process_goal_with_gotcha · AGI- MCP: Risk & Policy

WHAT IT DOES

What process_goal_with_gotcha does on AGI-MCP

AI agents invoke process_goal_with_gotcha to trigger actions in AGI-MCP. 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 process_goal_with_gotcha needs a policy

This tool executes a complex, multi-step agentic pipeline across an entire cognitive architecture framework. Given the sibling tools include execute_command, execute_subagent, and execute_skill, processing a goal through 'all GOTCHA framework layers' almost certainly triggers cascading executions with unpredictable and potentially wide-ranging side effects.

From the tool's definition 'Process a goal through all GOTCHA framework layers' — triggers a multi-layer cognitive framework pipeline (GOTCHA) that orchestrates task management and reasoning, likely invoking subagents, skills, commands, and memory operations as part of an agentic…

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

process_goal_with_gotcha Rate-limited

process_goal_with_gotcha 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": {
    "process_goal_with_gotcha": {
      "limits": [
        {
          "counter": "process_goal_with_gotcha_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 AGI-MCP, so you can run agents against it safely.

FAQ

Questions about process_goal_with_gotcha

What does the process_goal_with_gotcha tool do? +

Process a goal through all GOTCHA framework layers. It is categorised as a Execute tool in the AGI-MCP MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on process_goal_with_gotcha? +

Register the AGI- MCP server in PolicyLayer and add a rule for process_goal_with_gotcha: 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 AGI-MCP. Nothing to install.

What risk level is process_goal_with_gotcha? +

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

Can I rate-limit process_goal_with_gotcha? +

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

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

process_goal_with_gotcha is provided by the AGI- MCP server (muah1987/agi-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.