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LIVEAIHELP — Hire a Live Human Expert

Check queue position

check_queue
Read-onlyIdempotent

Check your position in the expert holding queue. Poll until status is matched, then use the returned session_id with send_message / read_messages.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "queue_id": "<queue_id>"
    },
    "name": "check_queue"
  }
}

Input Schema

NameRequiredDescriptionDefault
queue_idYesThe queue_id from hire_human_expert.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover safety (readOnly, idempotent, non-destructive), and the description adds real value on top: this is a polling operation and it yields a session_id that gates subsequent send_message/read_messages calls. It leaves out what status values exist and what happens if the queue expires, but the core behavior is disclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences, zero filler, with the primary action and the follow-on step front-loaded. Every clause earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a polling tool with no output schema, the description never says what statuses to expect or how often to poll, which is the main thing an agent needs to run the loop correctly. It is adequate but leaves a meaningful operational gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the schema already explains queue_id comes from hire_human_expert, so the description adds nothing beyond it. Baseline 3 is appropriate for a single fully-documented parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Check your position in the expert holding queue'), which is unambiguous and clearly distinct from siblings like send_message or read_messages. It could have named the alternative (hire_human_expert) for creating the queue, but the purpose itself is sharp.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit workflow guidance: 'Poll until status is matched, then use the returned session_id with send_message / read_messages.' That tells the agent both the loop and the handoff. It stops short of saying when not to call it (e.g. after the session exists, don't keep polling), so no full 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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