get_discovery_statsReturns aggregate statistics for the PayAI Bazaar catalog and its settlement activity. Use it for a compact view of catalog size and payment volume rather than individual resources.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description conveys a read-only aggregation behavior and names the content areas (catalog size, payment volume), but with no annotations and no output schema it leaves the response structure and the precise meaning of 'settlement activity' unspecified. It is clear enough for basic selection but does not fully disclose behavioral details.
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, both informative: the first states what the tool returns, the second states when to use it and why. No filler, no redundancy, and the core purpose is 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?
For a parameterless tool, the description gives enough context for an agent to decide when to invoke it: aggregate stats over individual resources. It does not describe the output structure, but the summary nature is clearly conveyed. A small gap remains around exact returned metrics.
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 and schema coverage is trivially complete, so there is no parameter detail the description needs to add. The baseline of 4 applies, and the description adds no irrelevant parameter information.
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 ('Returns') and names the exact resource ('PayAI Bazaar catalog') and scope ('aggregate statistics... settlement activity'). It explicitly contrasts itself with individual-resource operations, distinguishing it from siblings like list_discovery_resources without ambiguity.
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?
It gives an explicit use case ('Use it for a compact view...') and an explicit when-not-to-use ('rather than individual resources'). This directly steers an agent toward this tool for summary-level insights and away from resource-level alternatives.
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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Each tool has a clear, non-overlapping purpose: aggregate stats, capability lookup, resource listing, payment verification, and fund settlement. The two catalog tools are distinguished by aggregate vs. paginated listing, and verify vs. settle is cleanly separated by whether funds move.
All names use lowercase snake_case and a verb-first structure, but read operations mix get_ and list_ (get_discovery_stats, get_supported, list_discovery_resources) while the two payment actions use settle_ and verify_. This is a minor inconsistency, not a confusing one.
Five tools is well-scoped for a facilitator that handles discovery, capability checks, and payment settlement. Each tool earns its place and the set is small enough for an agent to navigate easily.
The surface covers the core workflow: discover resources, check supported networks, verify payloads, and settle payments. There is no dedicated payment status/history tool, but settle_payment supports idempotent polling, so the gap is minor and workable.