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

Annotations already declare readOnly/idempotent/non-destructive/non-openWorld, so the burden is light. The description still adds real behavioral context beyond them: results are reproducible via seed, the output includes a 95% Wilson interval, the sample cap is 5 million, and CUDA is the only accelerated path.

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?

Three dense sentences with the core purpose front-loaded and no filler. The second sentence packs backend choice and the sample cap efficiently, though the semicolon-joined clause is slightly compressed.

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?

With no output schema, the description usefully names the returned estimate and Wilson interval, and it covers the reproducibility and cap constraints. It is still incomplete for a 4-parameter tool: device_ids is undocumented and the required/optional status of seed and samples is left to the schema.

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 0%, so the description must carry parameter meaning, and it partially does: seed implies reproducibility and the backend enum values are called out, with the 5M cap restating the samples maximum. The device_ids array is entirely unexplained (how many GPUs, and whether it only matters under CUDA), leaving a meaningful gap.

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 states a specific verb+resource ("Estimate pi") plus the algorithm and statistical method, so an agent knows exactly what it computes. It does not differentiate against siblings, but the sibling list (chess, orbits, shadows, trading) is unrelated enough that no differentiation is needed.

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?

"Select CPU or CUDA" plus "CUDA acceleration is available for this tool only" gives a backend-choice heuristic and a relative capability note versus siblings. However, there is no explicit when-to-use/when-not guidance beyond backend selection, and nothing about when a Monte Carlo pi estimate is the appropriate call.

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