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teams_read_chat_messages

Read Microsoft Teams chat messages to retrieve conversation history and track team discussions through your AI agent.

Instructions

Read messages from a Teams chat

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries full burden. It does not disclose read-only vs. destructive behavior, pagination limits, time range constraints, or what the return format looks like. Most critically, it fails to explain the zero-parameter behavior—how the tool identifies the target chat without an ID parameter.

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

Conciseness3/5

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

The single sentence is appropriately brief, but given the ambiguity around parameterless operation and lack of output schema, it is under-specified rather than elegantly concise. The critical missing context forces the user to guess at operational behavior.

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 unusual zero-parameter schema and absence of output schema or annotations, the description is incomplete. It fails to explain chat selection logic, message volume limits, or return structure—information necessary for an agent to invoke this tool successfully.

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?

The input schema contains zero parameters, which establishes a baseline score of 4 per the rubric. The description neither adds nor subtracts from this baseline since no parameters exist to document.

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 (Read) and resource (messages from a Teams chat). However, it fails to distinguish from sibling tool `teams_read_channel_messages`, which is critical since Teams distinguishes between 'chats' (1:1 or group direct messages) and 'channels' (team conversations).

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?

No guidance provided on when to use this versus `teams_read_channel_messages` or the generic `read_messages`. Crucially, given the input schema has zero parameters, the description offers no explanation of how the tool determines which specific chat to read from (e.g., active context, previously selected chat, etc.).

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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