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KalebJS

groupme-mcp

by KalebJS

post_as_bot

Send automated messages to GroupMe groups using a bot, with optional image attachments, to facilitate communication and announcements.

Instructions

Post a message as a bot.

Args:
    bot_id: The ID of the bot.
    text: Message text.
    picture_url: Optional image URL to attach.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bot_idYes
textYes
picture_urlNo
Behavior2/5

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 states the action ('Post a message') but doesn't describe what 'posting' entails (e.g., where the message appears, visibility, notification behavior), authentication requirements, rate limits, or error conditions. This leaves significant gaps for a tool that likely involves API calls and permissions.

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 efficiently structured with a clear purpose statement followed by parameter explanations. Every sentence serves a purpose: the first establishes the action, and the subsequent lines document parameters. There's no redundant or verbose language, making it easy to parse.

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?

For a tool with 3 parameters, 0% schema coverage, no annotations, and no output schema, the description is insufficient. It covers basic parameter names but lacks critical context: where messages are posted, authentication needs, response format, error handling, and usage boundaries relative to sibling tools. This leaves the agent poorly equipped to use the tool correctly.

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 0%, so the description must compensate. It lists all three parameters with brief explanations, adding meaning beyond the bare schema. However, it doesn't provide format details (e.g., bot_id format, text length limits, picture_url requirements), leaving the agent to guess or rely on external knowledge. This partial compensation earns a baseline score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Post') and resource ('a message as a bot'), making the purpose immediately understandable. It distinguishes from siblings like 'send_message' or 'send_direct_message' by specifying the bot identity aspect. However, it doesn't explicitly contrast with these alternatives in the description text itself.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'send_message' or 'send_direct_message'. There's no mention of prerequisites (e.g., needing bot credentials), appropriate contexts, or exclusion criteria. The agent must infer usage from the tool name alone.

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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