Search external AI/x402 catalog
search_external_catalogSearch indexed third-party services/opportunities with source attribution.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | ||
| limit | No | ||
| item_type | No |
search_external_catalogSearch indexed third-party services/opportunities with source attribution.
| Name | Required | Description | Default |
|---|---|---|---|
| q | No | ||
| limit | No | ||
| item_type | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful context about indexed third-party services and source attribution, but does not disclose behavior like pagination, ordering, result structure, or how item_type affects results. With annotations carrying the safety burden, this is adequate but not rich.
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 a single concise sentence that front-loads the action and object. There is no fluff, and every phrase adds some semantic value. However, it is so short that it misses opportunities to clarify parameters and usage context.
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 three undocumented parameters, no output schema, no enums, and many similar sibling search tools, the description is not complete enough for an agent to invoke the tool correctly without guessing. It omits parameter semantics, result format, and any differentiation from closely related search tools.
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?
Schema description coverage is 0% and the description provides no meaning for the three parameters: q, limit, and item_type. An agent cannot tell what values are valid, what item_type should contain, how limit behaves, or whether q is a full-text query. The description must compensate for the bare schema but does not.
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 states a specific verb ('Search') and resource ('indexed third-party services/opportunities'), and adds a distinguishing detail with 'source attribution' and 'external.' It is clear about what the tool targets, though it does not explicitly differentiate itself from the many sibling search 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?
No explicit guidance on when to use this tool versus alternatives such as search_external_earn, search_global_market, or search_opportunities. The word 'external' implies a scope, but the description does not state exclusions, preferred use cases, or conditions for selecting this 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.
There are multiple clusters of near-duplicate tools: earn, earn_now, earn_loop, find_money_opportunities, search_global_earn, and several rank_real_profit_opportunities variants. Even with descriptions, an agent would struggle to choose reliably among dozens of overlapping search, earn, and ranking entry points.
Most tools follow a snake_case verb_noun pattern, which provides some consistency. However, the set mixes prefixes like agentlot_, standalone verbs like earn and me, and many semantically interchangeable verbs such as find, search, discover, rank, route, and list applied to similar objects.
With 124 tools, this is an extreme mismatch for a coherent server surface. Even for a broad marketplace, this many entry points creates severe navigation overhead and includes multiple generations of similar tools instead of a disciplined, minimal API.
The tool set broadly covers marketplace lifecycles: listings, requests, orders, delivery, disputes, payouts, projects, and assets. However, there are notable gaps such as updating/unpublishing listings, canceling/refunding orders, and other core lifecycle management operations that would be expected in a complete marketplace surface.