reading_time

A read tool on the GadgetHumans API Hub MCP server.

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/reading-time.md

WHAT IT DOES

What reading_time does on GadgetHumans API Hub

AI agents call reading_time 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 reading_time is rated Low

Based on the tool name, this appears to be a read-only utility that computes reading time estimates from text input. It performs no modifications, deletions, or external operations. The empty description lowers confidence slightly, but the utility context (alongside similar tools like ascii_table, hashing, base64) and the descriptive name strongly suggest it retrieves or computes information without side effects.

From the tool's definition Tool name 'reading_time' suggests calculating or estimating the time needed to read text content. No description provided, but the name indicates data retrieval/computation without side effects.

Attacks that exploit this kind of access

RECOMMENDED RULE

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

reading_time Allowed

reading_time 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": {
    "reading_time": {}
  }
}

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 reading_time call is checked against it from then on.

FAQ

Questions about reading_time

What does the reading_time tool do? +

reading_time is a read tool on the GadgetHumans API Hub MCP server. 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 reading_time? +

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

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

Can I rate-limit reading_time? +

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

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

reading_time 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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