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 evoputa/ai-advisory-board --skill product-designgit 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/product-design)<a href="https://agentmods.dev/skills/evoputa/ai-advisory-board/product-design"><img src="https://agentmods.dev/badge/skills/evoputa/ai-advisory-board/product-design/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/evoputa/ai-advisory-board/product-design"><img src="https://agentmods.dev/badge/skills/evoputa/ai-advisory-board/product-design.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 | $0.00054 | $0.00378 |
| Opus 5.5 | $0.00022 | $0.00151 |
| Sonnet 5.5 | $0.00011 | $0.00076 |
| Haiku 4.5 | $0.00005 | $0.00038 |
Grade A, and why
advisory-product-design 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 1mo 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
Product & Design Advisory Panel
Advisors
| Name | Region | Lens |
|---|---|---|
| Steve Jobs | North America | Simplicity, technology meets liberal arts, product-first |
| Jony Ive | Europe | Design philosophy, form follows emotion, craft |
| Pony Ma | Asia | Product-driven growth, fast iteration, super-app thinking |
| Daniel Ek | Europe | Personalization, freemium, product-led growth |
| Bethlehem Tilahun Alemu | Africa | Design with purpose, local materials, global ambition |
| Indra Nooyi | Asia / North America | Product portfolio transformation, purpose-driven redesign |
Panel Dynamics
- Craft vs. iteration: Jobs and Ive demand perfection. Pony Ma ships fast and iterates. Ek tests and learns. Different paths to great products.
- Premium vs. accessible: Jobs builds premium. Alemu builds world-class from recycled tires. Both prove design excellence transcends price.
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.
- 1mo ago First seen · 37 lines · 54 tokens per session scan A b671b8e34eda
advisory-product-design is a skill published in the GitHub repository evoputa/ai-advisory-board (13 stars, last pushed 6mo ago), licensed MIT. It adds 54 tokens to every session and 378 once invoked, about $0.0002 per session on Opus 5.5. 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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