get_pricing_infoInspect current direct x402 per-call prices, authenticated connector starter-credit costs, supported USDC settlement networks, and the account-plan contact path. This is free read-only metadata; it does not initiate payment.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds valuable context beyond those annotations: it explicitly states the operation is free and 'does not initiate payment,' which is especially meaningful for a payment-adjacent tool. No contradictions with annotations.
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 sentences with no filler: the first sentence front-loads the exact data topics, and the second adds a crucial safety clarification. Every part 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?
The tool is simple (zero parameters), annotations are rich, and an output schema exists. The description covers the main behavioral caveat and lists the specific metadata categories an agent can expect, so nothing essential 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 and the schema coverage is fully represented by an empty properties object. The baseline of 4 applies because there are no parameters requiring explanation, and the description appropriately focuses on the output content rather than inputs.
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 a clear verb ('Inspect') and a specific resource: current direct x402 per-call prices, starter-credit costs, USDC settlement networks, and the account-plan contact path. This fully distinguishes the tool from its sibling data-access tools.
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 use case is clearly implied and well-scoped: use this tool when you need current pricing-related metadata such as per-call costs, connector credits, or settlement networks. It does not name alternative tools or exclusions, but the context is clear enough for an agent to select it correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a distinct primary purpose, but search and search_pairs overlap in discovery, and get_market_data_endpoint vs get_workflow_endpoint both build endpoints. Descriptions clearly differentiate them, so confusion is unlikely.
All tool names follow a consistent verb_noun pattern with snake_case (get_, list_, search_, fetch). The naming is predictable and uniform across the set.
With 8 tools covering search, catalog, pricing, and endpoint building, the count is well-scoped for a market intelligence discovery server. No redundancy or bloat.
The tools cover documentation search, instrument discovery, product/pricing info, and endpoint construction. The only minor gap is not executing actual paid data fetches, but that is intentionally left to the generated HTTP endpoints.