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social_source_evidence

Attributable public social-source observations with identity limitations; 0.006 USDC.

Input Schema

NameRequiredDescriptionDefault
queryNo
subjectNo
source_urlsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "query": "announcement",
      +    "source_urls": [
      +      "https://example.com"
      +    ]
      +  }
      +]
  2. First observed

TDQS

D1.7/5.0
Behavior2/5

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

With no annotations, the description carries the full behavioral burden. It does disclose two useful facts — the results carry an "identity limitations" caveat and the call costs 0.006 USDC — but says nothing about payment/auth mechanics, whether the operation is read-only, rate limits, or what happens on failure.

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

Conciseness2/5

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

It is a single sentence fragment, but brevity here reflects under-specification rather than tight editing — the price and caveat are packed in while the actual behavior is absent. There is no structure to front-load because there is almost no content.

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

Completeness1/5

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

A paid, 3-parameter tool with a required array, a nested object, no output schema, no annotations, and 0% parameter documentation leaves the agent unable to invoke it correctly. The 0.006 USDC cost and vague identity caveat are nowhere near sufficient.

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

Parameters2/5

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

Schema description coverage is 0% across three parameters, including a nested, unstructured "subject" object, and the description supplies no parameter meaning at all. An agent cannot infer what "subject" should contain or how "query" interacts with "source_urls" (1–5 URLs, required).

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

Purpose2/5

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

The description is a noun phrase ("attributable public social-source observations") rather than a verb+resource statement, so the agent cannot tell what action it performs. It also does not differentiate from siblings such as agent_reputation_evidence, company_enrichment_evidence, or entity_enrichment_evidence, which read almost identically.

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

Usage Guidelines1/5

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

There is no when-to-use guidance, no prerequisites, and no mention of any alternative tool such as try_service or preflight despite a large sibling set. The only contextual signal is a price, which does not help selection.

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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