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lmcp_state

Retrieve a structured snapshot of the LMCP environment, including server, tray, and Teams proxy versions, and detected AI client. Use it to verify configuration and diagnose issues.

Instructions

Returns a structured snapshot of the LMCP environment: server/tray/teams-proxy versions, detected AI client...

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

The description implies a read-only operation with no side effects, but without annotations, it does not disclose any potential prerequisites, rate limits, or behavior in edge cases (e.g., if LMCP is not running). Adequate but not 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 a single, concise sentence that front-loads the main purpose. However, it appears truncated (ending with '...'), which slightly reduces clarity.

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?

No output schema is provided, and the description only partially lists returned items, leaving the agent uncertain about the full structure. For a complex environment snapshot, more detail is needed to ensure correct interpretation.

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?

There are no parameters, so the schema coverage is 100%. The baseline for zero parameters is 4, and the description adds no parameter information, which is acceptable.

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 specifies the verb 'Returns' and the resource 'structured snapshot of the LMCP environment', listing specific items like versions and detected AI client. This clearly distinguishes it from sibling tools like lmcp_welcome or get_config.

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 is provided on when to use this tool versus alternatives. Sibling tools such as get_config or lmcp_welcome could perform similar informational roles, but no comparison or usage context is given.

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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