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andreahaku

GPT-5 MCP Server

by andreahaku

get_conversation_metadata

Retrieve metadata and messages for a specific conversation by providing its ID, enabling you to access conversation history and details for analysis or continuation.

Instructions

Return conversation metadata and messages

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
conversation_idYesConversation ID
Behavior2/5

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

With no annotations, the description must disclose behavioral traits itself, but it only says 'Return conversation metadata and messages'. It implies a read-only operation but provides no details on response structure, pagination, ordering, or potential side effects. This is minimal disclosure.

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?

The description is a single, short sentence that front-loads the verb and resource. It is appropriately sized for a simple getter tool, with no unnecessary words, though it could include more detail without becoming verbose.

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?

Given the tool's simplicity—one parameter, no output schema—the description covers the basic purpose. However, it lacks details on what metadata is returned, message format, or any limitations, leaving some gaps for a complete understanding.

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 only parameter, conversation_id, is fully described in the schema as 'Conversation ID', providing 100% schema description coverage. The tool description adds no additional meaning beyond the schema, so the 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?

The description uses a specific verb 'Return' and names the resource 'conversation metadata and messages', which clearly states the tool's purpose. It distinguishes itself from siblings like summarize_conversation or continue_conversation by focusing on metadata and messages, though it does not explicitly name alternatives.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives such as get_cost_report or set_conversation_options. The description only states the action, omitting context like prerequisites, use cases, or exclusions.

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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