I used the same url for two different postings.
Pre-scraped AI data feeds ($0.001 USDC)
| Name | Required | Description | Default |
|---|---|---|---|
| feedId | Yes | Feed report ID to query (e.g. trending-pairs) |
| Name | Required | Description | Default |
|---|---|---|---|
| oracle | No | Attestor identity | |
| report | Yes | Intelligence report data | |
| status | Yes | Report status |
Changes observed during successful MCP inspections.
Input schema / properties / feedId / descriptionAdded value: +"Feed report ID to query (e.g. trending-pairs)"Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "oracle": {
+ "description": "Attestor identity",
+ "type": "string"
+ },
+ "report": {
+ "description": "Intelligence report data",
+ "type": "object"
+ },
+ "status": {
+ "description": "Report status",
+ "type": "string"
+ }
+ },
+ "required": [
+ "status",
+ "report"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish read-only, idempotent, open-world behavior. The description adds useful operational context: the data is pre-scraped and costs $0.001 USDC. However, it does not disclose other behavioral traits such as response caching, rate limits, or what happens on payment failure.
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 extremely short, but it is under-specified rather than concisely informative. It lacks a sentence structure with a subject and verb, and it front-loads pricing over the core purpose.
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?
The tool is simple with one required parameter, an example feed ID, output schema, and safety annotations. The description mentions cost and data source type, which is useful. However, it still omits a clear action statement and any differentiation from similar sibling data-feed 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 100%, and the feedId parameter description includes a concrete example ('trending-pairs') and the verb 'to query'. The tool description itself adds no parameter meaning beyond the schema, so the baseline 3 applies.
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 is a noun phrase, 'Pre-scraped AI data feeds', with no verb stating what the tool does. It names the resource and adds pricing, but does not say 'query', 'retrieve', or 'fetch'. The parameter description ('Feed report ID to query') partially compensates, but the tool description itself remains tautological.
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 guidance is provided about when to use this tool versus alternatives like public_data_feed or x402_telemetry_feed. The description gives no selection criteria, exclusions, or context for choosing this over a sibling.
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.