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 NOMARJ/sigil --skill growth-metricsgit clone --depth 1 https://github.com/NOMARJ/sigilWrote 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/nomarj/sigil/growth-metrics)<a href="https://agentmods.dev/skills/nomarj/sigil/growth-metrics"><img src="https://agentmods.dev/badge/skills/nomarj/sigil/growth-metrics/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/nomarj/sigil/growth-metrics"><img src="https://agentmods.dev/badge/skills/nomarj/sigil/growth-metrics.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 | $0.00049 | $0.00776 |
| Opus 5 | $0.00024 | $0.00388 |
| Sonnet 5 | $0.00010 | $0.00155 |
| Haiku 4.5 | $0.00005 | $0.00078 |
Grade A, and why
growth-metrics 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 10d 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 — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Growth Metrics
Pre-requisites
Invoke business-context skill. Read GTM spec for this product.
Metrics are motion-specific
Using vanity metrics for the wrong motion is worse than no metrics. Track what the motion requires.
| Motion | Leading indicators | Lagging |
|---|---|---|
| Developer-led | GitHub stars, forks, issues opened, installs | Paid tier conversions |
| Content-led | Organic impressions, AI search appearances, backlinks | Trial signups |
| Community-led | Community mentions, helpful replies cited, DMs asking for access | Signups from community |
| Relationship-led | Conversations initiated, demos booked, warm intros made | Proposals sent, pipeline value |
Per-product metrics
Sigil (developer-led)
Weekly:
- GitHub stars (target: +10/week after launch)
- GitHub forks (target: +5/week)
- Issues opened (signal of engagement — quality > quantity)
- HN/Reddit mentions
Monthly:
- Install count from package manager
- Pull requests from external contributors
- Security community citations
Threshold for motion pivot: 3 months post-launch, <100 stars and 0 enterprise inquiries → review motion and channel, not just content.
InstaIndex (content-led)
Weekly:
- GSC impressions for target AEO keywords
- Position for "how to get indexed by AI search" variants
- New backlinks (ahrefs/SEMrush)
- Signups from organic
Monthly:
- AI search appearance count (perplexity.ai, chatgpt search queries)
- Blog posts published vs plan
- Paid conversion rate from organic
Threshold for motion pivot: 6 months, <500 organic monthly visits → review AEO targeting and content quality.
Operable (relationship-led)
Weekly:
- LinkedIn post impressions and comments (investment ops specific)
- Warm conversations initiated (email/LinkedIn/in person)
- Demos booked
Monthly:
- Pipeline value (deals in consideration)
- Referrals from existing network
- Event attendance + follow-up rate
Threshold: 6 months, 0 pipeline conversations → the network path isn't working, consider whether a different entry point (conference talk, written case study) unlocks it.
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.
- 10d ago First seen · 118 lines · 49 tokens per session scan A de40daedce51
growth-metrics is a skill published in the GitHub repository NOMARJ/sigil (5 stars, last pushed 4d ago), licensed Apache-2.0. It adds 49 tokens to every session and 776 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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