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

No annotations provided, so description carries full burden. It discloses return values, default behavior (latest STH), and what is proven vs. not. This is transparent for a proof-of-inclusion 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 concise and front-loaded with the main purpose. Two paragraphs efficiently convey functionality, return values, limitations, and offline usage.

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 no output schema and moderate complexity, the description covers return values, default behavior, proof semantics, and references ADR. Lacks error conditions but is fairly complete for the tool's purpose.

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 0%, but description explains purpose of parameters: receipt_id unifies identifiers, tree_size defaults, leaf_index as alternative. Adds meaning beyond the schema, though lacks detailed parameter descriptions.

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 states the tool proves a specific receipt is included in the tree, specifying identifiers and what it proves vs. does not prove. It distinguishes from siblings like receipt_log_consistency_proof and receipt_lookup.

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 implicitly distinguishes usage by focusing on inclusion proof, but does not explicitly state when to use this vs. alternatives like consistency proof. However, it provides a practical offline verification step.

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