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clickup_chat_message_send

Send messages to ClickUp Chat channels to communicate with teams. Post announcements, share updates, or coordinate tasks in designated channels using markdown formatting and mentions.

Instructions

Post a new top-level message to a ClickUp Chat channel. For replies inside a thread use clickup_chat_reply_send; for DMs use clickup_chat_dm. Returns the created message object including its new id, which you can pass to clickup_chat_reaction_add, clickup_chat_reply_send, etc.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
channel_idYesID of the target channel. Obtain from clickup_chat_channel_list (field: id).
contentYesMessage body. Supports markdown, @mentions (e.g. '@username'), and emoji.
team_idNoWorkspace (team) ID. Obtain from clickup_workspace_list (field: id). Omit to use the default workspace from config.
Behavior4/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It effectively describes the operation (posting a message), mentions the return value (created message object with id), and suggests downstream uses (passing id to reaction_add, reply_send). However, it doesn't mention potential constraints like rate limits, authentication requirements, or error conditions.

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 perfectly concise with two sentences that each serve distinct purposes: the first defines the tool's purpose and usage boundaries, the second describes the return value and downstream implications. Every word earns its place with no redundancy or wasted text.

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?

For a tool with no annotations and no output schema, the description does well by explaining the operation, differentiating from siblings, and describing the return value. However, it could be more complete by mentioning authentication requirements or potential error scenarios, which would be helpful given the lack of structured behavioral annotations.

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 schema already fully documents all three parameters. The description doesn't add any parameter-specific information beyond what's in the schema, which is acceptable given the comprehensive schema coverage. The baseline score of 3 reflects adequate but not enhanced parameter documentation.

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 ('Post a new top-level message') and target resource ('to a ClickUp Chat channel'), distinguishing it from sibling tools like clickup_chat_reply_send and clickup_chat_dm. It explicitly differentiates this tool's purpose from those alternatives.

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

Usage Guidelines5/5

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

The description provides explicit guidance on when to use this tool ('For replies inside a thread use clickup_chat_reply_send; for DMs use clickup_chat_dm'), clearly defining its scope and naming specific alternatives. This helps the agent select the correct tool for the intended use case.

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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