AI Visibility Audit for a Nonprofit

The website Family Caregivers Online exists for one reason: to make sure the people quietly caring for a parent, a spouse, a sibling (while also working, raising their own kids, running their own lives) have somewhere free and trustworthy to turn. No ads. No upsells. Just a publicly funded website doing exactly what caregivers do for everyone else: showing up, consistently, asking nothing in return.

This website is doing good, important work for its community. It just hadn’t had anyone check its own vitals in some time.

The AI Visibility Audit for a Nonprofit

I ran this AI Visibility audit for my client’s nonprofit website to see if tools like ChatGPT, Claude, and Perplexity can actually find the site, read it, understand what it offers, and confidently point someone toward it. Starting score: 65 out of 100. Not neglected. Just under-cared-for in the specific ways that don’t show up unless you go looking.

Here’s what the assessment turned up:

• No care plan on file.
  No llms.txt or llms-full.txt, the files that tell AI tools what a site is, who it’s for, and where to find its resources. Without them, AI tools were left guessing at a site whose whole purpose is to not make people guess.
• No documented consent for AI visits.
  The robots.txt file had no Content Signals: the emerging standard that tells AI crawlers explicitly whether they’re welcome to use a site’s content for search and citation versus training. Silence isn’t the same as an answer.
• A confused intake form.
  Two H1 headings competing on the homepage, a leftover of a Divi responsive design pattern, where a desktop hero and a mobile hero had both been marked as the page’s primary headline. Harmless to a human visitor. Confusing to a crawler trying to figure out what the page is actually about.
• No way to properly introduce itself.
  Twitter/X Card tags were missing, so when the site’s resources got shared on social media, there was no proper preview card, just a bare link doing none of the work of explaining what someone was about to click into.
• No easy-read version for visitors who need one.
  No markdown delivery for AI agents, meaning AI tools had to wade through full page HTML to read an article instead of getting a clean, direct version of the content.

None of this was visible to a family caregiver landing on the homepage at midnight looking for help. All of it mattered to whether an AI tool would ever reliably find and recommend this site to the person who needed it.

The Care Plan

Here’s what actually got treated, one item at a time:

• Wrote the care plan.
  Generated llms.txt (a structural index of the site’s core pages) and llms-full.txt (an expanded reference with mission, funders, and program details), so AI tools reading the site now get an intentional summary instead of having to piece one together themselves.
• Documented consent for AI visits.  
  Added Content Signals to robots.txt (search=yes, ai-input=yes, ai-train=no), explicitly welcoming AI tools to read and cite the site’s content for real-time answers, while opting out of it being used to train foundation models.
• Resolved the intake mix-up.
  Traced the duplicate H1 to Divi’s separate desktop and mobile hero blocks and brought the mobile heading down to an H2 in the Divi Builder, so the page has one clear, unambiguous headline again.
• Enabled the introduction card.
  Turned on Twitter/X Card output in Yoast’s social sharing settings and set explicit Twitter title and description fields on the homepage, since Yoast quietly skips writing those tags when they’d just duplicate the Open Graph ones.
• Added the easy-read version.
  Enabled VigIA’s built-in Markdown-for-Agents feature across posts and pages, so any AI tool that wants a clean, direct version of an article (instead of full page HTML) can request one automatically.
• Caught a filing error along the way.
  Both new AI files initially displayed with garbled special characters (em dashes and accented letters turning into gibberish) because the server wasn’t declaring a character set. Fixed it by adding a UTF-8 byte-order-mark directly to the files, so they’d render correctly no matter what the server did or didn’t announce.
• Checked vitals on the way out.
  Homepage response time briefly spiked to over a full second right after all the changes went in, a caching side effect of the edits, not a real problem. A cache purge brought it back down to 33 milliseconds.

The AI Visibility Audit for a Nonprofit Results

Score progression over the audit:

• Initial audit ……………………………………………… 65/100
• After llms.txt, llms-full.txt, and Content Signals …… 82/100
• After Twitter Cards, the duplicate H1 fix, and Markdown for Agents … 86/100 (masked by a temporary caching hiccup)
• Final, after clearing the cache …………………………… 91/100 (A+)

Before and after, by category: 

Same site, same content. No redesign. Just the kind of check-in this site has been giving to family caregivers all along, finally turned around and pointed at itself.

What I Learned

There’s nothing exotic about what was wrong here. It’s the ordinary, invisible residue of a site whose entire team has always been focused outward, on the caregivers who need it, rather than on the site’s own technical upkeep. That’s not a failure. It’s just what happens when an organization’s whole reason for existing is taking care of other people first.

It’s also exactly the blind spot an AI visibility audit is built to catch. If your organization’s website has been quietly doing good work for a while without anyone checking whether AI tools can actually find and recommend it, that’s the same nagging feeling I hear from a lot of clients, nonprofits especially, where there’s rarely time or budget for this specific kind of maintenance.

Book a free strategy session and let’s run an AI Visibility Audit on your site. Even the sites that take care of everyone else deserve a little care of their own.

AI Visibility Score Reference