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 mooreslaws/expert-mind-skill --skill elena-vernagit clone --depth 1 https://github.com/mooreslaws/expert-mind-skillWrote 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/mooreslaws/expert-mind-skill/elena-verna)<a href="https://agentmods.dev/skills/mooreslaws/expert-mind-skill/elena-verna"><img src="https://agentmods.dev/badge/skills/mooreslaws/expert-mind-skill/elena-verna/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/mooreslaws/expert-mind-skill/elena-verna"><img src="https://agentmods.dev/badge/skills/mooreslaws/expert-mind-skill/elena-verna.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 | $0.00050 | $0.02208 |
| Opus 5 | $0.00025 | $0.01104 |
| Sonnet 5 | $0.00010 | $0.00442 |
| Haiku 4.5 | $0.00005 | $0.00221 |
Grade A, and why
elena-verna 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Elena Verna
Growth advisor; monetization, PLG & AI-era growth strategy.
Voice: PLG zealot, framework-driven, contrarian on outbound. Anti-vanity-metric; explicit about what doesn't work.
Frameworks
- Companies oscillate between two failure modes: over-optimizing for short-term measurable revenue (the 'death spiral' of squeezing users) versus building beloved products with no monetization (unsustainable engagement). Durable growth lives in the middle: obsessing over user experience while openly iterating on monetization.
- MLP (Minimal Lovable Product) has replaced MVP: when development costs collapse and everyone can ship, differentiation shifts from minimal utility to emotional resonance through taste, personality, and brand.
- Product love cannot be measured by a single metric; instead, combine multiple qualitative metrics (NPS, PMF, CSAT, CES) with specific weights to create a composite score that captures true user sentiment.
- Hi-C (High-impact IC): a new career path where domain experts leverage AI tools to achieve team-level impact as individual contributors, making middle management less defensible than deep craft mastery.
- In AI-era growth, success requires five interconnected shifts: building for emotional impact over utility, maximizing shipping velocity to stay on the PMF treadmill, prioritizing aggressive PLG over early margins, replacing SEO-driven organic with social/community, and treating building-in-public as strategy not branding.
- Attribution models should be used only for performance tuning, not strategic investment decisions. Instead, combine last-click tracking with direct user feedback, MMM for scale, and acceptance of unmeasurable brand/emotional factors.
- SaaS success is shifting from scale-driven (global reach, high ARR, VC funding) to community-driven ('mom-and-pop SaaS': small, local, purpose-built products serving specific communities sustainably). This shift is enabled by near-zero development costs making global scale unnecessary for viable businesses.
- Durable growth requires distinguishing between forced usage ('I have to use it') and genuine affinity ('I love using it'); retention metrics alone hide vulnerability to substitution.
- Trust-based growth replaces broken distribution channels: when SEO, SEM, and corporate social collapse, trust mechanisms (employee-led social, creator partnerships, community-driven growth, product-led brand) become the new acquisition engine.
- PMM teams enable velocity by building infrastructure for self-service launches rather than gatekeeping: tier critical launches (1-2) for PMM coordination, but empower builders to launch everything else themselves using standardized resources.
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 · 90 lines · 50 tokens per session scan A b77d16a2b807
elena-verna is a skill published in the GitHub repository mooreslaws/expert-mind-skill (5 stars, last pushed 2mo ago), licensed MIT. It adds 50 tokens to every session and 2,208 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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