lmcp_state

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

With no annotations, the description carries the full burden. "Returns a snapshot" implies a read, but it doesn't confirm read-only safety, note any side effects, permissions, or rate limits, and the field enumeration is cut off mid-sentence ("cloud..."). Useful hints exist but the behavioral picture is thin.

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?

It is a single front-loaded sentence with no padding, but it trails off with an ellipsis ("cloud..."), leaving the enumeration visibly incomplete rather than deliberately brief.

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?

For a zero-param read tool with no output schema, the description should convey what the snapshot contains, and it partly does by listing fields. But the truncated ending and absence of any return-shape or scope detail leave it only minimally adequate.

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?

The tool takes zero parameters, so per the rubric the baseline is 4. The description correctly implies no inputs are needed to obtain the snapshot.

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?

States a specific verb ("Returns") and resource ("structured snapshot of the LMCP environment") and enumerates several fields (server/tray versions, detected AI client). However, it does nothing to distinguish itself from sibling diagnostic tools like lmcp_doctor, get_config, or run_diagnostics, so it lands at clear-but-undifferentiated.

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?

There is no when-to-use guidance and no mention of alternatives, even though the sibling list contains several overlapping diagnostic/config tools (lmcp_doctor, get_config, run_diagnostics, update_self_diagnosis). The agent is left to guess which one to call.

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