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

Goes well beyond the readOnly/openWorld annotations by disclosing plan-tier behavior differences (Studio vs Free/Pro output), that returned text originates from the tested site, that it is wrapped in <site-content> tags, and a direct instruction to treat it as untrusted evidence rather than commands. This is exactly the kind of prompt-injection and data-provenance context annotations cannot carry.

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?

Front-loads what is returned before the plan-tier and safety caveats, and every clause is substantive. The single long sentence is dense but not padded; it could be split for readability, which is the only deduction.

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?

Output schema exists so return values need no further explanation, yet the description still clarifies output structure and plan gating, and it fully covers the one input. Nothing an agent needs to call this correctly is missing.

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 coverage is 100% and the single test_id parameter is fully documented (format, source from run_test), so the schema already carries the semantics. The description adds no format or sourcing detail beyond what the schema states, matching the baseline 3.

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 (get) and resource (results of a finished Menso test) and enumerates what is returned: TRACES score, per-dimension scores and reasons, task outcome, and plan-dependent friction points. This clearly separates it from siblings like run_test and get_status.

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 phrase 'results of a finished Menso test' implies this is only for completed tests, routing the agent to get_status for in-progress checks. However, it never names an alternative tool or states the precondition explicitly, so the guidance is contextual rather than spelled out.

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