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oase-mcp

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by oase-app

Send a message to an Oase

send_message

Publish markdown chat messages to your oase, with options to select the oase and reply under a root message to maintain threaded conversations.

Instructions

Send a markdown chat message into an oase. Omit oase_id to use the default (last joined) oase. Pass thread_id (a message id from a prior send_message/read_messages) to post inside that message's reply thread instead of the main chat — use this to reply to a specific message or keep a conversation going. Threads are one level deep: you cannot reply to a reply. To continue a conversation, always thread under the root message; a reply's own id passed as thread_id is auto-resolved to its thread root.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messageYesThe message text (markdown supported).
oase_idNoTarget oase id. Defaults to the last joined oase.
thread_idNoRoot message id to reply under (keeps the conversation threaded). Must be a main-chat message, not a reply — replies can't be nested. Omit to post to the main chat.
Behavior4/5

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

With no annotations provided, the description discloses key behaviors: default oase selection, thread-post semantics (one level deep, root resolution, auto-resolution of reply ids). It does not describe return values or potential errors, but these are not strictly expected for a send operation and the threading details are thorough.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is five sentences, front-loaded with the core purpose, then detailed threading rules. It is efficient without redundant phrasing; each sentence contributes to operational clarity.

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 3-parameter tool with no output schema, the description covers default oase behavior, threading constraints, and explicit use-case guidance. Missing details like message length limits are minor and not essential for correct invocation; markdown support is mentioned.

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?

Schema covers all 3 parameters with descriptions, providing a baseline of 3. The description adds meaningful context beyond the schema: the default behavior for oase_id, the validation that thread_id must be a main-chat message, and auto-resolution logic — all of which clarify usage conditions not evident from the schema alone.

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 action ('Send a markdown chat message into an oase') with a specific verb and resource, and implicitly distinguishes from siblings like send_post (which sends posts, not chat messages). The mention of threading further separates it from read_messages and react_to_message.

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

Usage Guidelines4/5

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

It provides explicit guidance on when to use thread_id (to reply to a specific message or continue a conversation) and explains the default behavior when oase_id is omitted. It does not explicitly name alternative tools for comparisons, but the channel-specific language ('oase', 'chat message') is sufficient to infer posting vs. messaging contexts.

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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