Optimizing Content for Agents
cra.mr
cra.mr
There are some demos of this kind of thing already with curl | bash flows but my guess is we're going to see a huge incident using this pattern targeting people's Claws pretty soon.
Unit42 published research in March 2026 confirming websites in the wild embedding hidden instructions specifically targeting AI agents. Techniques include zero-font CSS text, invisible divs, and JS dynamic injection. One site had 24 layered injection attempts.
The same properties that make content agent-friendly (structured, parseable, in the DOM) also make it a perfect delivery mechanism for indirect prompt injection.
I'm surprised we haven't _already_ seen a major personal incident as early adopters tend to be less cautious - my guess is that it has already happened and no incident has been publicized or gone viral yet.
Especially I hope they'll figure this out before I get tempted to try this claw fad.
One thing I'd add from the agent-builder side: agent developers also need to think about how their agents present themselves to external services. Right now most agents hit websites as generic user-agents, and that's a missed opportunity. If agents identified themselves with structured capabilities (what formats they accept, what actions they can take, what permissions they have), services could tailor responses much more intelligently.
We're already seeing this with MCP -- the protocol gives agents a structured way to discover and invoke tools. But the content side is lagging behind. Your approach of treating documentation as a first-class agent interface closes that gap.
The point about models reading only the first N lines is underappreciated. I've seen agents fail not because the info wasn't there, but because it was buried 200 lines into a doc. Front-loading the most actionable content is basically SEO for agents.
Simlar to how everyone started optimising their pages for SEO, pages must be optimised for agents too, and its just simply detecting curl requests and returning structured files with internal linking to other pages.
It should basically be able to navigate the website like a file system. curl to the home page returns basic content with the basic sitemap structure, sitemaps ideally could have a description and token length of that specific page so agents can hit the sitemap route and know all pages/sub pages of the website.
Ideally if we can identify headless requests to a website to then return a markdown, with internal linking kind of layout then that'll be much better for agents to view websites.
Although yes there is firecrawl and cloudflare's new fetch apis, models will default to using curl or fetch on websites, and websites are not going anywhere, agents might need navigating websites more than us humans so it oculd be optimised for it.
Maybe it would be better to combine this with accessibility, so that both AI Agents, automation engines and blind people benefit at the same time? The biggest problem I have with this is that it won't easily work for static pages, since you need to respond to a special header.
Unit42's March 2026 research found 22+ techniques used in the wild to embed hidden instructions in HTML — zero-font CSS, invisible divs, dynamic JS injection. If more sites adopted this pattern and agents preferred the markdown path, a whole class of web-based IDPI attacks would be bypassed by design.
Compare https://docs.firetiger.com with https://docs.firetiger.com/llms.txt and https://docs.firetiger.com/llms-full.txt for a realy example.