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 fzfclee/consulting-skills --skill north-star-metricgit clone --depth 1 https://github.com/fzfclee/consulting-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/fzfclee/consulting-skills/north-star-metric)<a href="https://agentmods.dev/skills/fzfclee/consulting-skills/north-star-metric"><img src="https://agentmods.dev/badge/skills/fzfclee/consulting-skills/north-star-metric/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/fzfclee/consulting-skills/north-star-metric"><img src="https://agentmods.dev/badge/skills/fzfclee/consulting-skills/north-star-metric.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 | $0.00053 | $0.00738 |
| Opus 5 | $0.00026 | $0.00369 |
| Sonnet 5 | $0.00011 | $0.00148 |
| Haiku 4.5 | $0.00005 | $0.00074 |
Grade A, and why
north-star-metric 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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
North Star Metric
Use this skill to run North Star Metric as a practical consulting method, not as a generic framework explanation.
Method Notes
- The metric should reflect recurring customer value and be a leading indicator of growth.
- Add input metrics and guardrail metrics.
Required Inputs
Collect or infer these inputs before execution:
- business model
- user value proposition
- growth goal
- available metrics
If an input is missing, do not block automatically. Mark it as missing, state the assumption used, and add a validation action.
When Not To Use
Do not use when customer value, product scope, or strategic objective is unclear, or when one metric would hide harm across segments. Pair the north star with explicit guardrails.
Adjacent Methods
metrics-tree: connect an outcome to input drivers and guardrails.balanced-scorecard: manage several strategic perspectives rather than one value metric.
Step-by-Step Execution
| Step | Required input | How to execute | Output |
|---|---|---|---|
| Define core value | Product/service value proposition and user segment. | State the recurring customer value the product should create. | Core value statement. |
| Propose NSM | Core value, growth model, retention logic. | Choose one metric that captures delivered value and predicts growth. | North Star metric candidate. |
| Map input metrics | User behaviors and business drivers. | Identify measurable behaviors that drive the NSM. | Input metric tree. |
| Add guardrails | Quality, margin, risk, user trust, support burden. | Define counter-metrics that prevent gaming or regression. | Guardrail set. |
| Validate usability | Data availability, team ownership, actionability. | Check whether teams can influence and review the metric. | NSM operating plan. |
Output Template
### 1. Core Value
User:
Value event:
Frequency:
Business linkage:
### 2. North-Star Candidate
Metric:
Formula:
Why it reflects value:
Manipulation risk:
### 3. Input Metrics And Guardrails
| Metric | Type | Mechanism | Owner | Threshold |
|---|---|---|---|---|
| | | | | |
### 4. Operating Plan
| Review | Cadence | Decision | Validation / revision trigger |
|---|---|---|---|
| | | | |
### Evidence And Next Decision
- Confirmed facts:
- Assumptions:
- Missing evidence:
- Next action, owner, and timing:
- Expected signal and decision threshold:
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 · 87 lines · 53 tokens per session scan A 60c3d8c30cea
north-star-metric is a skill published in the GitHub repository fzfclee/consulting-skills (4 stars, last pushed 24d ago), licensed Apache-2.0. It adds 53 tokens to every session and 738 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 2026-08-31.
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