neuron

Bot API Get Messages

neuron_bot_api_get_messages

Read-onlyIdempotent

Retrieve message history for a specific conversation with cursor-based pagination. Requires a valid API key.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Maximum number of messages to return (default: 50)
`apiKey`	Yes	Bot API key with 'nrn_' prefix for authentication
`before`	No	Cursor for pagination — retrieve messages created before this message ID or ISO 8601 timestamp
`conversationId`	Yes	Unique identifier (UUID) of the conversation to retrieve messages from

TDQS

B3.3/5.0

Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds that it uses cursor-based pagination and requires API key authentication, which provides some additional behavioral context. However, it does not explain pagination behavior, error handling, or rate limits. With annotations covering safety, a 3 is appropriate.

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?

The description is extremely concise at two sentences, front-loading the main purpose and then adding the authentication requirement. Every word earns its place with no redundancy.

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 that the tool has no output schema, the description should at least hint at the return format or pagination details (e.g., what the cursor represents or that it returns an array of messages). It is adequate but could be more complete for a tool with moderate complexity.

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%, so the input schema already documents all four parameters thoroughly. The description offers no additional parameter-level meaning beyond what the schema provides. Baseline of 3 is correct.

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 clearly states the tool retrieves message history for a specific conversation using cursor-based pagination. It specifies the verb 'retrieve' and resource, but does not differentiate from the sibling 'neuron_get_messages' which likely has a similar purpose, so it misses full distinction.

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?

The description mentions a prerequisite (requires API key) but provides no guidance on when to use this tool over alternatives like 'neuron_get_messages' or other bot API tools. There is no mention of appropriate contexts 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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TDQS

B3.4/5.0

Disambiguation3/5

Most tools are clearly separated by resource type, but there is meaningful overlap in messaging entry points (send_message, send_whatsapp, compose_message, bot_api_send) and contact ingestion/sync tools (import_contacts, populate_contacts, sync_whatsapp_contacts). The descriptions help disambiguate, but with 309 tools an agent will frequently need to read closely to pick the right one.

Naming Consistency4/5

The overwhelming majority of tools follow a consistent verb_noun snake_case pattern: create_*, get_*, list_*, update_*, delete_*. Minor deviations like sales_stats, lead_stats, wallet_balance, and whoami break the pattern slightly, but overall naming is highly predictable.

Tool Count1/5

309 tools is an extreme count for any MCP server, even a broad platform. This creates significant cognitive load and navigation overhead for agents, and far exceeds the well-scoped 3-15 tool range where coherence is strongest.

Completeness4/5

The tool surface is remarkably comprehensive across bots, contacts, campaigns, flows, knowledge bases, personas, marketplace, wallet, and products. Minor gaps exist — lead sources lack update/delete tools, and there is no single get_task or get_webhook alongside their list/update/delete counterparts — but these are workable gaps rather than dead ends.

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