m365_meetings

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

Since no annotations are provided, the description carries the full burden of behavioral disclosure. It effectively describes key behavioral traits: the tool returns structured data (notes, decisions, tasks with owners, mentions), has prerequisites (transcription enabled, 4-hour delay), and has exclusions (channel meetings, meetings without transcription). However, it doesn't mention error handling, rate limits, or authentication needs, which could be relevant for an AI agent.

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

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

The description is well-structured and concise, with each sentence earning its place. It starts with the core purpose, then details returns, prerequisites, use cases, and exclusions in a logical flow. There's no redundant or verbose language, making it easy for an AI agent to parse quickly.

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

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

Given the tool's complexity (involving meeting insights with prerequisites) and the absence of annotations and output schema, the description does a good job of covering essential context: purpose, usage, behavioral constraints, and exclusions. However, without an output schema, it could benefit from more detail on the structured data format (e.g., sample outputs or data types), which would help the agent understand what to expect.

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

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

Schema description coverage is 100%, so the schema already documents all three parameters (meeting_id, join_url, since) with clear descriptions. The description doesn't add any parameter-specific information beyond what's in the schema, such as explaining interactions between parameters or providing examples. The baseline score of 3 is appropriate when the schema does the heavy lifting.

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

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

The description clearly states the tool's purpose: 'Get AI-generated meeting summaries, action items, and mentions from Teams.' It specifies the resource (Teams meetings) and the verb (get) with concrete outputs (summaries, action items, mentions). It distinguishes itself from sibling tools like m365_chat or m365_search by focusing specifically on meeting insights rather than chat or general search functionality.

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

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 ('Post-meeting follow-up', 'Finding action items assigned to you', 'Checking what you missed in meetings') and when not to use it ('Does NOT work for: Channel meetings, Meetings without transcription enabled'). It also mentions prerequisites ('Transcription enabled during meeting', '~4 hours after meeting ends for insights to be ready'), giving clear context for appropriate usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.