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 KirKruglov/claude-skills-kit --skill north-star-metric-auditorgit clone --depth 1 https://github.com/KirKruglov/claude-skills-kitWrote 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/kirkruglov/claude-skills-kit/north-star-metric-auditor)<a href="https://agentmods.dev/skills/kirkruglov/claude-skills-kit/north-star-metric-auditor"><img src="https://agentmods.dev/badge/skills/kirkruglov/claude-skills-kit/north-star-metric-auditor/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/kirkruglov/claude-skills-kit/north-star-metric-auditor"><img src="https://agentmods.dev/badge/skills/kirkruglov/claude-skills-kit/north-star-metric-auditor.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 | $0.00078 | $0.01708 |
| Opus 5 | $0.00039 | $0.00854 |
| Sonnet 5 | $0.00016 | $0.00342 |
| Haiku 4.5 | $0.00008 | $0.00171 |
Grade A, and why
north-star-metric-auditor 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 — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
North Star Metric Auditor
This skill audits a North Star Metric (NSM) against 4 standard criteria and proposes 2–3 alternative candidates calibrated to the stated business model.
Input:
- Current NSM (metric name; optionally, how it is measured)
- Business model description (1–3 sentences: product type, revenue model, core user value)
- Optional: strategic focus area (growth / retention / monetisation)
Output:
- Markdown audit report: criteria table with 4 ratings, overall verdict (Strong / Acceptable / Weak), 2–3 alternatives with trade-offs, and a single actionable recommendation
Language Detection
Detect the user's language from their message:
- If Russian (or contains Cyrillic): respond in Russian
- If English (or other Latin-script language): respond in English
- If ambiguous: respond in the language of the trigger phrase used
Instructions
Step 1: Parse Input
- Extract the NSM name and measurement definition (if provided).
- If no NSM provided: stop and ask for it in the user's language (per Language Detection). EN: "Please share your current North Star Metric. Example: 'weekly active users'." RU: «Укажи свою текущую North Star Metric. Например: „количество еженедельно активных пользователей“.»
- Extract the business model description.
- If missing: ask one focused question before continuing to Step 4 (alternatives): "What is your product type and how do you earn revenue?"
- Extract optional strategic focus if stated (growth / retention / monetisation).
Step 2: Audit Against 4 Criteria
Evaluate the NSM against each criterion. For each, assign a rating (Strong, Acceptable, or Weak) and write 1–2 sentences of concrete justification tied to the stated NSM and business model.
- Customer Value: Does the metric capture the moment users receive the product's core value? A strong NSM rises when users succeed, not just when they open the app.
- Revenue Predictability: Does growth in this metric reliably predict long-term revenue growth or retention? Lagging financial output metrics score Weak here.
- Team Actionability: Can the product team directly influence this metric through product decisions? Metrics driven primarily by external factors (seasonality, macro) score lower.
- Leading Indicator: Is this an early signal of future success rather than a trailing summary of past results? Revenue and profit are classic lagging metrics and score Weak.
What ships with it
4 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.
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 · 138 lines · 78 tokens per session scan A e9ff9c188957
north-star-metric-auditor is a skill published in the GitHub repository KirKruglov/claude-skills-kit (18 stars, last pushed 1mo ago), licensed MIT. It adds 78 tokens to every session and 1,708 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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