list_tokensEvery token on Canton DEXes with price, 24h/7d change, liquidity and volume. sort_by: liquidity, volume, change_24h, change_7d or premium.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many tokens to return, 1 to 100 | |
| sort_by | No | Order of the list, largest first: liquidity (USD), volume (24h USD), change_24h, change_7d, or premium (largest gap to the outside price, either sign) | liquidity |
Changes observed during successful MCP inspections.
Input schema / properties / limit / descriptionAdded value: +"How many tokens to return, 1 to 100"Input schema / properties / sort_by / descriptionAdded value: +"Order of the list, largest first: liquidity (USD), volume (24h USD), change_24h, change_7d, or premium (largest gap to the outside price, either sign)"Input schema / properties / sort_by / enumAdded value: +[
+ "liquidity",
+ "volume",
+ "change_24h",
+ "change_7d",
+ "premium"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds real value by enumerating what each row contains (price, 24h/7d change, liquidity, volume), which matters because there is no output schema. It does not mention default page size or how many results come back by default.
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?
Two short sentences, front-loaded with the resource and payload. The second sentence duplicates the enum already present in the schema, which is the only wasted space.
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?
For a two-parameter read-only listing with no output schema, the description covers the resource, the returned fields and the sort dimension. Only minor gaps remain: default limit behavior and whether results are paginated.
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 100% with both parameters documented and the enum fully spelled out, so the schema carries the load. The description's restatement of the sort_by values is largely redundant, though 'premium' is at least framed as a ranking concept rather than a raw field.
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 resource and scope: every token on Canton DEXes, with the fields returned (price, 24h/7d change, liquidity, volume). It is clearly a bulk listing rather than the single-token sibling 'token', though it never names that sibling explicitly.
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?
Usage is only implied by the scope phrase 'Every token on Canton DEXes' – an agent can infer this is the enumeration call versus 'token' for detail, but the description never states when to prefer one over the other or any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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