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Delete employer conversation

delete_conversation
DestructiveIdempotent

Delete a conversation. Accepts room_name or talent_slug. Uses the connected Himalayas employer account; no extra sign-in needed.

Input Schema

NameRequiredDescriptionDefault
room_nameNoRoom name from list_conversations
talent_slugNoTalent slug (from search_talent results) — resolves to room name automatically

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • removedInput schema / additionalProperties
      Removed value: -false
  2. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare destructiveHint=true and idempotentHint=true, so the safety profile is carried by structured data. The description adds only the auth context (connected employer account, no extra sign-in) and the mutually-exclusive identifier input; it never says whether messages/threads are erased or whether the deletion is recoverable.

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?

Three short sentences, front-loaded with the action, then the accepted inputs, then the auth note. No filler and nothing is buried.

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 destructive mutation with no output schema, the description covers inputs and auth but omits the most consequential detail an agent needs: the blast radius (what exactly is removed) and whether the operation can be undone. Annotations cover the safety hint but not the effect of the call.

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 both parameters carry their own provenance notes (room_name from list_conversations, talent_slug from search_talent results). The description restates the either/or choice, adding little beyond the schema, so baseline 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 (Delete) and resource (a conversation), and the title pins the scope to an employer conversation, which distinguishes it from get_conversation/list_conversations. It does not explicitly name which sibling to prefer, but the destructive action is unambiguous.

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 description tells the agent the two accepted identifiers (room_name or talent_slug) and confirms no extra sign-in is needed, which is useful pre-invocation context. However, it never states when to delete vs. when to use an alternative, nor any prerequisite such as needing an existing conversation.

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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