Manage the shared agent task queue. Create tasks for other agents, claim your assigned tasks, report results, or check task status. This enables inter-agent coordination — agents can delegate work and track outcomes.
AI agents use agent_task to create or update resources in Exocortex — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Exocortex environment.
This tool primarily writes to a shared task queue by creating tasks and updating their status/results. While it enables inter-agent coordination (which could have indirect consequences if an agent creates harmful tasks), the tool itself performs reversible write operations: tasks can be modified, reassigned, or cleared.
From the tool's definition Tool description explicitly states it can 'Create tasks for other agents' and 'report results', which are write operations that modify shared state. The task queue is a data structure that this tool creates and updates entries in.
Attacks that exploit this kind of access
Manage the shared agent task queue. Create tasks for other agents, claim your assigned tasks, report results, or check task status. This enables inter-agent coordination — agents can delegate work and track outcomes. It is categorised as a Write tool in the Exocortex MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Exocortex MCP server in PolicyLayer and add a rule for agent_task: 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 Exocortex. Nothing to install.
agent_task is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the agent_task 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_task. 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_task is provided by the Exocortex MCP server (shawnhack/exocortex). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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