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/goofish-item-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/goofish-item-detail)<a href="https://agentmods.dev/skills/browser-act/skills/goofish-item-detail"><img src="https://agentmods.dev/badge/skills/browser-act/skills/goofish-item-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/goofish-item-detail"><img src="https://agentmods.dev/badge/skills/browser-act/skills/goofish-item-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 | $0.00195 | $0.01576 |
| Opus 5 | $0.00097 | $0.00788 |
| Sonnet 5 | $0.00039 | $0.00315 |
| Haiku 4.5 | $0.00019 | $0.00158 |
Grade A, and why
goofish-item-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 — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Goofish (闲鱼) — Item Detail
item URL (or item_id + category_id) → full listing data: title, price, seller info, description, images, tags, want-count
Language
All process output to user (progress updates, process notifications) follows the user's language.
Objective
Load a single Goofish item detail page and extract its complete listing data including seller information, item description, image gallery, and attribute tags.
Prerequisites
- Browser with an active Goofish session (login required — item detail pages require authenticated access)
- Target item URL format:
https://www.goofish.com/item?id={item_id}&categoryId={category_id}
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.
2. Login Verification
If login status for Goofish has been confirmed in the current session → skip this step.
Otherwise: open https://www.goofish.com/ and observe the page:
- User avatar or account entry exists → logged in, continue
- Login/register prompt → not logged in; inform user that login is required; assist login flow
User refuses or cannot log in → terminate execution.
Capability Components
This Skill's operational boundary = what the user can manually do in their browser. It only reads data already displayed on the page. JS code is encapsulated in Python files under the
scripts/directory, invoked viaeval "$(python scripts/xxx.py {params})".$(...)is bash syntax; use the bash tool for execution.
Network Capture: load item detail page
The item detail API (mtop.taobao.idle.pc.detail/1.0/) auto-fires when navigating to the item URL. Provide parameters via URL:
navigate https://www.goofish.com/item?id={item_id}&categoryId={category_id}wait stable- Proceed to DOM extraction below
Error handling:
- If a CAPTCHA slider appears ("Please slide to verify"): the session is rate-limited. Wait 5–10 minutes, or use remote-assist to complete the slider manually, then re-navigate.
- If "网络不见了" error page appears: the item page API call failed. Retry once after 30 seconds; if it persists, the session may be temporarily blocked.
- If item shows "该宝贝已下架" or similar: item has been removed/sold — skip and move to next item.
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 · 121 lines · 195 tokens per session scan A c84e820263bf
goofish-item-detail is a skill published in the GitHub repository browser-act/skills (5,875 stars, last pushed 17d ago), licensed MIT. It adds 195 tokens to every session and 1,576 once invoked, about $0.0010 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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