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ExchangeRebel — pay-per-call APIs for AI agents (x402 on Solana)

fact_bank_status

Fact bank STATUS lookup, $0.01 per call (x402), price RULED. Latest-per-status_field current state for one entity, served verbatim with per-fact provenance. Call fact_bank_status_preflight first to check coverage for free. — USDC on Solana via x402 (over MCP: call without payment to get the PaymentRequired challenge, then retry with the payment at _meta["x402/payment"]). HTTP equivalent: POST https://exchangerebel.com/toll/facts/status.

Input Schema

NameRequiredDescriptionDefault
nameNoName-resolution form (alternative to entity_id).
teamNo
limitNo
cursorNo
leagueNo
streamYes
positionNo
entity_idNoCanonical entity id, verbatim as stored.
series_idNo
status_fieldNoOptional; omit for all current fields.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.5/5.0
Behavior4/5

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

Adds substantial context the annotations do not: $0.01 per call, USDC on Solana via x402, the exact MCP retry mechanics ('call without payment to get the PaymentRequired challenge, then retry with the payment at _meta["x402/payment"]'), and an HTTP equivalent. This is exactly the billing/auth disclosure the sparse annotations leave uncovered; it stops at 4 because return shape and pagination behavior (limit/cursor) are never described.

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

Conciseness3/5

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

The core purpose appears early, but the opening clause 'price RULED' is opaque filler and the payment/HTTP mechanics sprawl into a long final sentence. Everything is relevant, yet the ordering leads with cost rather than with what the tool returns.

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?

For a 10-parameter, paid, no-output-schema tool the description covers the billing path and provenance well, but an agent still cannot infer which stream to pass, how the optional filters behave, or how results are paginated. Payment is complete; parameter selection is not.

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 coverage is only 30% across 10 parameters, and the description compensates for very little: it clarifies that results are per entity and per status_field, but never explains the required `stream` enum values, how `league`/`team`/`position`/`series_id` combine per stream, or what `limit`/`cursor` do. The majority of parameters remain undocumented in both schema and prose.

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

Purpose4/5

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

States a specific verb and resource: 'Fact bank STATUS lookup' returning 'Latest-per-status_field current state for one entity, served verbatim with per-fact provenance.' That scope is precise enough to separate it from a trend/history tool, but no sibling (fact_bank_tendency, fact_bank_catalog) is named to confirm the distinction, so it stops short of a 5.

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

Usage Guidelines4/5

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

Gives actionable routing advice: 'Call fact_bank_status_preflight first to check coverage for free,' which directly steers sequencing against a real sibling. It does not state when to prefer fact_bank_tendency or fact_bank_catalog instead, so the when-not side is missing.

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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