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send_message

Send messages to Zulip streams and topics using markdown formatting for AI agent communication and bot integration.

Instructions

Send a message to a specific stream and topic (fire-and-forget).

Args: stream: Stream/channel name. topic: Topic name. content: Message content (supports Zulip markdown).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
streamYes
topicYes
contentYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries full burden and adds valuable behavioral context: 'fire-and-forget' indicates asynchronous operation without delivery guarantees, and it specifies that content supports Zulip markdown. It doesn't cover rate limits, authentication requirements, or error conditions, but provides more than minimal behavioral disclosure for a messaging tool.

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?

Perfectly structured with a clear purpose statement upfront, followed by organized parameter explanations. Every sentence earns its place: the first establishes core functionality and behavior, while the parameter descriptions provide essential context without redundancy. No wasted words or unnecessary elaboration.

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?

Given the tool's moderate complexity (3 required parameters), no annotations, and the presence of an output schema (which handles return values), the description is reasonably complete. It covers purpose, key behavior, and parameter meanings. However, it lacks information about error conditions, permissions, or how this interacts with sibling tools like 'typing' indicators.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description compensates well by explaining all three parameters: 'stream' as stream/channel name, 'topic' as topic name, and 'content' as message content with Zulip markdown support. This adds meaningful semantics beyond the bare schema types, though it doesn't provide format examples or constraints.

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 clearly states the specific action ('Send a message'), the target resource ('to a specific stream and topic'), and the behavioral characteristic ('fire-and-forget'). It distinguishes this from sibling tools like 'send_direct_message', 'reply', and 'edit_message' by specifying the stream/topic destination rather than direct messaging or editing existing messages.

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

Usage Guidelines3/5

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

The description implies usage context through 'fire-and-forget' (suggesting asynchronous sending without waiting for delivery confirmation) and specifying stream/topic targeting. However, it doesn't explicitly state when to use this versus alternatives like 'send_direct_message' for private messages or 'reply' for threaded responses, nor does it mention prerequisites like required permissions or stream subscription status.

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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