BrowserAct is a browser automation system that lets AI agents use real, separate browser sessions to extract data and complete account-based web tasks. It is for agents and teams that need parallel workflows, reused login states, human handoffs, or access to sites that resist ordinary automated requests.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/browser-act/skillsnpx agentmods add skills/browser-act/skills/airbnb-listing-detailWrote 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/browser-act/skills/airbnb-listing-detail)<a href="https://agentmods.dev/skills/browser-act/skills/airbnb-listing-detail"><img src="https://agentmods.dev/badge/skills/browser-act/skills/airbnb-listing-detail/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/browser-act/skills/airbnb-listing-detail"><img src="https://agentmods.dev/badge/skills/browser-act/skills/airbnb-listing-detail.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 | $0.00118 | $0.01283 |
| Opus 5 | $0.00059 | $0.00642 |
| Sonnet 5 | $0.00024 | $0.00257 |
| Haiku 4.5 | $0.00012 | $0.00128 |
Grade A, and why
airbnb-listing-detail 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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Airbnb — Listing Detail
Listing ID → full property detail via internal GraphQL API (no login required)
Language
All process output to user (progress updates, process notifications) follows the user's language.
Objective
Fetch comprehensive listing data for an Airbnb property using the internal StaysPdpSections GraphQL API.
Prerequisites
- Browser is open (any page). The API call is made via
fetch()in the browser context — no specific page navigation required. - No login required — the API endpoint is publicly accessible
Pre-execution Checks
1. Tool Readiness
If browser-act has been confirmed available in the current session → skip this step.
Invoke browser-act via Skill tool to load usage. If installation or configuration issues arise, follow its guidance to resolve then retry.
Capability Components
This Skill's operational boundary = what the user can manually do in their browser. It only reads data already displayed to the user on the page, never bypassing authentication or access controls. JS code is encapsulated in Python files under the
scripts/directory, invoked viaeval "$(python scripts/xxx.py {params})".$(...)is bash syntax; it is recommended to use the bash tool for execution.
API: fetch listing detail
eval "$(python scripts/listing-detail.py '{listing_id}')"
Parameters:
listing_id: numeric Airbnb listing ID (e.g.,5476930). Extract from listing URL:airbnb.com/rooms/{listing_id}--checkin: check-in date in YYYY-MM-DD format, default: none (price info unavailable without dates)--checkout: check-out date in YYYY-MM-DD format, default: none--adults: number of adult guests, default:1--locale: response locale, default:en--currency: price currency code, default:USD
Output example:
{
"id": "5476930",
"url": "https://www.airbnb.com/rooms/5476930",
"title": "Bright Studio in Notting Hill",
"room_type": "ENTIRE_HOME",
"description": "<p>Welcome to this charming studio...</p>",
"photos": ["https://a0.muscache.com/im/pictures/...jpeg"],
"lat": 51.5101,
"lng": -0.1949,
"city": "London, England, United Kingdom",
"amenities": [
{"name": "Kitchen", "available": true},
{"name": "Wifi", "available": true}
],
"house_rules": ["Check-in after 3:00 PM", "Checkout before 11:00 AM", "1 guest maximum"],
"highlights": [
{"title": "Self check-in", "subtitle": "Check yourself in with the keypad."}
],
"rating_overall": 4.85,
"review_count": 142,
"ratings": [
{"category": "CLEANLINESS", "value": "4.9"},
{"category": "LOCATION", "value": "4.8"}
],
"bedrooms": [
{"title": "Bedroom 1", "subtitle": "1 king bed"}
]
}
What ships with it
1 file 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 · 113 lines · 118 tokens per session scan A a61f302eca8a
airbnb-listing-detail is a skill published in the GitHub repository browser-act/skills (5,875 stars, last pushed 17d ago), licensed MIT. It adds 118 tokens to every session and 1,283 once invoked, about $0.0006 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.
Other skills, from other repositories
skill-monitor
Analyze skill effectiveness across sessions. Computes per-skill metrics (action rate, friction, outcomes), identifies degrading skills, and generates improvement recommendations. Requires session-scan data in metrics.jsonl.
phx-deps-audit
Audit Hex deps for supply-chain security risk — bidi chars, compile-time exec, maintainer changes, typosquats, CVEs. Use after mix deps.update, when checking if a package upgrade is safe, or reviewing mix.lock PR diffs.
release
CONTRIBUTOR TOOL - Cut a plugin release: bump plugin.json version, finalize CHANGELOG, update README if needed, gate on make ci, commit, tag vX.Y.Z, and create the GitHub release. Use when shipping a new plugin version. NOT distributed.
session-deep-dive
Deep qualitative analysis of high-signal sessions. Spawns subagents with v2 template, synthesizes patterns, compares against known findings. Use after /session-scan.
catchup
Summarize and review what changed while you were away. Use after a weekend, vacation, or flight to check missed PRs, git commits, Linear tickets, and meetings — one prioritized brief, not a firehose.
audit
Project health audit and health check — architecture, performance, tests, dependencies, code quality. Use when assessing overall project health, before releases, or after refactors.