Browser History Search

Search the user's browser history to find visited pages, analyze browsing patterns, and retrieve forgotten information.

When to use

• User asks about pages they visited ("what github repos did I look at last week?")
• User wants to find a forgotten page ("find that article about LLMs I read")
• User asks about browsing habits ("how much time did I spend on Twitter?")
• User wants browsing statistics ("show my most visited sites")

Requirements

• sqlite3 CLI

Setup

First, detect available browsers by running:

./find-browser.sh

• Output: PATH,TYPE,BROWSER,LAST_MODIFIED
• TYPE: firefox or chromium (determines SQL syntax)
• Use the first result (most recently used browser) by default
• If multiple browsers were used recently (within last 24h), ask the user which one to search

Querying the database

Use ?immutable=1 in the SQLite URI to read the database even when the browser is open:

sqlite3 "file:///path/to/history.db?immutable=1" "SELECT ..."

Firefox databases (places.sqlite)

Search by keyword:

SELECT
    title,
    url,
    datetime(last_visit_date/1000000, 'unixepoch', 'localtime') as visit_date
FROM moz_places
WHERE url LIKE '%keyword%' OR title LIKE '%keyword%'
ORDER BY last_visit_date DESC
LIMIT 50;

Search by date range:

SELECT url, title, datetime(last_visit_date/1000000, 'unixepoch', 'localtime') as visit_date
FROM moz_places
WHERE last_visit_date > strftime('%s', '2025-01-01') * 1000000
  AND last_visit_date < strftime('%s', '2025-01-31') * 1000000
ORDER BY last_visit_date DESC;

Time spent analysis (uses moz_places_metadata):

SELECT
    SUM(m.total_view_time) / 1000 / 60 as minutes,
    COUNT(*) as sessions
FROM moz_places_metadata m
JOIN moz_places p ON m.place_id = p.id
WHERE p.url LIKE '%example.com%'
  AND m.created_at > strftime('%s', '2025-01-01') * 1000;

Note: created_at is in milliseconds, last_visit_date is in microseconds.

Most visited sites:

SELECT
    SUBSTR(url, INSTR(url, '://') + 3,
           INSTR(SUBSTR(url, INSTR(url, '://') + 3), '/') - 1) as domain,
    SUM(visit_count) as visits
FROM moz_places
WHERE url LIKE 'http%'
GROUP BY domain
ORDER BY visits DESC
LIMIT 20;

Chromium databases (History)

Important: Chromium timestamps are microseconds since January 1, 1601 (Windows epoch).

Conversion: (timestamp/1000000) - 11644473600 gives Unix epoch.

Search by keyword:

SELECT
    title,
    url,
    datetime((last_visit_time/1000000)-11644473600, 'unixepoch', 'localtime') as visit_date
FROM urls
WHERE url LIKE '%keyword%' OR title LIKE '%keyword%'
ORDER BY last_visit_time DESC
LIMIT 50;

Search by date range:

SELECT url, title, datetime((last_visit_time/1000000)-11644473600, 'unixepoch', 'localtime') as visit_date
FROM urls
WHERE last_visit_time > (strftime('%s', '2025-01-01') + 11644473600) * 1000000
  AND last_visit_time < (strftime('%s', '2025-01-31') + 11644473600) * 1000000
ORDER BY last_visit_time DESC;

Database schema

Firefox (moz_places)

Column	Description
url	Full URL
title	Page title
last_visit_date	Microseconds since Unix epoch
visit_count	Number of visits
frecency	Frequency + recency score

Firefox (moz_places_metadata)

Column	Description
place_id	Foreign key to moz_places
total_view_time	Milliseconds spent on page
created_at	Milliseconds since Unix epoch
scrolling_time	Time spent scrolling
key_presses	Number of key presses

Chromium (urls)

Column	Description
url	Full URL
title	Page title
last_visit_time	Microseconds since 1601-01-01
visit_count	Number of visits

Output guidelines

• Present results in a readable format, grouped by domain when relevant
• For time analysis, show hours/minutes, not raw milliseconds
• When showing history, include the date and a clickable link
• If results are numerous, summarize by domain or time period
• You might include a small ASCII/Unicode chart (daily breakdown, histogram) if relevant

See @README.md for output examples.