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brs_audit_track_record

Read-onlyIdempotent

The public proof: every call BRS has made and what Bitcoin did next.

Returns the keyless track record — each entry carries timestamp, side (bullish/bearish), price at call time, confidence, regime, zone, and resolved +4h/+24h outcomes where the paper-trading log has them (return %, worst drawdown, best upside). Outcomes are fixed once written and never re-scored, so this is auditable evidence, not marketing.

This is the "don't trust us — query us" surface: no API key and no payment are required. Use it to verify the system's real silence before trusting any signal.

Args: limit: Number of recent calls to return (1–500, default 100).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
tierNofree
as_ofYes
errorNo
statusYes
qualityNo
evidenceNo
disclaimerNoMarket-structure context; not an execution instruction.
request_idYes
schema_versionNo1.0
freshness_secondsNo
valid_for_secondsNo
methodology_versionNo2026.09

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior4/5

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

The description discloses that outcomes are fixed and never re-scored, which is important append-only/immutability behavior not fully captured by the readOnly/idempotent annotations. It also confirms no auth or payment is needed. No contradiction with the annotations is present.

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 description contains redundant marketing-style phrases like 'public proof', 'don't trust us — query us', and 'not marketing' that do not add technical value. It is still relatively short, but some sentences could be tightened to improve signal-to-noise.

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

Completeness4/5

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

Given the output schema is present, the description sufficiently covers the tool's purpose, the meaning of the limit parameter, and the key fields returned (timestamp, side, price, confidence, regime, zone, outcomes). It does not describe error cases or pagination, but these are not essential for a simple read-only list tool.

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

Parameters5/5

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

The only parameter, limit, is fully explained as 'Number of recent calls to return (1–500, default 100)', which directly adds meaning beyond the schema's min/max/default. This is exactly what an agent needs to correctly set the parameter.

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?

The description clearly states it returns a track record of past calls and their outcomes, which distinguishes it from the sibling tools focused on market state, rejection funnel, and system status. Some phrasing like 'public proof' and 'keyless track record' is stylistic but does not obscure the core purpose.

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?

It explicitly frames this as the verification surface ('don't trust us — query us') and notes that no API key or payment is required, giving clear when-to-use guidance. It does not explicitly contrast with siblings, but the purpose is distinct enough that an agent can infer when to choose this tool.

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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