Skip to main content
Glama

Get conversation required attributes

get_conversation_required_attributes
Read-onlyIdempotent

Read the attribute_keys of the conversation custom attributes that must be filled before a conversation can be resolved (an empty list means none). Call before making a change.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_conversation_required_attributes"
  }
}

Input Schema

NameRequiredDescriptionDefault
fieldsNoOptional: return only these fields of each record.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds genuinely new semantics: that the return is a list of attribute keys and that an empty list means no attributes are required — information an agent cannot get from annotations or the schema.

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 with no filler: the first defines what is read and how to interpret the result, the second gives the call timing. Nothing is wasted and the key semantic (empty list = none) is front-loaded.

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

Completeness4/5

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

With no output schema, the description usefully explains the return shape and the empty-list edge case. It leaves minor ambiguity about scope (account-wide vs. per-inbox) but covers everything needed to invoke the tool correctly.

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 description coverage is 100% and the single optional 'fields' parameter is documented in the schema as a projection filter. The description adds nothing about it, but with only one fully documented parameter the baseline of 3 applies.

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 ('Read') and a precisely scoped resource ('attribute_keys of the conversation custom attributes that must be filled before a conversation can be resolved'). This is clearly distinct from the sibling update_conversation_required_attributes, though the write counterpart is alluded to rather than named.

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 closing instruction 'Call before making a change' gives an explicit trigger for invocation and implicitly frames this as the read step preceding the update tool. It stops short of naming the alternative tool or stating any when-not-to-use condition, so it falls just short of a 5.

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.

Resources