agent_record
ONE-SHOT: record a computer-use agent (template computer-ghosty-gemini) while it performs a task, and return a public URL to the resulting mp4. Internally: starts screen recording, sends
This record as markdown: /tools/cloud-easybits-easybits/agent-record.md
What agent_record does on EasyBits
AI agents invoke agent_record to trigger actions in EasyBits. 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 agent_record is rated High
Executes an agent to perform arbitrary computer-use tasks with external effects.
From the tool's definition record a computer-use agent while it performs a task
Attacks that exploit this kind of access
The rule that runs agent_record safely
PolicyLayer is an MCP gateway: it sits between your AI agents and EasyBits, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For agent_record, this is the rule to start with:
agent_record 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 EasyBits, apply this rule, and every agent_record call is checked against it from then on.
Questions about agent_record
ONE-SHOT: record a computer-use agent (template computer-ghosty-gemini) while it performs a task, and return a public URL to the resulting mp4. Internally: starts screen recording, sends. It is categorised as a Execute tool in the EasyBits MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the EasyBits MCP server in PolicyLayer and add a rule for agent_record: 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 EasyBits. Nothing to install.
agent_record 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 agent_record 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 agent_record. 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.
agent_record is provided by the EasyBits MCP server (@easybits.cloud/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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