get_registry_stats_api_registry_stats_get
Get Registry Stats
Get registry-wide statistics.
Responses:
200: Successful Response (Success Response) Content-Type: application/json
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Get Registry Stats
Get registry-wide statistics.
200: Successful Response (Success Response) Content-Type: application/json
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden of behavioral disclosure. It only states the tool returns registry-wide statistics and lists a 200 success response, without revealing authentication needs, rate limits, what data is actually returned, or any side effects. This is insufficient for transparency.
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 very concise and front-loaded with its purpose, consisting of two core sentences. The 'Responses' section is somewhat redundant ('Successful Response (Success Response)') but provides the content type, adding minor value. Overall, it is efficient with minimal fluff.
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 simple zero-parameter endpoint, this description is minimally viable. However, it lacks specifics about what statistics are included, how they are aggregated, or any error conditions beyond 200. Given no output schema or annotations, the description could have provided more context about the expected response.
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 an empty schema, so there is nothing to document. The description adds no parameter information, but none is required; this meets the baseline for a parameterless tool.
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 clearly states the tool's action ('Get Registry Stats') and resource ('registry-wide statistics'), making the purpose specific. It implicitly distinguishes itself from sibling endpoints like list_agents or get_mint_info by focusing on aggregate registry stats, though it does not explicitly compare itself to alternatives.
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 description provides no guidance on when to use this tool versus the many sibling endpoints, nor does it mention exclusions or alternative tools. It merely states what it does, leaving the agent without context for tool selection.
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.
Most tools have clearly distinct purposes, with descriptions that differentiate related operations like discovery vs. scanning or mint vs. melt quotes. A few pairs (e.g., list_agents vs. a2a_public_discovery, get_agent vs. discover_single_agent) could cause confusion, but the endpoint paths and descriptions mitigate this.
All tool names follow a consistent pattern: a descriptive operation prefix followed by the full API path and HTTP method (e.g., list_agents_api_agents_get, create_melt_quote_api_payments_ecash_melt_quote_post). No mixed casing or inconsistent verb styles.
With 36 tools, the server is overloaded. Even though it covers multiple domains (directory, trust, discovery, payments), the count exceeds the 25+ threshold and likely should be split into focused sub-servers. The tool set feels sprawling rather than well-scoped.
The core workflows for agent registration, search, trust, A2A discovery, scanning, and ecash payments are well-covered. Minor gaps exist, such as no update or delete agent operations and no way to modify agent details post-registration, but these are not critical dead-ends for the platform's purpose.