analyze_tone

Analyze the tone, emotion, and sentiment of text with detailed breakdown.

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

Low RISK CLASS

Category Read

Parameters 00 required

Recommended Allowedsee the rule below

Registry record Grade F, identity unverified Pull the record →

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

WHAT IT DOES

What analyze_tone does on GadgetHumans API Hub

AI agents call analyze_tone to retrieve information from GadgetHumans API Hub without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

RISK

Why analyze_tone is rated Low

This tool retrieves and computes analysis results from input text without side effects. No data is modified, deleted, or executed; it is informational only. Misuse by an AI agent (e.g., analyzing untrusted text) poses minimal risk, as the output is analytical metadata rather than actionable commands or state changes.

From the tool's definition Tool analyzes text to return sentiment/emotion/tone metrics with 'detailed breakdown' — no modification, deletion, or execution of external operations occurs. It is purely a data analysis and retrieval function.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs analyze_tone 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 analyze_tone, this is the rule to start with:

analyze_tone Allowed

analyze_tone is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "analyze_tone": {}
  }
}

ALLOW ONLY 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 analyze_tone call is checked against it from then on.

FAQ

Questions about analyze_tone

What does the analyze_tone tool do? +

Analyze the tone, emotion, and sentiment of text with detailed breakdown. It is categorised as a Read tool in the GadgetHumans API Hub MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on analyze_tone? +

Register the GadgetHumans API Hub MCP server in PolicyLayer and add a rule for analyze_tone: 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 analyze_tone? +

analyze_tone is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit analyze_tone? +

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

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

analyze_tone 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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