What the Dashboard shows

The Dashboard is the first tab you land on when you open Agentimus. It answers one plain question with two sides:

  • Is AI sending readers to you? The Traffic from AI card counts real people who clicked through to your site from an AI assistant like ChatGPT or Perplexity.
  • Is AI reading from you? The agent activity log records each time a bot or crawler fetches one of the machine-readable files Agentimus publishes (things like /llms.txt or a page’s .md version).

Alongside these sits a Readiness summary — an at-a-glance health check of how well your site is set up for AI.

Everything on this tab is first-party and local-only. All of it lives in your own WordPress database, nothing is ever sent to Agentimus or any third party, and — importantly — no IP addresses and no personal data are stored. The two data stores are pruned and size-capped automatically, so they never grow without bound.

The whole Dashboard is powered by a single setting, Agent activity log, which is on by default. It covers both directions at once — the traffic-in card and the bots-out log are one feature. If you ever turn it off in Settings, both stop recording.

Traffic from AI

The Traffic from AI card is the “giving back” side of the story: it shows whether AI tools are actually sending human readers to your pages, and where those readers land.

It reports three things over a rolling window (30 days by default):

  • Totals — visits today, and visits across the whole window.
  • Top sources — which assistants sent the most readers (up to eight).
  • Top landing pages — which of your pages AI readers arrived on most (up to eight).

Below those is the by-day breakdown, which is where the detail lives.

The by-day breakdown

For each day in the window, the card shows which assistant sent a reader to which page. Each day carries:

  • the date,
  • the total AI-referred visits that day, and
  • a list of source → page rows — for example, ChatGPT → /pricing with a count.

To keep a busy day from ballooning the card, each day keeps its 12 busiest source-and-page pairings and rolls the rest into a “+N more” note. Days are listed newest-first, and within a day the busiest pairing comes first.

There is no clock time anywhere in this breakdown — the day is the finest level of “when” the plugin stores. That is deliberate: a per-visit timestamp starts to look like a trail back to an individual, and this card is built so that no stored row can ever represent a person.

How AI referrals are detected

Detection is simple, private, and makes no outbound calls. It reads two signals that are already attached to the incoming page request:

  1. The referrer host — the address of the page the reader clicked from. When someone follows a link inside a Perplexity, Gemini, Claude, Copilot, You.com or Poe answer, their browser reports that assistant’s domain as the referrer. Subdomains count too (for example, a link from something.chatgpt.com still resolves to ChatGPT).
  2. The utm_source tag — a marker some assistants stamp onto the links they hand out. ChatGPT, for instance, adds utm_source=chatgpt.com. This is a belt-and-braces signal: it catches a referral even when the browser strips the referrer away.

Both signals are lowercased, have any leading www. removed, and are matched against a fixed list of known AI sources. If neither signal points at a known assistant, nothing is recorded — the vast majority of visits (direct traffic, internal clicks, ordinary search) exit instantly without ever touching the database.

One more gate: the visitor must be using a real web browser. A reader clicking out of an AI answer is a person on a browser; a bot that happens to arrive carrying a referrer is not “a visitor AI sent”, so it is not counted here.

Which assistants are recognised

Assistant Detected from
ChatGPT chatgpt.com, chat.openai.com (and the utm_source=chatgpt.com tag)
Perplexity perplexity.ai
Gemini gemini.google.com, bard.google.com
Copilot copilot.microsoft.com
Claude claude.ai
You.com you.com
Poe poe.com

Google “AI Overviews” is intentionally left out. Those visits arrive with a plain google.com referrer that is indistinguishable from an ordinary Google search, so counting them would be guesswork — and Agentimus would rather show you nothing than show you a number it can’t stand behind.

What gets counted, and what doesn’t

A visit is recorded only when all of these are true:

  • it’s a normal front-end page view (a GET request — not the admin area, a REST/AJAX call, a feed, a 404, a trackback, or robots.txt);
  • the visitor is a real browser;
  • the referrer or utm_source matches a known AI assistant; and
  • the visitor is not you — a logged-in administrator browsing their own site is skipped, so your own clicks never inflate the numbers.

When a visit does count, the plugin stores exactly one thing: a per-day tally of (assistant, landing page). It keeps no IP address, no User-Agent, no query string — the landing page’s query string (including any tracking tags) is stripped off before the path is saved, and the path itself is length-limited. There is nothing in a stored row that could identify a reader.

The agent activity log

The activity log is the mirror image of the Traffic-from-AI card: instead of humans arriving from AI, it records bots and crawlers fetching your content — the AI tools reading your site so they can train on it or answer questions about it.

A hit is logged each time an agent fetches one of the machine-readable documents Agentimus serves, for example:

Endpoint What it is
llms.txt Your site’s content map for AI
llms-full.txt The full-text edition of your content
markdown A page or post fetched as clean .md
discovery.json The machine-readable discovery document
mcp.json, openapi.json, api-catalog Tool/API descriptions for agents
sitemap, tdmrep.json, oauth-protected-resource Supporting discovery files

What a “hit” records

Each logged hit stores just four small facts:

  • the endpoint that was fetched (a short label like llms.txt),
  • a friendly agent name worked out from the request (see below),
  • a truncated copy of the User-Agent string the client sent, and
  • the time, stored in UTC.

That’s it. No IP address is ever recorded — so there is no personal-data or GDPR footprint by default — and the log is never transmitted anywhere. Repeat hits from the same client are grouped with a count, newest first, so the view stays readable.

As with the traffic card, you are skipped: a logged-in administrator opening discovery.json in a browser to check it isn’t agent traffic, so it doesn’t clutter the log.

How agents are identified

Raw User-Agent strings are noisy, so Agentimus translates each one into a plain-English label. Recognised crawlers get their real name — for example GPTBot (OpenAI), ClaudeBot (Anthropic), PerplexityBot, Googlebot, Bingbot, Bytespider (ByteDance), CCBot (Common Crawl). A client that isn’t in that catalog but which declares its own product name — for example TheWebReport/1.0 — is shown by that name (TheWebReport), the very name the review queue uses, so the two never disagree. Only when there’s no name to show at all does a client fall into a clear generic bucket:

  • Other bot — self-declares as a crawler, but isn’t one Agentimus has a name for.
  • Script/tool — an HTTP library or command-line tool (curl, wget, Python requests, and the like).
  • Likely spoof/scanner — a client pretending to be a long-dead phone or embedded device (Symbian, Java ME, old BlackBerry, Windows CE…). No real reader fetches a machine endpoint from a 2004 feature phone, so these are almost always scanners hiding behind a harmless-looking string.
  • Browser — a normal web browser.
  • No user-agent — the client sent no User-Agent at all.
  • Unrecognized — the client sent a User-Agent, but nothing Agentimus can name it by.

These same labels feed the review queue, so the naming never disagrees with itself.

The daily chart and per-day requests

The log includes a per-day chart spanning the retention window, with every day present even if it saw no traffic. Each day also carries a compact breakdown of who hit you (its top clients) and what they fetched (its top endpoints), capped at five of each with a distinct-count so a day with fifty different endpoints still shows five rows and a “+50” — the card never grows with your traffic.

Click into a day and the “View requests” view shows every hit recorded on that date, newest first (capped at a generous per-day limit), so you can inspect a spike in detail.

Activity to review

Sitting alongside the log is a small review queue that flags clients worth a second look — ones that are new, unusually high-volume, or spoofed/scanner by the definition above. Each flagged client comes with a one-click Block (or Allow/trust) action. This pairs with the optional Block scanners & scrapers enforcement covered on the Settings page — the review queue and the blocking feature share one definition of who is who, so a decision you make in one is honoured by the other.

Flood protection

To keep one abusive burst from drowning out the traffic you care about, the log is flood-aware. A recognised crawler (GPTBot, Googlebot, ClaudeBot…) is always logged, however fast it hits — that’s exactly the signal you want. Everything else (unknown clients, scripts, spoofs) is throttle-eligible: once such hits pass a threshold within a short window, the log keeps only a sample of them. So a stampede of throwaway user-agents (EvilBot-1, EvilBot-2, …) can’t push real agents out of the log.

Your privacy: local-only, no IPs, no personal data

This is the point worth repeating, because it shapes every design choice on this tab:

  • Local-only. Both the traffic card and the activity log live entirely in your WordPress database. Nothing is sent to Agentimus, and the plugin makes no outbound calls to gather any of it.
  • No IP addresses. Neither store records an IP, ever — so there’s no personal-data trail to manage.
  • The traffic card stores no person-level data at all. Its rows are pure per-day tallies of (assistant → page) with no IP, no User-Agent, and no query string.
  • The activity log keeps only technical request facts — the endpoint, a friendly agent label, a truncated User-Agent, and a UTC time. A User-Agent is a self-declared software string, not a person.
  • You’re excluded. Your own logged-in admin visits are skipped in both directions, so your browsing never skews the data.

If you ever want a clean slate, the log offers a Clear action that empties it in one step.

How data is pruned and capped

Nothing here accumulates forever. Both stores are tied to the same housekeeping:

  • Retention window. By default, Agentimus keeps (and reports on) the last 30 days. What you see always equals what’s retained — the daily chart span, the reporting window, and the cleanup cutoff are all the same number.
  • Daily prune. A once-a-day background task deletes anything older than the retention window, for both the activity log and the traffic tallies.
  • Hard row cap. As a backstop for an extreme-traffic day (so the table can’t bank a huge number of rows before the daily prune runs), the activity log is also capped at a maximum row count and trimmed opportunistically as new hits come in.

For most site owners the defaults are exactly right and need no attention. Developers who want a longer or shorter memory can adjust the retention and the cap with filters (below).

The Readiness summary in the sidebar

The Dashboard sidebar carries a condensed view of your Readiness report — the same pass / warn / fail checks shown in full on the Readiness tab, boiled down to an at-a-glance signal of how AI-ready your site is.

These checks look at the things that decide whether agents can find and read you well, such as:

  • whether your site is public and using pretty permalinks,
  • whether /llms.txt (and the full-text edition) are enabled and have real substance,
  • whether you’ve set an author/entity profile and expertise topics,
  • whether Topics for AI are in use,
  • whether a sitemap exists and is advertised in robots.txt, and
  • whether your AI-usage and security signals are in place.

The sidebar summary is a jumping-off point: use it to spot that something needs attention, then open the Readiness tab for the full breakdown, where each item comes with a plain-English explanation and a deep link straight to the fix. The Readiness & agent preview page in this manual covers those checks in detail.

Turning the Dashboard on or off

The Dashboard’s data collection is controlled by a single Agent activity log setting, found under Settings. It’s on by default and governs both sides at once:

  • turn it off and Agentimus stops recording both AI referrals and agent hits (the tab simply shows nothing new);
  • turn it back on and recording resumes from that point.

Turning it off doesn’t delete what’s already there — use the log’s Clear action if you want to wipe the history as well.

For developers: adjusting the defaults (optional)

If you manage the site’s code, a few filters let you tune this feature. Site owners can safely ignore this section.

// Change how long activity + referrals are kept and reported on (days). Default 30.
add_filter( 'agentimus_activity_retention_days', fn() => 90 );

// Change the hard row cap on the activity log (0 disables the cap). Default 50000.
add_filter( 'agentimus_activity_max_rows', fn() => 100000 );

// Add your own AI-referral sources (referrer host / utm_source => display label).
add_filter( 'agentimus_ai_referral_sources', function ( $map ) {
	$map['mistral.ai'] = 'Le Chat';
	return $map;
} );

// Add or rename entries in the agent-name map used by the activity log.
add_filter( 'agentimus_agent_map', function ( $map ) {
	$map['mynewbot'] = 'My New Bot';
	return $map;
} );

// Log your own admin visits too (default is to skip logged-in administrators).
add_filter( 'agentimus_activity_skip_self', '__return_false' );

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Built and maintained by Sheikh Heera. Agentimus is free software (GPL-2.0-or-later); this documentation is generated from the plugin source — if something here disagrees with the code, the code wins.

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