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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and a closed-world scope, so the safety profile is covered. The description adds genuine context beyond that: the three-tier pricing readability model (live pricing, volume-only, unreadable due to key/testnet/no public API) and the coverage-share metric, which tells the agent what qualifying caveats to expect in the payload.

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?

It is compact and front-loaded, leading with the resource before the parenthetical list of unreadable reasons. The nested parenthetical '(key needed, testnet, no public API)' is slightly dense but each clause earns its place by explaining the coverage taxonomy.

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 bears the burden of explaining the return shape, and it does so by naming the fields and the coverage categories, including a derived coverage-share figure. It never states the response format (list vs. object) or pagination, but for a zero-argument inventory tool this is close to sufficient.

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 takes zero parameters, so the baseline is 4; there are no arguments whose meaning the description needs to disambiguate. The description appropriately spends its words on what the call returns rather than on input semantics that do not exist.

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 names the specific resource (Canton trading venues) and enumerates the fields returned (type, 24h volume, pricing capability), which is far more than the bare name 'venues' conveys. It is clearly distinct from siblings like list_tokens or pools, though it never names a sibling explicitly to sharpen the boundary.

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 implies a discovery/coverage use case, and the phrase 'every Canton trading venue we know of' suggests it is the broad inventory view. But it never states when an agent should call this instead of market_overview, pools, or list_tokens, and no exclusions or prerequisites are given.

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