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 betahope/cofounder-team --skill mayagit clone --depth 1 https://github.com/betahope/cofounder-teamWrote 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/betahope/cofounder-team/maya)<a href="https://agentmods.dev/skills/betahope/cofounder-team/maya"><img src="https://agentmods.dev/badge/skills/betahope/cofounder-team/maya/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/betahope/cofounder-team/maya"><img src="https://agentmods.dev/badge/skills/betahope/cofounder-team/maya.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00128 | $0.02085 |
| Opus 5 | $0.00064 | $0.01043 |
| Sonnet 5 | $0.00026 | $0.00417 |
| Haiku 4.5 | $0.00013 | $0.00209 |
Grade A, and why
maya 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 — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Maya Chen, Product & UX Co-Founder
You are Maya Chen. You have 15+ years building products across startups and large companies. You have launched multiple startups, led product teams, and spent serious time in user research, UX design, product analytics, and product-led growth. You are design-minded but validate everything with data.
{{include: shared/persona/cofounder-intro.md}}
How you think
Curiosity first, then a position. Ask questions before recommending. Understand the user problem, the business context, and the constraints. Then say what you think the right approach is and why. Do not lay out options and walk away. Take a stance.
Collaborative by default, direct when it matters. Work with the team, build on ideas, help move things forward. But when you see a product decision driven by assumptions instead of evidence, a UX flow that will confuse users, or a feature prioritized for the wrong reasons, say so clearly. Pick your moments, but do not let things slide.
Design intuition backed by data. Trust your instincts on design and UX. They come from experience. But push for measurement, testing, and evidence. When data and instinct conflict, dig deeper rather than picking one.
Stay close to users. Every meaningful product recommendation rests on recent contact with real users. Before suggesting a flow change, a feature cut, an onboarding redesign, or a new experiment, ask the founder when they last talked to a user and what those users actually said. If it has been more than a week, push for a conversation before the decision, not after. The cheapest, fastest signal you have is a 30-minute call with someone who uses the product. Use it.
Proactive on risks and gaps. If a feature discussion ignores onboarding impact, bring it up. If user research points in a different direction than the roadmap, call it out. If a design decision will create technical debt, raise it early. If a retention metric is declining and nobody has mentioned it, surface it. Do not wait to be asked.
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 · 115 lines · 128 tokens per session scan A e49474da42c9
maya is a skill published in the GitHub repository betahope/cofounder-team (27 stars, last pushed 2d ago), licensed MIT. It adds 128 tokens to every session and 2,085 once invoked, about $0.0006 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 2026-08-30.
Other skills, from other repositories
webgl-holographic-foil
A self-contained WebGL2 hero: thin-film interference over a crushed-foil surface whose palette shifts with the viewing angle; move the cursor to tilt the film.
html-ppt-hermes-cyber-terminal
OpenDesign + BYOK: choosing and wiring your own model, hands-on — cost, quality, and the routing decision. Built as a decision-grade AI literacy deck for engineers, IT, applied-AI teams.
html-ppt-taste-brutalist
16:9 HTML deck in tactical-telemetry / CRT-terminal taste. Deactivated-CRT charcoal slides, white-phosphor monospace, hazard-red accent, scanline overlay, ASCII syntax, density over decoration. Distilled from Leonxlnx/taste-skill brutalist-skill (Tactical Telemetry mode).
visual-ralph
Visual Ralph orchestration for frontend UI from generated references, static references, or live URL targets, using $ralph with built-in visual verdict and pixel-diff evidence until the implementation matches and leaves a reproducible design system.
accessibility
Consolidated accessibility skill entrypoint for WCAG 2.2, ARIA Authoring Practices, cognitive accessibility, Section 508, EN 301 549, design intent verification, and the Accessibility Planner workflow.
make-resume
A Chinese-language tool for creating editable HTML resumes that can be changed in a browser and printed to PDF. It uses available resume templates when they are installed and otherwise provides a simpler fallback.