start_work_on_task | PolicyLayer

WHAT IT DOES

What start_work_on_task does on Eureka Labo Task Management MCP Server

AI agents invoke start_work_on_task to trigger actions in Eureka Labo Task Management MCP Server. 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 IT NEEDS A POLICY

Why start_work_on_task needs a policy

This tool triggers automated operations (git baseline capture, work session initialization) whose effects depend on the current repository state and task context. While not destructive (changes are reversible), and not a simple read operation, it executes an external operation that modifies tracking state and workflow context.

From the tool's definition Tool description states it 'Begin working on a task' and 'Captures git baseline for change tracking', indicating it executes a workflow that initiates a git capture operation and changes the local development state.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

start_work_on_task Rate-limited

start_work_on_task 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "start_work_on_task": {
      "limits": [
        {
          "counter": "start_work_on_task_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Eureka Labo Task Management MCP Server, so you can run agents against it safely.

FAQ

Questions about start_work_on_task

What does the start_work_on_task tool do? +

Begin working on a task. Captures git baseline for change tracking. Requires clean working directory (no uncommitted changes). It is categorised as a Execute tool in the Eureka Labo Task Management MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on start_work_on_task? +

Register the Eureka Labo Task Management MCP Server MCP server in PolicyLayer and add a rule for start_work_on_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 Eureka Labo Task Management MCP Server. Nothing to install.

What risk level is start_work_on_task? +

start_work_on_task is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit start_work_on_task? +

Yes. Add a rate_limit block to the start_work_on_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.

How do I block start_work_on_task completely? +

Set action: deny in the PolicyLayer policy for start_work_on_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.

What MCP server provides start_work_on_task? +

start_work_on_task is provided by the Eureka Labo Task Management MCP Server MCP server (mazemaze/mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.