Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add glebis/claude-skills --skill browsing-historygit clone --depth 1 https://github.com/glebis/claude-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/glebis/claude-skills/browsing-history)<a href="https://agentmods.dev/skills/glebis/claude-skills/browsing-history"><img src="https://agentmods.dev/badge/skills/glebis/claude-skills/browsing-history/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/glebis/claude-skills/browsing-history"><img src="https://agentmods.dev/badge/skills/glebis/claude-skills/browsing-history.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00063 | $0.01539 |
| Opus 5 | $0.00032 | $0.00770 |
| Sonnet 5 | $0.00013 | $0.00308 |
| Haiku 4.5 | $0.00006 | $0.00154 |
Grade A, and why
browsing-history scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Browsing History Skill
Query browsing history from all synced devices with natural language.
When to Use
Use this skill when the user asks about:
- Articles/pages they read (yesterday, last week, etc.)
- Browsing history from specific devices (iPhone, iPad, desktop)
- Finding pages by topic, domain, or keyword
- Exporting browsing history to files
- Grouping history by category or domain
Database
Location: ~/data/browsing.db
Synced devices: iPhone, iPad, Mac, desktop, Android
Timestamps
- visit_time: Actual visit timestamp from Chrome (100% coverage for all devices)
- first_seen: Import timestamp (fallback when visit_time unavailable)
The skill uses COALESCE(visit_time, first_seen) for accurate time-based queries.
Usage
python3 ~/.claude/skills/browsing-history/browsing_query.py "<query>" [options]
Options
| Option | Description | Example |
|---|---|---|
--device |
Filter by device | --device iPhone |
--days |
Number of days back | --days 7 |
--domain |
Filter by domain | --domain medium.com |
--limit |
Max results | --limit 50 |
--format |
Output format | --format json |
--output |
Save to file | --output history.md |
--group-by |
Group results | --group-by domain or --group-by category |
--categorize |
Use LLM to categorize | --categorize |
Example Queries
Basic queries:
# Yesterday's browsing history
python3 ~/.claude/skills/browsing-history/browsing_query.py "yesterday"
# Articles from iPhone yesterday
python3 ~/.claude/skills/browsing-history/browsing_query.py "yesterday" --device iPhone
# Last week's history grouped by domain
python3 ~/.claude/skills/browsing-history/browsing_query.py "last week" --group-by domain
# Find articles about economics
python3 ~/.claude/skills/browsing-history/browsing_query.py "economics" --days 7
Save to Obsidian:
# Save yesterday's history as markdown
python3 ~/.claude/skills/browsing-history/browsing_query.py "yesterday" \
--output ~/Research/vault/browsing-2025-11-27.md
# Save with LLM categorization
python3 ~/.claude/skills/browsing-history/browsing_query.py "yesterday" \
--categorize --group-by category \
--output ~/Research/vault/browsing-categorized.md
# Save as JSON
python3 ~/.claude/skills/browsing-history/browsing_query.py "last week" \
--format json --output ~/Research/vault/history.json
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 191 lines · 63 tokens per session scan A ab3b631c858b
browsing-history is a skill published in the GitHub repository glebis/claude-skills (374 stars, last pushed 9d ago), licensed MIT. It adds 63 tokens to every session and 1,539 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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