Agent View

The site as an AI agent gets it, beside the site as a person sees it. What it can read, what it has to cut away, and what it never sees.

askyourdatabase.com90 pages read on October 24, 2026
Full screen
askyourdatabase.com/seo/ai-database-query/reference.sql
askyourdatabase.com/seo/ai-database-query/reference.sql
No main heading

-- Synthetic PostgreSQL reference, not an AI benchmark. -- Run the complete file in one disposable local session. Temporary tables only. CREATE TEMP TABLE context_users (user_id integer PRIMARY KEY, region text NOT NULL, is_test boolean NOT NULL); CREATE TEMP TABLE context_events (event_id integer PRIMARY KEY, user_id integer REFERENCES context_users, event_type text NOT NULL, occurred_at timestamptz NOT NULL); INSERT INTO context_users VALUES (1,'North',false),(2,'North',false),(3,'South',false),(4,'South',true),(5,'West',false); INSERT INTO context_events VALUES (101,1,'project_created','2026-09-03 10:00:00+00'), (102,1,'report_exported','2026-09-04 10:00:00+00'), (103,2,'login','2026-09-05 10:00:00+00'), (104,3,'project_created','2026-09-01 00:00:00+00'), (105,4,'project_created','2026-09-06 10:00:00+00'), (106,2,'project_created','2026-10-01 00:00:00+00'), (107,2,'project_created','2026-08-31 23:59:59+00'), (108,NULL,'report_exported','2026-09-07 10:00:00+00'); -- Q1: Distinct non-test users with qualifying activity in September UTC. Expected 2. SELECT COUNT(DISTINCT u.user_id) AS active_users FROM context_users AS u JOIN context_events AS e ON e.user_id = u.user_id WHERE u.is_test = false AND e.event_type IN ('project_created', 'report_exported') AND e.occurred_at >= TIMESTAMPTZ '2026-09-01 00:00:00+00' AND e.occurred_at < TIMESTAMPTZ '2026-10-01 00:00:00+00'; -- Q2: Same definition by current user region, including regions with zero. North 1, South 1, West 0. SELECT u.region, COUNT(DISTINCT e.user_id) AS active_users FROM context_users AS u LEFT JOIN context_events AS e ON e.user_id = u.user_id AND e.event_type IN ('project_created', 'report_exported') AND e.occurred_at >= TIMESTAMPTZ '2026-09-01 00:00:00+00' AND e.occurred_at < TIMESTAMPTZ '2026-10-01 00:00:00+00' WHERE u.is_test = false GROUP BY u.region ORDER BY u.region; -- Q3: Only report exporters; retain September UTC, non-test users and zero regions. North 1, South 0, West 0. SELECT u.region, COUNT(DISTINCT e.user_id) AS active_users FROM context_users AS u LEFT JOIN context_events AS e ON e.user_id = u.user_id AND e.event_type = 'report_exported' AND e.occurred_at >= TIMESTAMPTZ '2026-09-01 00:00:00+00' AND e.occurred_at < TIMESTAMPTZ '2026-10-01 00:00:00+00' WHERE u.is_test = false GROUP BY u.region ORDER BY u.region;

Drawn from the HTML mttr fetched, not a screenshot.
page.md243 words, about 581 tokens
-- Synthetic PostgreSQL reference, not an AI benchmark. -- Run the complete file in one disposable local session. Temporary tables only. CREATE TEMP TABLE context_users (user_id integer PRIMARY KEY, region text NOT NULL, is_test boolean NOT NULL); CREATE TEMP TABLE context_events (event_id integer PRIMARY KEY, user_id integer REFERENCES context_users, event_type text NOT NULL, occurred_at timestamptz NOT NULL); INSERT INTO context_users VALUES (1,'North',false),(2,'North',false),(3,'South',false),(4,'South',true),(5,'West',false); INSERT INTO context_events VALUES (101,1,'project_created','2026-09-03 10:00:00+00'), (102,1,'report_exported','2026-09-04 10:00:00+00'), (103,2,'login','2026-09-05 10:00:00+00'), (104,3,'project_created','2026-09-01 00:00:00+00'), (105,4,'project_created','2026-09-06 10:00:00+00'), (106,2,'project_created','2026-10-01 00:00:00+00'), (107,2,'project_created','2026-08-31 23:59:59+00'), (108,NULL,'report_exported','2026-09-07 10:00:00+00'); -- Q1: Distinct non-test users with qualifying activity in September UTC. Expected 2. SELECT COUNT(DISTINCT u.user_id) AS active_users FROM context_users AS u JOIN context_events AS e ON e.user_id = u.user_id WHERE u.is_test = false AND e.event_type IN ('project_created', 'report_exported') AND e.occurred_at >= TIMESTAMPTZ '2026-09-01 00:00:00+00' AND e.occurred_at < TIMESTAMPTZ '2026-10-01 00:00:00+00'; -- Q2: Same definition by current user region, including regions with zero. North 1, South 1, West 0. SELECT u.region, COUNT(DISTINCT e.user_id) AS active_users FROM context_users AS u LEFT JOIN context_events AS e ON e.user_id = u.user_id AND e.event_type IN ('project_created', 'report_exported') AND e.occurred_at >= TIMESTAMPTZ '2026-09-01 00:00:00+00' AND e.occurred_at < TIMESTAMPTZ '2026-10-01 00:00:00+00' WHERE u.is_test = false GROUP BY u.region ORDER BY u.region; -- Q3: Only report exporters; retain September UTC, non-test users and zero regions. North 1, South 0, West 0. SELECT u.region, COUNT(DISTINCT e.user_id) AS active_users FROM context_users AS u LEFT JOIN context_events AS e ON e.user_id = u.user_id AND e.event_type = 'report_exported' AND e.occurred_at >= TIMESTAMPTZ '2026-09-01 00:00:00+00' AND e.occurred_at < TIMESTAMPTZ '2026-10-01 00:00:00+00' WHERE u.is_test = false GROUP BY u.region ORDER BY u.region;

No <main>: Wrap the page’s own content in <main>, so a reader knows where it starts and stops, and Clean can be measured. No h1: Give each one h1 that says what the page is.

The figures

90 pages, set against the 168,011 sites with figures.

See its rivals
Readablehigher is better
100%90 of 90 pages
All 168,011 sitesBetter than 47%

Pages whose own text is in the HTML the server sends, enough of it for their kind.

Cleanhigher is better
93%middle page
All 168,011 sitesBetter than 91%

Of the words before script, the share that are the page and not menus, footer and forms. 11 pages are not measured, with no <main> or no words.

Costshown, never scored
244,794tokens
About 2,720 a page

To read every page once. A long page that answers well is not worse for it. Tokens are estimated at about 4 characters each.

How its pages spread on Clean

Its middle, 93%

70 pages measured. Not measured: 11 with no <main> or no words.

Against its rivals

The sites nearest it by what they do, with figures. Close means similar work, not better.

Readinghigher is betterCostnot scored
SiteReadableCleanTokens a page
askyourdatabase.comThis site, 90 pages100%93%2,720
forem.com100 pages98%75%1,966
dqc.ai100 pages96%44%876
itpathsolutions.com100 pages98%96%6,200

First of 4 on Readable, second on Clean.

AI crawler access

What robots.txt says to each, as read on October 24, 2026. 8 of 8 may read the site.

Open robots.txt
Crawlerrobots.txt saysUsed forThe line that decides
GPTBotOpenAINot namedTraining modelsFalls to User-agent: *
OAI-SearchBotOpenAINot namedChatGPT searchFalls to User-agent: *
ChatGPT-UserOpenAINot namedA page a person asks aboutFalls to User-agent: *
ClaudeBotAnthropicNot namedTraining modelsFalls to User-agent: *
Claude-SearchBotAnthropicNot namedClaude’s searchFalls to User-agent: *
PerplexityBotPerplexityNot namedPerplexity searchFalls to User-agent: *
Google-ExtendedGoogleNot namedTraining GeminiFalls to User-agent: *
bingbotMicrosoftNot namedBing and CopilotFalls to User-agent: *

Every AI crawler mttr checks may read it. Not named means the rules for every crawler apply.

Every page

Worst first. Each opens in Agent View at the top.

11 pages have no <main>. Wrap the page’s own content in <main>, so a reader knows where it starts and stops, and Clean can be measured.Open the action plan

What an agent getshigher is betterSignalsCostnot scored
PageWordsCleanReadableMain headingTokensWhat it loses
/resources/sql-server-latest-status-example.sql142No <main>YesNone291No <main> and 1 more
/seo/ai-database-query/reference.sql243No <main>YesNone581No <main> and 1 more
/seo/crm-pipeline/reference.sql189No <main>YesNone349No <main> and 1 more
/seo/mysql-gui/session-timezone.sql115No <main>YesNone214No <main> and 1 more
/seo/natural-language-rollout/reference.sql144No <main>YesNone353No <main> and 1 more
/seo/postgresql-report/reference.sql142No <main>YesNone380No <main> and 1 more
/seo/sql-dashboard/reference.sql248No <main>YesNone670No <main> and 1 more
/seo/sql-query-generator/join-aggregation.sql143No <main>YesNone264No <main> and 1 more
/seo/text-to-sql-evaluation/fixture.sql95No <main>YesNone285No <main> and 1 more
/seo/text-to-sql/reference.sql95No <main>YesNone245No <main> and 1 more
/seo/warehouse-sql-routing/definition-change.sql145No <main>YesNone256No <main> and 1 more
11 pages shown.

Show where it stands

A card, a badge and a line, each with the figures.

askyourdatabase.com in Agent View: 100% readable
1200 by 630, for linksDownload

A badge for the site

Agent View: 100% readable
<a href="https://mttr.si/agent-view/askyourdatabase.com"><img src="https://mttr.si/agent-view/askyourdatabase.com/badge.svg" alt="Agent View: 100% readable, 93% clean" height="20"></a>
Drawn again after every read

The figures in one line

askyourdatabase.com in Agent View: 100% of pages readable, better than 47% of sites; 93% clean; 244,794 tokens to read all 90 pages. mttr.si/agent-view/askyourdatabase.com

What to do next

Fix the pages, let an agent do it, and read the site again to see the figures move.

Fix what agents miss

19pages lose something
  • Give 19 pages a main headingClearer
  • Wrap 11 pages in <main>Clean measured
Open the action plan

Connect your agent

Claude Code, Codex or Cursor reads the site’s fixes over MCP, fixes a page in your code, has mttr read it again, and checks the fix landed.

https://mttr.si/mcp
Set up an agent

Claim the site

Prove it is yours with a DNS record or a file. Your agent can then reach its reads and jobs, and set each change to wait for your approval.

Claim the site

Drawn from the HTML mttr fetched on its read of October 24, 2026, not a screenshot, and only from the 90 pages read. An assistant’s own reader may differ. Tokens are estimated at about 4 characters each. A site an agent reads well is not a site an assistant cites.

Agent Viewaskyourdatabase.com Close Esc
askyourdatabase.com/seo/ai-database-query/reference.sql
askyourdatabase.com/seo/ai-database-query/reference.sql
No main heading

-- Synthetic PostgreSQL reference, not an AI benchmark. -- Run the complete file in one disposable local session. Temporary tables only. CREATE TEMP TABLE context_users (user_id integer PRIMARY KEY, region text NOT NULL, is_test boolean NOT NULL); CREATE TEMP TABLE context_events (event_id integer PRIMARY KEY, user_id integer REFERENCES context_users, event_type text NOT NULL, occurred_at timestamptz NOT NULL); INSERT INTO context_users VALUES (1,'North',false),(2,'North',false),(3,'South',false),(4,'South',true),(5,'West',false); INSERT INTO context_events VALUES (101,1,'project_created','2026-09-03 10:00:00+00'), (102,1,'report_exported','2026-09-04 10:00:00+00'), (103,2,'login','2026-09-05 10:00:00+00'), (104,3,'project_created','2026-09-01 00:00:00+00'), (105,4,'project_created','2026-09-06 10:00:00+00'), (106,2,'project_created','2026-10-01 00:00:00+00'), (107,2,'project_created','2026-08-31 23:59:59+00'), (108,NULL,'report_exported','2026-09-07 10:00:00+00'); -- Q1: Distinct non-test users with qualifying activity in September UTC. Expected 2. SELECT COUNT(DISTINCT u.user_id) AS active_users FROM context_users AS u JOIN context_events AS e ON e.user_id = u.user_id WHERE u.is_test = false AND e.event_type IN ('project_created', 'report_exported') AND e.occurred_at >= TIMESTAMPTZ '2026-09-01 00:00:00+00' AND e.occurred_at < TIMESTAMPTZ '2026-10-01 00:00:00+00'; -- Q2: Same definition by current user region, including regions with zero. North 1, South 1, West 0. SELECT u.region, COUNT(DISTINCT e.user_id) AS active_users FROM context_users AS u LEFT JOIN context_events AS e ON e.user_id = u.user_id AND e.event_type IN ('project_created', 'report_exported') AND e.occurred_at >= TIMESTAMPTZ '2026-09-01 00:00:00+00' AND e.occurred_at < TIMESTAMPTZ '2026-10-01 00:00:00+00' WHERE u.is_test = false GROUP BY u.region ORDER BY u.region; -- Q3: Only report exporters; retain September UTC, non-test users and zero regions. North 1, South 0, West 0. SELECT u.region, COUNT(DISTINCT e.user_id) AS active_users FROM context_users AS u LEFT JOIN context_events AS e ON e.user_id = u.user_id AND e.event_type = 'report_exported' AND e.occurred_at >= TIMESTAMPTZ '2026-09-01 00:00:00+00' AND e.occurred_at < TIMESTAMPTZ '2026-10-01 00:00:00+00' WHERE u.is_test = false GROUP BY u.region ORDER BY u.region;

Drawn from the HTML mttr fetched, not a screenshot.
page.md243 words, about 581 tokens
-- Synthetic PostgreSQL reference, not an AI benchmark. -- Run the complete file in one disposable local session. Temporary tables only. CREATE TEMP TABLE context_users (user_id integer PRIMARY KEY, region text NOT NULL, is_test boolean NOT NULL); CREATE TEMP TABLE context_events (event_id integer PRIMARY KEY, user_id integer REFERENCES context_users, event_type text NOT NULL, occurred_at timestamptz NOT NULL); INSERT INTO context_users VALUES (1,'North',false),(2,'North',false),(3,'South',false),(4,'South',true),(5,'West',false); INSERT INTO context_events VALUES (101,1,'project_created','2026-09-03 10:00:00+00'), (102,1,'report_exported','2026-09-04 10:00:00+00'), (103,2,'login','2026-09-05 10:00:00+00'), (104,3,'project_created','2026-09-01 00:00:00+00'), (105,4,'project_created','2026-09-06 10:00:00+00'), (106,2,'project_created','2026-10-01 00:00:00+00'), (107,2,'project_created','2026-08-31 23:59:59+00'), (108,NULL,'report_exported','2026-09-07 10:00:00+00'); -- Q1: Distinct non-test users with qualifying activity in September UTC. Expected 2. SELECT COUNT(DISTINCT u.user_id) AS active_users FROM context_users AS u JOIN context_events AS e ON e.user_id = u.user_id WHERE u.is_test = false AND e.event_type IN ('project_created', 'report_exported') AND e.occurred_at >= TIMESTAMPTZ '2026-09-01 00:00:00+00' AND e.occurred_at < TIMESTAMPTZ '2026-10-01 00:00:00+00'; -- Q2: Same definition by current user region, including regions with zero. North 1, South 1, West 0. SELECT u.region, COUNT(DISTINCT e.user_id) AS active_users FROM context_users AS u LEFT JOIN context_events AS e ON e.user_id = u.user_id AND e.event_type IN ('project_created', 'report_exported') AND e.occurred_at >= TIMESTAMPTZ '2026-09-01 00:00:00+00' AND e.occurred_at < TIMESTAMPTZ '2026-10-01 00:00:00+00' WHERE u.is_test = false GROUP BY u.region ORDER BY u.region; -- Q3: Only report exporters; retain September UTC, non-test users and zero regions. North 1, South 0, West 0. SELECT u.region, COUNT(DISTINCT e.user_id) AS active_users FROM context_users AS u LEFT JOIN context_events AS e ON e.user_id = u.user_id AND e.event_type = 'report_exported' AND e.occurred_at >= TIMESTAMPTZ '2026-09-01 00:00:00+00' AND e.occurred_at < TIMESTAMPTZ '2026-10-01 00:00:00+00' WHERE u.is_test = false GROUP BY u.region ORDER BY u.region;
Drawn from the HTML mttr fetched, not a screenshot. An assistant’s own reader may differ.Tokens are estimated at about 4 characters each.