create_analogy

Create a clear analogy comparing a concept to something familiar.

SERVERGadgetHumans API Hub SOURCEpypi:gadgethumans-api-hub-mcp

Medium RISK CLASS

Category Write

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-scotia1973-bot-api-hub/create-analogy.md

WHAT IT DOES

What create_analogy does on GadgetHumans API Hub

AI agents use create_analogy to create or update resources in GadgetHumans API Hub, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your GadgetHumans API Hub environment.

RISK

Why create_analogy is rated Medium

An AI agent can call create_analogy faster than any human can review: one bad instruction and it creates or modifies resources in GadgetHumans API Hub by the hundred, each call as confident as the last.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs create_analogy safely

PolicyLayer is an MCP gateway: it sits between your AI agents and GadgetHumans API Hub, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For create_analogy, this is the rule to start with:

create_analogy Rate-limited

create_analogy 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.

View as policy code

policy.json

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

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect GadgetHumans API Hub, apply this rule, and every create_analogy call is checked against it from then on.

FAQ

Questions about create_analogy

What does the create_analogy tool do? +

Create a clear analogy comparing a concept to something familiar. It is categorised as a Write tool in the GadgetHumans API Hub MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on create_analogy? +

Register the GadgetHumans API Hub MCP server in PolicyLayer and add a rule for create_analogy: 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 GadgetHumans API Hub. Nothing to install.

What risk level is create_analogy? +

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

Can I rate-limit create_analogy? +

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

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

create_analogy is provided by the GadgetHumans API Hub MCP server (pypi:gadgethumans-api-hub-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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