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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, covering the safety profile. The description adds the useful constraint that the target is always Canton, but says nothing about output format or lookup behavior. With annotations doing the heavy lifting, a 3 is appropriate.

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?

Three sentences, front-loaded with the core purpose, then scope, then the routing alternative. No filler; every sentence earns its place.

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?

No output schema exists, so the description carries some burden for return expectations, which it does not describe. However, for a simple read-only concept-mapping lookup with a fully documented single parameter and complete routing guidance, an agent has enough to invoke it 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?

Schema description coverage is 100% for the single 'concept' parameter, so the schema already carries the semantics. The description's example list duplicates the schema's own examples rather than adding new meaning, so baseline 3 applies.

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?

States a specific verb (Map) and resource (EVM concept → Canton equivalent), gives concrete examples, and names the direction constraint ('target is always Canton'). It clearly distinguishes itself from the adjacent learning-path sibling.

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?

Explicitly scopes usage to 'single concept-to-concept translations' and routes the alternative case to get_started_guide for 'a full EVM-to-Canton learning path'. This is a textbook when-to-use / when-to-use-something-else split.

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