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

With no annotations, the description carries the full burden and does so thoroughly: it discloses the data source (totalSupply() hourly), counting basis (at par), precomputation cadence (every 5 minutes), staleness handling (computedAt/validUntil, withholds rows with dataNote), null behavior for immature readings, and an explicit disclaimer ('Says nothing about peg'). This goes beyond typical descriptions.

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 a single dense sentence but front-loads the core purpose and then lists the data returned. Every clause adds relevant information; however, the lack of paragraph breaks or bullet points makes it slightly harder to parse quickly. Minor structural weakness prevents a 5.

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?

Given the tool has no parameters, no output schema, and no annotations, the description is remarkably complete. It explains the data source, the exact list of returned fields, the refresh cadence, staleness semantics, null cases, and even a caveat about what it does not claim (peg). An agent has enough to call and interpret the 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 an empty schema, so by the rubric the baseline is 4. The description adds nothing parameter-specific (there is nothing to add), but it does not need to since there are no 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 states a specific verb ('read') and resource ('stablecoin float on Robinhood Chain') and enumerates the exact metrics returned (per-stable supply, share of float, changes, minted/burned totals, holders, deployed ratio, large mints/burns, gateway legs). This is precise and clearly distinguishes the tool from siblings like get_bridge_flow or chain_composition.

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 description clearly conveys the scope (stablecoin data on Robinhood Chain) and the specific outputs, so an agent can infer when to use it (e.g., when needing stablecoin supply or flow metrics). However, it does not explicitly name alternative tools or state when NOT to use it, which prevents a 5.

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