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BeliefState Get Author Track Record
x402
BeliefState Get Author Track Record is a paid API for AI agents from beliefstate.ai, paid per call via x402, $0.02/call, status unknown (last checked 2026-10-29).
Retrieves the historical track record of a specific analyst (author) on the BeliefState platform, including their past research theses and prediction outcomes.
Price / call$0.02
Success—
StatusUnknown
How this service works
The first AI-powered platform for top analyst research. Get theses from top analysts, dated evidence, and available outcomes for your AI.
Output
Returns a JSON object containing the analyst's track record data as of the specified date, including schema version and generation timestamp. The response includes historical thesis outcomes, prediction performance, and dated evidence tied to the specified analyst, optionally filtered by ticker, belief, entity, or source.
Example use cases
Vetting an analyst before acting on research
“Before I use this analyst's latest NVDA thesis, can you pull their BeliefState track record for person_id 'f47ac10b-58cc-4372-a567-0e02b2c3d479' and show me how their past predictions have held up, especially on semiconductor stocks?”
Comparing analyst performance on a specific ticker
“I want to see the historical accuracy of analyst person_id '550e8400-e29b-41d4-a716-446655440000' on TSLA calls — pull their track record from BeliefState filtered to the 'released' corpus and any research published from 2022-06-01T00:00:00Z onward.”
Auditing analyst credibility for an AI research workflow
“As of 2025-01-01T00:00:00Z, what does BeliefState show for the track record of analyst person_id '6ba7b810-9dad-11d1-80b4-00c04fd430c8'? I need to know if their theses historically resolved correctly before I feed their reports into my trading model.”
Technical details
Endpoint
POSThttps://beliefstate.ai/v1/research/get_author_track_record?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need to evaluate the historical credibility and prediction accuracy of a specific analyst before trusting or acting on their research. It is ideal for AI agents performing due diligence on analyst sources, building analyst scoring models, or filtering research by author quality. Prefer this over general search endpoints when you already have a person_id and want performance history rather than thesis content.
Side effects
- Invalid or unknown person_id UUID returns an error or empty result
- Malformed UUID format causes validation failure
- Date filters with no matching data return empty result sets
- Requesting a future as_of date may return no resolved outcomes
- Corpus type mismatch (only 'released' is supported) causes rejection
- Network or payment failure (x402 micropayment not completed) blocks the call
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| outputrequired | object |
Output
Schema · Response
{
"type": "json",
"example": {
"as_of": "2026-10-24T00:00:00.000Z",
"generated_at": "2026-10-24T00:00:00.000Z",
"schema_version": "1"
}
}Tags
x402
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