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List employer conversations

list_conversations
Read-only

List all your messaging conversations with last message preview. Shows conversation status (awaiting reply, new reply, read). Uses the connected Himalayas employer account; no extra sign-in needed.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description goes beyond them by disclosing the return payload ('last message preview') and the enumerated status values (awaiting reply, new reply, read), plus the auth model ('no extra sign-in needed') – genuinely useful context for a tool with no output schema.

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

Conciseness4/5

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

Three short sentences, front-loaded with the core action and progressively adding scope, return content, and auth context. Each sentence carries information; only the auth sentence is arguably marginal, but it is brief.

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?

For a read-only, parameterless list tool with no output schema, the description covers what is returned (preview + statuses) and the account context needed to call it. Missing only minor operational detail such as ordering or pagination limits, which is acceptable at this complexity.

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

Parameters4/5

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

The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline for a parameterless tool applies. No missing parameter context.

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 and resource ('List all your messaging conversations') and adds scope via 'employer account', which distinguishes it from the candidate-side conversation tools in the sibling list. It stops short of naming the sibling it contrasts with (e.g. list_my_conversations), so differentiation is implied rather than explicit.

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

Usage Guidelines3/5

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

The phrase 'Uses the connected Himalayas employer account' implies this is the employer-side listing, which is the key selection context against list_my_conversations and get_my_conversation. However there is no explicit when-to-use/when-not-to guidance and no alternative named, so usage must be inferred.

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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