Let an Agent Read Your AI Crawler Logs and Propose robots.txt Fixes
A concrete loop where an agent reads AI crawler logs, finds the pages crawlers cannot reach, and proposes a robots.txt change you review before it ships.
A robots.txt file is a small text file with large consequences for AI search. Get it right and the AI crawlers reach the pages you want cited. Get it wrong and you quietly block ChatGPTBot, ClaudeBot, or PerplexityBot from the pages that would have earned the citations. The mistake is usually invisible, because the crawlers do not complain. They just stop coming, and your visibility drops for reasons that look like a content problem but are actually an access problem.
This guide builds a loop where an agent reads your AI crawler logs, finds the pages the crawlers cannot reach, and proposes a robots.txt fix you review before it ships. The agent does not edit the file. You do. The agent's job is to find the evidence and draft the change.
Why crawler logs are the right input
A robots.txt change should start from crawl evidence, not from a guess about what crawlers want. The Promptwatch Agent Analytics surface streams live AI crawler logs for ChatGPTBot, ClaudeBot, PerplexityBot, GoogleOther, and the Meta AI crawler, with a crawl-to-citation path and error tracking. That is the data that tells you which crawlers came, which pages they read, and which requests failed. A robots.txt proposal built on that evidence is grounded. A proposal built on a hunch is not.
The agent reads this surface over the Promptwatch MCP server. The two tools that matter are getCrawlerTrend, which shows how crawler hits moved over time, and getTopCrawlerPages, which shows which pages each crawler read most. getSiteHealth adds structural context, since a page that returns a 5xx or a redirect chain is a different problem from a page that is disallowed.
The loop, step by step
Start the session with a read-only key. The agent is diagnosing, not editing, so the write tools should not be present.
Step one is the trend. The agent calls getCrawlerTrend for the last 14 days and looks for a drop in any crawler's hit rate. A sudden fall in ChatGPTBot requests, for example, is the signal that something changed on the access side. The agent notes which crawler dropped and when.
Step two is the page level. The agent calls getTopCrawlerPages for the crawler that dropped and compares it to the previous period. The question is which pages the crawler stopped reading. If a whole section of the site dropped out of the crawl, that is a strong robots.txt signal. If a single page dropped, it might be a link or sitemap issue instead.
Step three is the cross-check. The agent calls getSiteHealth to see whether the affected pages return errors or redirects. If getSiteHealth shows a 200 for the pages the crawler stopped reading, the access problem is likely in robots.txt or a server-side block, not in the page itself. If it shows errors, the fix is on the server, not in robots.txt, and the agent should say so rather than propose a robots.txt change.
Step four is the crawl-to-citation check. The agent calls getCitations and getCitationTopPages to see whether the pages the crawler stopped reading were the ones getting cited. If they were, the visibility cost of the block is real and quantified. If they were not, the block matters less, and the report should rank it accordingly. This step keeps the loop honest. Not every crawl drop is worth fixing.
Drafting the robots.txt proposal
With the evidence in hand, the agent drafts the proposed change. The proposal has four parts. The crawler affected, named by user agent. The pages or paths blocked, with the evidence from getTopCrawlerPages. The current robots.txt rules that appear to cause the block, if the agent can read the file from your repo. And the proposed new rules, written as actual robots.txt syntax.
A reasonable proposal looks like this.
# Current
User-agent: ChatGPTBot
Disallow: /resources/
# Proposed
User-agent: ChatGPTBot
Allow: /resources/
Disallow: /resources/private/
The agent should explain the change in plain English. The current rule blocks the entire resources section from ChatGPTBot. The proposed rule allows the section except for the private subdirectory, which is the part that should stay blocked. The evidence is that ChatGPTBot stopped reading the resources pages on a specific date, and those pages were cited for three tracked prompts.
The agent should not claim the fix will restore visibility. It should claim the fix will restore access, and that visibility should be re-measured after the crawlers return.
The human gate
The agent does not commit the change. You do. The proposal lands as a document or a pull request draft, depending on how you wired the loop. A person reads the proposed rules, checks them against the actual robots.txt, and decides whether to ship.
This gate matters because robots.txt is global and immediate. A wrong Allow opens pages you did not want open. A wrong Disallow blocks pages you need cited. The agent's job is to find the evidence and draft the syntax. The human's job is to confirm the syntax matches intent. Keep that boundary.
If you want the loop to ship the change as a pull request, wire the agent to write the proposed file to a branch in your repo and open a PR. That is a filesystem write, not a Promptwatch write, so it does not need the Promptwatch write key. The Promptwatch side of this loop stays read-only, which is the safe default.
Verifying the fix
After the robots.txt change ships, the verification is the same evidence the diagnosis used. The agent calls getCrawlerTrend over the next week and checks whether the affected crawler's hit rate recovered. It calls getTopCrawlerPages to confirm the previously blocked pages are being read again. It calls getCitations and getCitationTopPages to see whether the restored crawl led to restored citations, and getVisitorTrend to see whether traffic followed.
The result might be that the crawler came back but the citation did not. That is a useful result, because it tells you the access problem is fixed and the remaining problem is content. The agent should report that distinction rather than claiming the fix worked. Access restored is the goal of this loop. Citation restored is the goal of the next loop.
The full loop in one pass
Here is the loop end to end. The agent reads getCrawlerTrend to find a crawler drop. It reads getTopCrawlerPages to find the pages that stopped being read. It reads getSiteHealth to rule out a server error. It reads getCitations and getCitationTopPages to quantify the visibility cost. It drafts a robots.txt proposal with the crawler, the blocked paths, the current rule, and the proposed rule. A person reviews and ships the change. A week later, the agent reads getCrawlerTrend, getTopCrawlerPages, getCitations, and getVisitorTrend to verify whether access and citations recovered.
That is a crawler-log to robots.txt loop, with the human gate at the file change and the measurement gate at the end. The Promptwatch Agent Analytics surface, through getCrawlerTrend and getTopCrawlerPages, is what makes the diagnosis grounded in crawl evidence instead of a guess. Run it read-only, ship the change yourself, and let the verification step tell you whether the next problem is access or content.