neuron_edit_messageEdit the content of a previously sent message in a conversation. Only the message sender can edit their messages.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Unique identifier (UUID) of the conversation | |
| msgId | Yes | Unique identifier (UUID) of the message to edit | |
| content | Yes | New text content to replace the existing message |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description aligns with annotations (idempotentHint=true, destructiveHint=false) and adds the important behavioral detail that only the sender can edit. It does not contradict annotations and provides useful context beyond the structured metadata.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences that front-load the essential purpose and constraint. Every word is necessary and there is no wasted text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (3 required params, no output schema) and the annotations, the description is fairly complete. It covers the core behavior and a key constraint, though it could mention error cases or what happens if the message is not found.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents all three parameters. The description does not add any additional meaning beyond what the schema provides, so it meets the baseline expectation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'edit' and the resource 'content of a previously sent message'. It distinguishes from sibling tools like send_message and delete_message by specifying that it modifies an existing message. The constraint 'only the message sender can edit' further clarifies its scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear condition for usage: 'Only the message sender can edit their messages.' This helps the agent decide when to use this tool, though it does not explicitly mention alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.