Use when an agent needs to drive a real Chrome window via opencli — inspect a page, fill forms, click through logged-in flows, or extract data ad-hoc. Covers the selector-first target contract, compound form fields, stale-ref handling, network capture, and the agent-native envelopes the CLI returns. Not for writing adapters — see opencli-adapter-author for that.
68
82%
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Critical
Do not install without reviewing
Security
2 findings: 1 critical severity, 1 high severity. Installing this skill is not recommended: please review these findings carefully if you do intend to do so.
Detected high-risk code patterns in the skill content — including its prompts, tool definitions, and resources — such as data exfiltration, backdoors, remote code execution, credential theft, system compromise, supply chain attacks, and obfuscation techniques.
This documentation exposes powerful browser-driving capabilities (tab binding, in-page/frame eval, network capture, file upload, download/watch) that can be used to read and exfiltrate sensitive user data (cookies, card numbers, API responses, local files) and to execute arbitrary JS in page/frame contexts — enabling credential theft and remote data exfiltration if misused.
The skill handles credentials insecurely by requiring the agent to include secret values verbatim in its generated output. This exposes credentials in the agent’s context and conversation history, creating a risk of data exfiltration.
The skill includes examples that require embedding user credentials or sensitive fields verbatim into commands (e.g., a literal password in the login recipe and an eval that reads a card number), which forces the LLM to handle/output secret values directly.
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
The required workflow includes `web read --url <url>` and “driving a live browser”, which fetches arbitrary outsider-authored web page content at runtime and passes the extracted Markdown/page text into the agent’s context for LLM processing (indirect prompt-injection risk).
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