discover_income_factory
Discover Income Factory metered intelligence tollbooths, prices and native x402 payment endpoints.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Discover Income Factory metered intelligence tollbooths, prices and native x402 payment endpoints.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility for disclosing behavior. It hints at 'metered' and 'payment endpoints,' which suggests potential costs or payment requirements, but it doesn't state whether the tool is read-only, has side effects, or requires authentication. The description is too vague to set agent expectations.
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 sentence and relatively short, but it is cryptic and not front-loaded with the most important information. It reads more like a tagline than a functional explanation. It could be restructured to lead with the action and outcome.
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 no output schema, no annotations, and zero parameters, the description is the only source of information. It fails to explain what the tool returns, what kind of data it provides, or how to interpret the results. For a tool that appears to involve metering and payments, this is a significant gap.
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 100% (vacuous). Per the rubric, a 0-parameter tool gets a baseline of 4 because the description doesn't need to explain parameters. The description adds some context about the tool's domain but doesn't need to compensate for schema gaps.
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 the verb 'Discover' and names a resource ('Income Factory metered intelligence tollbooths, prices and native x402 payment endpoints'), but it's unclear what action the agent performs. It doesn't specify whether this is a lookup, search, or retrieval tool. The phrasing is ambiguous and doesn't clearly distinguish from sibling tools, though it is not a tautology.
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?
There is no guidance on when to use this tool versus the sibling tools like google_maps_b2b_leads or tiktok_trends. It doesn't mention use cases, prerequisites, or exclusions. The agent is left to infer the intended scenario.
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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