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data_feeds

Read-onlyIdempotent

Pre-scraped AI data feeds ($0.001 USDC)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
feedIdYesFeed report ID to query (e.g. trending-pairs)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
oracleNoAttestor identity
reportYesIntelligence report data
statusYesReport status

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / feedId / description
      Added value: +"Feed report ID to query (e.g. trending-pairs)"
    • changedOutput 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"
      +}
  2. First observed

TDQS

C2.9/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so safety is covered. The description's one added behavioral fact is the cost ($0.001 USDC per call), which is genuinely useful for an agent deciding whether to invoke it, but it says nothing about freshness, rate limits, or what a feed contains.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single terse phrase, zero filler, and the resource plus price are front-loaded. It is efficiently written, though the brevity borders on under-specification rather than pure concision.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return values need not be explained, and the tool is low-complexity with one fully-documented parameter. However, a paying tool with a paid-call side effect and many overlapping siblings should at least state what a 'feed' is and when to choose it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%: feedId is documented with an example ('trending-pairs'). The description adds no information about valid feed IDs, discovery of IDs, or defaults, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description is a noun phrase with no verb: 'Pre-scraped AI data feeds' largely restates the tool name, though the modifiers 'pre-scraped' and 'AI' plus the price hint at a distinct resource. An agent can guess it retrieves pre-scraped feeds, but the action (list? fetch by ID?) is left implicit.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No when-to-use guidance is given, and no alternative among the many siblings (public_data_feed, web_scraper, browser_scraper, arc_analytics) is named or excluded. The only selection aid is the embedded price.

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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