---

name: browser-history description: Search local browser history. Use when user asks about visited pages, forgotten URLs, or time spent on sites.

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:

Copy./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:

Copysqlite3 "file:///path/to/history.db?immutable=1" "SELECT ..."

Firefox databases (places.sqlite)

Search by keyword:

CopySELECT
    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:

CopySELECT 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):

CopySELECT
    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:

CopySELECT
    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:

CopySELECT
    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:

CopySELECT 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)

Firefox (moz_places_metadata)

Chromium (urls)

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.