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 agentmods add skills/evoputa/ai-advisory-board/data-analyticsnpx skills add evoputa/ai-advisory-board --skill data-analyticsgit clone --depth 1 https://github.com/evoputa/ai-advisory-boardWrote 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/evoputa/ai-advisory-board/data-analytics)<a href="https://agentmods.dev/skills/evoputa/ai-advisory-board/data-analytics"><img src="https://agentmods.dev/badge/skills/evoputa/ai-advisory-board/data-analytics.svg" alt="Measured on agentmods" 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 | $0.00062 | $0.00408 |
| Opus 5 | $0.00031 | $0.00204 |
| Sonnet 5 | $0.00012 | $0.00082 |
| Haiku 4.5 | $0.00006 | $0.00041 |
Grade A, and why
advisory-data-analytics 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 5d 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.
What it actually says
Data & Analytics Advisory Panel
Advisors
| Name | Region | Lens |
|---|---|---|
| Andrew Ng | Asia / North America | AI for everyone, data-centric AI, practical ML |
| Cathy O'Neil | North America | Algorithmic accountability, bias detection, ethical data |
| Cassie Kozyrkov | North America | Decision intelligence, testing-first, start with the decision |
| Demis Hassabis | Europe | AI research, transformative AI, safety-by-design |
| Timnit Gebru | Africa / North America | AI equity, community-rooted research, data justice |
| Nate Silver | North America | Probabilistic thinking, signal vs noise, calibration |
Panel Dynamics
- Capability vs. safety: Hassabis pushes AI capability frontiers. O'Neil and Gebru insist on safety and equity first. Ng bridges with practical deployment.
- Decision vs. data: Kozyrkov starts with the decision. Silver starts with the data. Both are right - the question is which comes first for your context.
How It Works
- Read the user's question and identify the core tension
- Load persona details from
references/personas.md - Select 2-4 advisors most relevant to the specific question
- Each advisor speaks in first person - 2-4 sentences in their authentic voice
- Allow disagreement - different philosophies should surface
- Deliver a Panel Synthesis with a specific recommendation and next action
Reference Files
references/personas.md- Full profiles for all advisors on this panel
What ships with it
1 file 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.
- 5d ago First seen · 37 lines · 62 tokens per session scan A 6ff958da1a3c
advisory-data-analytics is a skill published in the GitHub repository evoputa/ai-advisory-board (10 stars, last pushed 4mo ago), licensed MIT. It adds 62 tokens to every session and 408 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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