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 ljucask/pureinn-product-development --skill pm-kpisgit clone --depth 1 https://github.com/ljucask/pureinn-product-developmentWrote 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/ljucask/pureinn-product-development/pm-kpis)<a href="https://agentmods.dev/skills/ljucask/pureinn-product-development/pm-kpis"><img src="https://agentmods.dev/badge/skills/ljucask/pureinn-product-development/pm-kpis/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/ljucask/pureinn-product-development/pm-kpis"><img src="https://agentmods.dev/badge/skills/ljucask/pureinn-product-development/pm-kpis.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 | $0.00038 | $0.04410 |
| Opus 5 | $0.00019 | $0.02205 |
| Sonnet 5 | $0.00008 | $0.00882 |
| Haiku 4.5 | $0.00004 | $0.00441 |
Grade A, and why
pm-kpis 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 11d 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 — 437 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PM - KPIs & Metrics Framework
Agent mode (--agent)
Supports --agent: runs autonomously in a subagent, drafts the artifact from existing inputs, and returns a short summary + coverage note.
- No flag → interactive (default); if inputs are heavy, offer agent mode.
--agent→ obey. First check inputs are complete. Anything missing: do NOT invent it - mark[ASSUMED - what/why]in the output and summary. Never hallucinate to fill a gap.
What this skill does
Translates the business model and validated problem into a structured measurement framework:
- North Star Metric - the single metric that best captures value delivered to customers
- AARRR Funnel Metrics - acquisition through revenue measurement chain
- OKRs - Objectives and Key Results for the first 2 quarters post-launch
This is a decision skill, not a data skill. Claude derives metrics from the business model logic and validates their coherence. No invented benchmarks without basis.
Dependencies
Recommended before running:
pm-business-model- revenue model and customer relationship type determine the right metricspm-problem-validation- validated pains define what "value delivered" means (North Star input)pm-personas- customer behavior patterns inform leading indicators
Produces artifacts used by:
pm-prd- KPIs are a required PRD sectionpm-business-case- metrics inform financial model assumptions (conversion rates, retention)pm-product-roadmap- success metrics anchor roadmap phases
Step 0: Current state check
Check for existing artifacts:
- KPIs & Metrics Framework
- North Star Metric definition
- OKRs
Also check: does a Business Model Canvas exist? Cross-reference the revenue model type - subscription SaaS needs different metrics than marketplace or usage-based. Does a Problem Validation Summary exist? The North Star must connect to the core validated problem.
Look for: North Star that measures activity not value (e.g., "DAU" vs. "properties actively managed"), AARRR metrics without conversion rate benchmarks, OKRs without measurable Key Results (vague KRs like "improve retention" are invalid), missing leading indicators.
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.
- 11d ago First seen · 437 lines · 38 tokens per session scan A 98ac62d2a048
pm-kpis is a skill published in the GitHub repository ljucask/pureinn-product-development (2 stars, last pushed yesterday), licensed MIT. It adds 38 tokens to every session and 4,410 once invoked, about $0.0002 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 2026-08-31.
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