List AI markets
list_marketsList every market (kind of AI API) that has prices, with its id and pricing unit. Start here to find the market id.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
list_marketsList every market (kind of AI API) that has prices, with its id and pricing unit. Start here to find the market id.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the safety profile is fully covered. The description contributes the substantive filter ('markets that have prices') and the returned fields, but adds no pagination, ordering, or auth context.
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 tight sentences with no waste; the scope (markets with prices) and the payoff (finding the market id) are both front-loaded.
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 parameters and no output schema, the description carries the burden of describing what comes back, and it does: an id and a pricing unit per market. Nothing an agent needs to call this correctly is missing.
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, which sets the baseline at 4. There is nothing for the description to clarify, and it correctly signals that the call needs no input.
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 and resource ('List every market'), defines the domain term ('kind of AI API'), and scopes it ('that has prices'), plus names the returned fields. It implies an entry-point role but never names a sibling like describe_market or search_offerings, so differentiation is left to inference.
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?
'Start here to find the market id' gives clear context for why an agent would call this and what it enables downstream. There are no exclusions or explicit alternatives, but for a no-arg enumeration tool the guidance is sufficient.
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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