stream_send_message⚠️ WRITE: post a new message to a channel, attributed to user_id (must be an existing user in the app). POST /api/v2/chat/channels/{type}/{id}/message.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Channel id. | |
| text | Yes | Message text. | |
| type | Yes | Channel type, e.g. "messaging". | |
| user_id | Yes | Existing user id to send the message as. | |
| mentioned_users | No | User ids to @mention. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide destructiveHint=true, and the description reinforces this with the WRITE warning. It adds the endpoint and the existing-user prerequisite, but the prerequisite is already present in the schema's user_id description. There is little new behavioral detail such as side effects, response behavior, or failure modes.
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 a single front-loaded sentence with the WRITE disclaimer and endpoint, which is efficient. It repeats 'WRITE' from the title, creating a small redundancy, but otherwise contains no filler.
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?
For a straightforward message-posting call, the description and schema provide enough to invoke it correctly. However, there is no output schema and the description says nothing about the expected response, error cases, or side effects, leaving some operational uncertainty for the agent.
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?
The schema covers 100% of parameters with meaningful descriptions, so the description does not need to compensate. It does not add significant meaning beyond what the schema already states, earning the baseline 3 for well-covered schemas.
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 specific action: 'post a new message to a channel, attributed to user_id.' It also names the resource and endpoint, making it unambiguous. This distinguishes it from siblings like stream_send_reaction because it targets message creation, not reactions.
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 WRITE label and 'post a new message' wording imply this is the tool to use for sending messages, but the description never explicitly says when not to use it or names alternatives among the read/query siblings. Usage context is implied rather than stated, leaving the agent to infer routing.
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.
Each tool targets a distinct resource and action: app info, channel state, messages, reactions, replies, unread counts, and various query types. Even similar tools like get_channel vs query_channels are clearly separated by single-item vs list operations.
All tools follow the consistent pattern stream_<verb>_<resource> (e.g., stream_get_message, stream_query_channels, stream_send_message). Verb usage is coherent across the set.
With 13 tools, the set is well-scoped for a chat API server, covering core read, query, search, and write operations without excessive fragmentation.
Core chat workflows are covered: app info, channel access, messaging, reactions, threads, unread counts, and user/channel queries. Missing mutations like channel/message update or delete are notable but not severe, as the get-or-create channel behavior and send actions cover primary use cases.