pricing_infoFree — list every paid tool in the 'china-macro' bundle with its price, payTo address and network. Call this first if you don't have a wallet ready yet.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds valuable context beyond that: the tool is free, it lists every paid tool, and it includes payTo address and network details, which are essential for payment setup. This helps the agent understand the tool's role in the transaction process without contradicting the 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?
The description is two short sentences, front-loaded with 'Free' and the action 'list.' Every word adds value: pricing, bundle scope, specific data fields, and a usage directive. No redundant or filler content.
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 zero-parameter, read-only listing tool with no output schema, the description is fully sufficient. It explains what information is available and when to call it. There are no missing critical details that would impair the agent's ability to use 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?
The tool has zero parameters, so the schema is trivially complete (100% coverage). Per the rubric, 0 params warrants a baseline of 4. The description adds no parameter information because none exist, but it compensates by explaining the tool's output content, which is the relevant semantic context.
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 uses a specific verb ('list') and identifies the resource ('paid tools in the china-macro bundle') plus the exact contents (price, payTo address, network). It clearly distinguishes this pricing tool from the sibling monitoring tools. The phrase 'Call this first' adds a clear use case, making the purpose unambiguous.
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 states when to use: 'Call this first if you don't have a wallet ready yet.' This provides direct usage guidance and implies it should be used before the paid sibling tools. It also notes the tool is 'Free,' setting expectations. No alternatives are named, but the 'call first' directive is strong and sufficient for this simple tool.
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 monitor targets a distinct data domain: 1688 suppliers, OECD FDI, GLEIF LEI entities, and World Bank macro revisions. The pricing_info tool is clearly separate as a billing helper. No two tools overlap in purpose.
The four data monitors follow a consistent 'china-<domain>-monitor' pattern, making the tool's purpose predictable. pricing_info deviates but serves a distinct meta-function, so the minor inconsistency is acceptable.
With 5 tools, the bundle is well-scoped for a China macro and supply signals monitor server. Each tool covers a different aspect, and none are redundant or excessive.
The surface covers macro data, FDI flows, entity changes, and supplier supply-side metrics. Missing potentially useful monitors (e.g., trade or inflation) but core workflows are well covered with no dead ends.