effect_probe
Verifica se uma acao no jogo produziu o efeito esperado.
This record as markdown: /tools/mcp-godot-desenvolvimento/effect-probe.md
What effect_probe does on Mcp Godot Desenvolvimento
AI agents use effect_probe to create or update resources in Mcp Godot Desenvolvimento, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Mcp Godot Desenvolvimento environment.
Why effect_probe is rated Medium
An AI agent can call effect_probe faster than any human can review: one bad instruction and it creates or modifies resources in Mcp Godot Desenvolvimento by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
The rule that runs effect_probe safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Mcp Godot Desenvolvimento, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For effect_probe, this is the rule to start with:
effect_probe 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.
The button opens the PolicyLayer dashboard: create your workspace, connect Mcp Godot Desenvolvimento, apply this rule, and every effect_probe call is checked against it from then on.
Questions about effect_probe
Verifica se uma acao no jogo produziu o efeito esperado. It is categorised as a Write tool in the Mcp Godot Desenvolvimento MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Mcp Godot Desenvolvimento MCP server in PolicyLayer and add a rule for effect_probe: 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 Mcp Godot Desenvolvimento. Nothing to install.
effect_probe 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 effect_probe 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 effect_probe. 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.
effect_probe is provided by the Mcp Godot Desenvolvimento MCP server (joabcostamd/mcp-godot-desenvolvimento). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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