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usenotra

notra

Official
by usenotra

post_chat_message

Send a message to an existing chat and receive the AI assistant's reply. Optionally select a model or attach context from GitHub or Linear.

Instructions

Post a message to an existing chat and return the assistant's reply text

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoModel to use for the reply
chatIdYesThe chat ID to send a message to
contextNoRepository or Linear context to attach to the chat
messageYesMessage to send
timezoneNoIANA timezone for contextual responses
thinkingLevelNoThinking budget level
enableThinkingNoWhether to enable model thinking
externalChannelIdNoExternal channel to associate with the chat
Behavior2/5

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

Annotations only provide destructiveHint=false, so the description carries the transparency burden. It discloses that the tool posts a message and returns the reply, but does not explain synchronous behavior, permission requirements, or side effects. Many optional features like context, thinking, and external channels are ignored.

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 a single sentence with zero wasted words, making it extremely concise and front-loaded. Every word contributes to understanding the core action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (8 parameters, no output schema), the description is too minimal. It does not mention the behavior of optional parameters like model, context, thinking, or the return format beyond 'reply text', leaving the agent under-informed.

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?

All 8 parameters have schema descriptions (100% coverage), so the description adds no additional semantic value beyond what is already in the input schema.

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 verb 'Post a message' to an existing chat and specifies the outcome 'return the assistant's reply text'. It distinguishes from sibling tools that list, get, or create chats, and from post-generation tools.

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 when an existing chat ID is available, but does not explicitly guide when to use this tool versus alternatives like 'create_chat' for new chats or 'get_chat' for reading messages. No exclusion criteria are provided.

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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