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

fact_bank_tendency_preflight

Read-onlyIdempotent

FREE preflight for fact_bank_tendency. Counts only: eligibility, history depth, distinct-value count, freshness, servable/reason_class, and the $0.02 RULED toll quote. No fact values are returned. — no payment required: call directly without payment (no x402 challenge; this tool is free). HTTP equivalent: POST https://exchangerebel.com/toll/facts/tendency/preflight.

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_fieldYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior4/5

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

Annotations cover the safety profile (readOnly, idempotent, non-destructive), and the description adds genuinely new behavior: no x402 payment challenge, no fact values in the response, and the exact set of count fields returned. It does not describe failure modes (what happens when an entity is ineligible or the stream has insufficient history) or error shapes.

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?

Front-loads the key fact (free preflight, counts only) and the sentence order is logical: purpose, response shape, payment note, HTTP equivalent. The free-ness is restated three times ('FREE', 'no payment required', 'this tool is free'), which is mild waste but not disruptive.

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?

With no output schema, the description usefully compensates by enumerating the returned count fields, and it removes payment ambiguity. But for a 10-parameter tool with 20% schema coverage, the input side is badly under-explained — an agent cannot tell what 'status_field' should contain or when 'stream' vs 'series_id' applies.

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 only 20% across 10 parameters, yet the description says nothing about them — the enumerated items (history depth, freshness, servable) are output fields, not inputs. Required parameters 'stream' and 'status_field' are left entirely uninterpreted, and the name/entity_id alternative forms go unmentioned.

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

Purpose5/5

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

States a specific verb and resource ('preflight for fact_bank_tendency') and enumerates exactly what is computed: eligibility, history depth, distinct-value count, freshness, servable/reason_class, and the toll quote. It also distinguishes itself from the paid sibling by declaring 'No fact values are returned,' so an agent can tell the two apart without opening either schema.

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?

The word 'preflight' plus the explicit 'no payment required: call directly without payment (no x402 challenge; this tool is free)' tells the agent this is the cheap check to run before spending $0.02 on fact_bank_tendency. It falls short of an explicit 'use this before X, skip it when Y' instruction, leaving the sequencing to inference.

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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