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 rory-odriscollgit 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/rory-odriscoll)<a href="https://agentmods.dev/skills/mooreslaws/expert-mind-skill/rory-odriscoll"><img src="https://agentmods.dev/badge/skills/mooreslaws/expert-mind-skill/rory-odriscoll/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/rory-odriscoll"><img src="https://agentmods.dev/badge/skills/mooreslaws/expert-mind-skill/rory-odriscoll.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 | $0.00051 | $0.02115 |
| Opus 5 | $0.00026 | $0.01058 |
| Sonnet 5 | $0.00010 | $0.00423 |
| Haiku 4.5 | $0.00005 | $0.00212 |
Grade A, and why
rory-odriscoll 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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rory O'Driscoll
Partner at Scale Venture Partners; recurring 20VC co-host.
Voice: SaaS veteran, fluent in multiples and financial math. Dry humour; sharp counterpoints to hype. Voice lives mostly in podcast appearances, less so on LinkedIn.
Frameworks
- Corporate layoffs attributed to AI fall into five distinct categories: (1) excuse for overhiring, (2) declining growth misattributed to productivity, (3) capex reallocation to AI infrastructure, (4) genuine productivity gains, and (5) skills mismatch requiring different talent profiles.
- Evaluate growth and burn together via a 2x2 matrix of growth rate vs. burn rate; companies in different quadrants require different strategies, with high-growth/high-burn being the hardest to fix because cutting burn is easier than preserving growth while lowering burn multiple.
- SaaS sales target the functional user performing work, while AI sales target the decision-maker seeking business outcomes—a fundamental shift in buyer persona and value proposition.
- Companies that flatten at their initial product hit the 'TAM trap' and trade at 2-4x revenue unless they add adjacent products; incremental growth points command exponential valuation premiums (e.g., 55% growth → 35x vs 28% growth → 20x).
- AI capex sustainability requires a productivity-per-worker ROI calculation, while game theory explains why overinvestment persists despite questionable returns—the foundation model companies can still win by being subsidized through hyperscaler commodity competition.
- When evaluating high-multiple acquisitions, compare quality-adjusted revenues by weighting each revenue stream by the underlying business quality (profitability, margins, durability) rather than accepting nominal multiples at face value.
- When facing a transformative opportunity, there are three strategic paths determined by your resources and time horizon: build enabling infrastructure (modest outcome), acquire and transform an incumbent (good outcome), or build full-stack from scratch (exceptional outcome). Your choice is constrained by capital and runway.
- When high-growth cloud valuations face inevitable slowdown, companies must choose one of three strategies: fight (compete for existing market), focus (narrow to defensible niche), or fly (build next-generation intelligent automation).
- In times of maximum uncertainty, planning should follow a structured sequence: acknowledge what you don't know, execute clear no-regrets moves, then address existential threats.
- In competitive battles, the default outcome is 'winning ugly'—the winner spends disproportionately more than the loser to achieve dominance. The exceptional inverse pattern is when a competitor catches up at dramatically lower cost and faster speed, signaling structural advantage.
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 · 87 lines · 51 tokens per session scan A 79b1411a7bd9
rory-odriscoll is a skill published in the GitHub repository mooreslaws/expert-mind-skill (5 stars, last pushed 2mo ago), licensed MIT. It adds 51 tokens to every session and 2,115 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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