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

No annotations are provided, so the description carries the full disclosure burden. It transparently describes the data scope and metric shape, making it clear this is a read-only metrics snapshot. It doesn't mention data freshness, computation basis, or response formatting, which prevents a 5.

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?

The description is two tight sentences: the first front-loads the resource and metrics, the second gives concise when-to-use and when-not-to-use guidance. Every clause earns its place with no redundancy or filler.

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-parameter tool with no output schema and no annotations, the description adequately covers pool scope, metric names, use cases, and an exclusion. Minor details such as units or return structure are absent, but they are not necessary for an agent to select and invoke this tool correctly.

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 has zero parameters and the schema coverage is 100%, so there is no parameter burden for the description. The zero-parameter baseline applies here, and the description correctly focuses on the returned data rather than inputs.

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 clearly identifies the resource—all six Zcash value pools by name—and the exact metrics returned: balances, share of supply, and 1h/24h deltas. This differentiates it from generic chain or block tools and leaves no ambiguity about what the tool covers.

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?

It explicitly provides when-to-use contexts (privacy-pool capital allocation, shielded-supply trends, ZEC macro flows) and a direct do-not-use case with a named alternative, chain_status(zec). This gives an agent clear routing logic without needing to inspect siblings.

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