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

Annotations already cover the safety profile (readOnlyHint, idempotent, non-destructive, openWorld), so the description's real contribution is disclosing the shape of the result set: three distinct derived metrics and the >50% threshold used for the Nakamoto coefficient. That matters because no output schema exists. It stops short of saying whether shares are percentages or fractions, or how pools with zero blocks are represented.

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?

One dense sentence that front-loads the computation and closes with the window values; nothing is extraneous. It is slightly telegraphic, but every clause carries information.

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 single optional parameter, read-only analytics tool with no output schema, the description adequately covers what is computed and what the returned fields mean. Minor gaps remain around output units and the sibling distinction, but nothing an agent needs in order to call it 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 'window' parameter already carries its enum list and default, so the description restating '1h,6h,24h,48h,7d' adds nothing new. Baseline 3 applies when the schema does the heavy lifting.

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?

Names a specific analytic resource ('Mining-pool distribution') and the exact quantities computed: block share per pool, largest-pool share, and the Nakamoto coefficient, which it defines inline. It does not distinguish itself from the sibling pool_sources, so an agent must guess which of the two to pick for pool-related questions.

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 metric definitions imply the analytical use case, but there is no explicit when-to-use statement, no exclusions, and no pointer to pool_sources as the alternative for source/registry data. The guidance is inferred rather than stated.

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