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

The annotations confirm this is a safe, read-only operation. The description adds critical contextual behavior by listing the specific, complex technologies involved in the preservation (e.g., Arweave, IPFS pinning), giving the agent a deeper understanding of the underlying 'data state' beyond the safety hints.

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, perfectly structured sentence that addresses the core function and the necessary verification step without any filler. It is highly efficient.

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 its informational, static nature and zero parameters, the definition is entirely complete. The description covers the 'what' (preservation methods) and the 'how' (verification), and the annotations cover the safety profile.

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?

With zero parameters and 100% schema coverage, the description cannot add specific parameter semantics. This score represents the baseline expectation for tools with no complex 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 is highly specific, outlining not just that it provides information, but exactly *what* information it provides: the various archival mechanisms (Ethereum, Arweave, IPFS) and the method for verification. This distinguishes it from simple data retrieval siblings like get_piece.

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?

Since this is a 0-parameter, information-providing tool, its usage is defined by necessity—when the agent needs to know the preservation policy, which is outside the scope of data retrieval tools like get_collection. It clearly targets conceptual queries rather than data lookup.

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