Skip to main content
Glama

pearl-api-mcp-server

askExpert

askExpert

Use this when the user explicitly asks to speak with a real human expert, needs personalized advice in a complex or sensitive domain, or says something like 'Can I talk to a real expert?'. Supports phone callback — pass phoneNumber and contactPreference='phone' if the user wants a call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
questionYesThe user's question
sessionIdNoOptional session ID for continuing a conversation
chatHistoryNoOptional conversation history. This ensures experts see the complete context
phoneNumberNoCustomer's phone number for expert callback in E.164 format (e.g., +15551234567). Only pass when the user explicitly provides it.
contactPreferenceNoCustomer's preferred contact method. Set to 'phone' when the user wants a phone callback.
enableMockResponseNoWhen true, the API returns a hardcoded mock expert success response instead of routing to a real expert. Useful for testing downstream behavior.

TDQS

A3.9/5.0
Behavior3/5

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

The description reveals that the tool routes to a human expert and supports phone callback via specific parameters, which is useful behavior. With no annotations, the description carries the burden, but it does not explain response behavior, latency, or potential limitations, leaving some uncertainty about what happens after invocation.

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?

The description is two sentences, front-loaded with usage triggers and the phone callback option. Every word contributes value, with no redundancy or unnecessary details.

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 tool with six parameters and no output schema, the description gives core usage context but omits what the user can expect after submission (e.g., chat reply vs. separate callback). It also does not differentiate from the sibling 'askPearlExpert', which could be a similar function, making the description only partially complete.

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?

The schema provides comprehensive descriptions for all 6 parameters (100% coverage), so the description adds little beyond restating the phone callback combination. It does not clarify enableMockResponse or sessionId beyond schema, so it stays at the baseline for full schema coverage.

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

Purpose5/5

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

The description clearly states the tool's purpose: to connect the user with a real human expert. It provides specific triggers like 'explicitly asks to speak with a real human expert' and 'needs personalized advice in a complex or sensitive domain', which distinguishes it from siblings like askPearlAi that likely provide AI-based answers.

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?

The description explicitly states when to use the tool: when the user asks for a real expert, needs complex/sensitive advice, or uses phrases like 'Can I talk to a real expert?'. However, it does not name alternative tools or provide when-not-to-use scenarios, so it falls short of full comparative guidance.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4/5.0
Disambiguation4/5

The tools are distinguished by request type: AI-only, expert-only, hybrid, and verification. Descriptions explicitly state when to use each, but askExpert and askPearlExpert both lead to human experts and askPearlAi vs askPearlExpert could be confused without careful reading.

Naming Consistency3/5

Three tools share the 'ask' prefix, but verifyAnswer breaks the pattern. Within the 'ask' group, 'askExpert' lacks the 'Pearl' brand used in 'askPearlAi' and 'askPearlExpert', making naming mixed and not fully systematic.

Tool Count5/5

Four tools is well-scoped for a Q&A/advice server, covering distinct interaction modes without being overly minimal or excessive. Each tool has a clear role.

Completeness4/5

The set covers the main ways to obtain an answer (AI, human, hybrid) plus a verification step. A minor gap is lack of a tool for managing or tracking ongoing requests, but the surface feels complete for the apparent synchronous use case.

Resources