research_ready

THE RISK

Medium Risk

Why research_ready needs a policy

This tool modifies the state of a task by marking research as complete and validating documentation. It is a reversible state change (Write), not destructive. Misuse could cause premature implementation starts if research is marked complete incorrectly, giving it medium severity.

From the tool's definition 'Mark research as complete for a task' and 'Validates that all required research items are documented'

Documented attack patterns abuse exactly the kind of access research_ready gives an agent:

POLICY

How to control research_ready

PolicyLayer is an MCP gateway — it sits between your AI agents and Agent Orchestration, and nothing reaches the server without passing your rules. This is the rule we recommend for research_ready:

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "research_ready": {
      "limits": [
        {
          "counter": "research_ready_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

research_ready stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

Create a free account and register Agent Orchestration — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

LIMIT THIS TOOL →

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EXPLORE

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Go deeper

The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Argument validation → Checking tool call arguments against schema and policy before they run.
Scoped token → Per-person credentials that grant a defined subset of servers and tools.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →

FAQ

Questions about research_ready

What does the research_ready tool do? +

Mark research as complete for a task. Validates that all required research items are documented based on task complexity. Call this before starting implementation. It is categorised as a Write tool in the Agent Orchestration MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on research_ready? +

Register the Agent Orchestration MCP server in PolicyLayer and add a rule for research_ready: 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 Agent Orchestration. Nothing to install.

What risk level is research_ready? +

research_ready is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit research_ready? +

Yes. Add a rate_limit block to the research_ready 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 research_ready completely? +

Set action: deny in the PolicyLayer policy for research_ready. 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 research_ready? +

research_ready is provided by the Agent Orchestration MCP server (madebyaris/agent-orchestration). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Agent Orchestration tool call.

Start from Agent Orchestration, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

CHECK YOUR STACK →