For AI agents: a documentation index is available at /llms.txt — markdown versions of all pages are available by appending index.md to any URL path.

About Us

About the Agent Ecosystem Collective

An independent research collective studying how AI agents interact with the web, documentation, and developer tooling. We publish reports and open specifications, build compliance tools, and educate the ecosystem on what works.

Dachary Carey

Dachary Carey

Lead Researcher

The Agent Ecosystem Collective grew from direct experience: watching agents fail while trying to retrieve information on hundreds of documentation sites, and realizing that nobody was systematically studying these failure modes or building standards to fix them.

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Dachary Carey
Kay Rhodes
Kay Rhodes

Kay Rhodes

Developer

Lending 20+ years of development experience to build the tooling registry, installation CLI, and other planned developer tools for the agent ecosystem.

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Rhyannon Rodriguez

Rhyannon Rodriguez

Poker-of-Things

Bringing a background combining library science, development expertise, and technical writing to ask questions, run tests, and document the results.

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Rhyannon Rodriguez

Our Principles

What Drives Us

Independent, empirical, open, and built to be used.

Independence

The collective is self-funded, with no commercial stake in any platform or vendor. Published findings reflect what the data shows.

Empirical Rigor

We don’t speculate about what might matter. We measure what does. Every specification traces back to observed agent behavior.

Open by Default

Specifications, tools, scoring algorithms, and research methodologies are open source. Ecosystem standards should be available to everyone.

Adoption through Utility

We build specs that solve real problems and tools that make compliance easy to measure. Standards get adopted when they’re useful, not when they’re promoted.

Open Source Tools

6

Agent Skills Audited

673+

Sites Scored via Agent Score

500+

FAQ

Frequently Asked Questions

Common questions about the Agent Ecosystem Collective.

An independent research collective studying how AI agents interact with documentation, tools, and web infrastructure. We publish reports and open specifications based on what we find, and build the tooling that measures compliance. Companies are already measuring their documentation against our specs and competing on their scores.
The collective is self-funded by its members. Individuals who find the work valuable can support it through GitHub Sponsors, but there’s no corporate sponsorship program and nobody pays for our conclusions: published findings reflect what the data shows. That independence is what makes the research credible and useful.
It means documentation that coding agents (like Claude Code, Cursor, GitHub Copilot) can effectively discover, access, and use. Our 23-check specification covers content discoverability, markdown availability, page size, content structure, URL stability, observability, and authentication. When documentation meets these checks, agents can use it reliably; when it doesn’t, agents fail in predictable and preventable ways.
All specifications, tools, and benchmarks live in the agent-ecosystem GitHub organization. Published reports are freely available at their dedicated sites, and aeshift.com carries commentary on ecosystem developments.
Everyone building or using agent tooling. Agent platform companies benefit when documentation works well with their agents. Developer tool companies benefit when they understand how agents consume their docs. IDE and coding tool companies benefit from better tool quality and interoperability standards. And developers benefit from an ecosystem that just works.
Yes. Our specifications, audit tools (afdocs, skill-validator), and research methodologies are all open source. Published research and reports are freely available. We believe ecosystem standards should be open by default.

Research Built in the Open

The collective is independent and self-funded by design. Nobody pays for our conclusions, and everything we publish (specifications, tools, scoring algorithms, and research methodology) is open source and freely available.

Follow the Work on GitHub