current baseline: [Leave as [ADD BASELINE] for user to fill] Target: [Leave as [ADD TARGET] for user to fill]
3. Metric Tree
Show how supporting metrics roll up to the North Star. Format as a hierarchy:
[North Star Metric]
├── [Driver 1: e.g. Acquisition]
│ ├── [L2 metric: e.g. Organic signups / week]
│ └── [L2 metric: e.g. Paid CAC by channel]
├── [Driver 2: e.g. Activation]
│ ├── [L2 metric: e.g. % users completing onboarding within 7 days]
│ └── [L2 metric: e.g. Time to first value action]
└── [Driver 3: e.g. Retention]
├── [L2 metric: e.g. Day 30 retention rate]
└── [L2 metric: e.g. Feature adoption depth]
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.
- 6d ago First seen · 112 lines · 62 tokens per session scan A 7ea057addff0
metrics-framework is a skill published in the GitHub repository cnfeat/top-pm-skills (48 stars, last pushed 2mo ago), licensed MIT. It adds 62 tokens to every session and 1,147 once invoked, about $0.0003 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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