How we audited index365 for AI legibility

Marketing Signal is now the index365 Page Check. This post preserves a pre-consolidation scan of index365.co as product lineage. On July 31, 2026, that scan scored 99/100 and returned six open findings.

Both parts matter. The score summarized the page. The findings identified the work.

One historical command

At the time, the terminal flow started with one command:

index365 scan index365.co

The saved output ended on the score:

• Completed - score 99/100.

The completed run stayed attached to the project as history.

What 99/100 does not tell you

A report that stops at the score is a screenshot for a slide deck. The score is a summary statistic. The findings are the work.

Our 99 arrived with six findings across crawlability and structure. A score that high with open findings is not a contradiction. It means the site is broadly legible to AI readers while specific, fixable gaps remain, and the gaps are enumerated instead of hidden inside a rounded number. If we had read only the score, we would have learned nothing actionable. Reports stop at the score. Findings carry the fix.

Reading the findings

The findings list is the actual audit output. No run ID needed: findings reads your latest run and says which run it resolved.

index365 findings

The list prints one numbered line per finding plus a severity summary. Excerpted, the line that mattered most to us:

• 3 medium crawlability llms.txt guidance
• 6 findings.

Five of the six stay unnamed here; they spread across crawlability and structure and were queued the same way. The one we will walk through is the llms.txt finding, because it changed our own site.

From Finding to fix prompt

Each Finding carries its evidence and a copy-pasteable fix prompt. That prompt is the handoff point to a coding agent. The number is the ordinal from the list above.

index365 findings get 3

The command prints the Finding and then the fix prompt block:

• Fix prompt:
• Fix this website finding: llms.txt guidance
• Affected URLs: https://index365.co/llms.txt
• Remediation: extend llms.txt so AI readers get the current product inventory and agent entry points, and generate it from application code so it cannot drift from the live site.
• Apply the remediation, then re-scan to confirm the finding is resolved.

We pasted that prompt to a coding agent working in our own project. The agent used the Finding to fix the page: it rewrote the llms.txt route, added the agent entry points, and shipped the change through our normal review. index365 did not ship the fix. The coding agent did, with the Finding as its spec, which is the entire division of labor the product is built around.

What we fixed

The honest part of dogfooding is publishing the result. Because of this scan, index365.co now generates its llms.txt and llms-full.txt from application code, with the product inventory and agent instructions kept current by the same deploy that changes the site. Our own site had the exact class of gap we scan other sites for, and the scan is why it is closed.

After the change, we ran another check and reviewed the new evidence. A later Page Check does not automatically match or verify an earlier finding.

Run the current Page Check

Marketing Signal is the current Page Check for yoursite.com. It scores one page across six categories and returns findings with reasoning and a scoped fix prompt.

See what Marketing Signal checks. Start from the Marketing Signal product page. The CLI guide explains the supported terminal workflow.