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Neuratel-AI

Neuratel MCP Server

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by Neuratel-AI

get_conversation_timeline

Get a unified timeline of messages and voice sessions for a conversation, merging chat exchanges and call attempts chronologically.

Instructions

Get a unified timeline of messages + voice sessions for a conversation.

Useful when a contact has both chat exchanges and call attempts on the same thread — the timeline interleaves them chronologically.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
sinceNo
beforeNo
conversation_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

There are no annotations, so the description carries the burden of behavioral disclosure. It reveals that the tool interleaves messages and voice sessions chronologically, which is a key behavior. However, it does not disclose details like whether the timeline is ascending/descending, how pagination works, or what the response structure looks like. This is adequate but not rich.

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 two sentences long and front-loaded: the first sentence states the core action, and the second adds context on when to use it. Every sentence earns its place, though it could be slightly more structured (e.g., explicit parameter notes) without bloating.

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?

The tool is relatively simple (4 params, output schema exists), so the description doesn't need to explain return values. It covers the primary use case and differentiates from siblings. The lack of pagination details is a minor gap but not critical given the schema provides types and defaults.

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 has 0% description coverage, and the description does not add any parameter-specific semantics beyond the schema itself. The parameters (limit, since, before, conversation_id) are self-explanatory from their names and types, so the baseline of 3 is appropriate given the schema is decent.

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 uses a specific verb ('Get') and resource ('unified timeline of messages + voice sessions for a conversation'), making the tool's function immediately clear. It also distinguishes itself from likely sibling tools like list_conversation_messages by emphasizing the interleaved chronological merging of both message types.

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 states when this tool is useful ('when a contact has both chat exchanges and call attempts on the same thread'), providing clear context. It does not explicitly name alternative tools or say when not to use it, but the usage context is specific enough to guide an agent.

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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