browser_fill
Clear and fill an input element Use when native WebFetch is wrong because you need real browser automation — JS-heavy SPA scraping, login flows with cookie reuse, replay against DOM-drifted versions, AIDefence PII gating before content reaches Claude. For static HTML pages, native WebFetch is fas...
This record as markdown: /tools/ruflo/browser-fill.md
What browser_fill does on Ruflo
AI agents invoke browser_fill to trigger actions in Ruflo. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
Why browser_fill is rated High
This tool performs browser automation by filling input elements, which constitutes executing actions in an external system (the browser/web). It can be used in login flows (submitting credentials), form submissions, and other interactive web operations. The effects depend entirely on what form is being filled — ranging from benign search boxes to credential fields or financial forms.
From the tool's definition 'Clear and fill an input element' with 'real browser automation — JS-heavy SPA scraping, login flows with cookie reuse' — this tool drives a real browser, interacts with DOM elements, and can participate in login flows and form submissions
Attacks that exploit this kind of access
The rule that runs browser_fill safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Ruflo, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For browser_fill, this is the rule to start with:
browser_fill stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Ruflo, apply this rule, and every browser_fill call is checked against it from then on.
Questions about browser_fill
Clear and fill an input element Use when native WebFetch is wrong because you need real browser automation — JS-heavy SPA scraping, login flows with cookie reuse, replay against DOM-drifted versions, AIDefence PII gating before content reaches Claude. For static HTML pages, native WebFetch is faster and free. It is categorised as a Execute tool in the Ruflo MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Ruflo MCP server in PolicyLayer and add a rule for browser_fill: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Ruflo. Nothing to install.
browser_fill is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the browser_fill rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for browser_fill. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
browser_fill is provided by the Ruflo MCP server (ruvnet/ruflo). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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