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

Beyond the read-only, idempotent, and closed-world annotations, the description discloses the exact return structure, attribution requirements, source terms, data contract, disclaimer status, and no-argument behavior. This is unusually rich behavioral context for a no-parameter retrieval tool.

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 front-loaded with purpose, then discusses output structure because no output schema exists. It is dense and mostly earns its length, but the very long field enumeration and the unhelpful 'Example: {}.' slightly reduce conciseness.

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 and no parameters, the description fully carries the burden by defining the return shape, nested exposure fields, attribution, data contract, and bulk-data alternative. An agent has enough information to call the tool and interpret the response.

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, so the baseline is 4. The description reinforces this by stating 'Takes no arguments,' which prevents the agent from expecting filters or input options.

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 resource and scope: Bitcoin held on the balance sheets of tracked public companies, in aggregate and by largest holder. This clearly differentiates the data domain from siblings such as sovereign reserves or ETF flows, but it does not explicitly name or contrast the sibling tools.

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 gives a clear usage context and an explicit exclusion: for bulk, history, backfills, and scheduled pulls, use the CSVs and datapackage.json. However, it does not explicitly say when to choose this tool over related sibling tools like get_sovereign_reserves or get_etf_flows.

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