ledgerfc-mcp

get_track_record

Retrieves settled betting record, high-confidence subset, and closing line value insights for grounded sports analytics.

Instructions

Honest settled record + high-confidence subset + CLV.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_track_record"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Aug 24, 2026

TDQS

D1.8/5.0

Behavior1/5

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

With zero annotations, the description must cover behavioral disclosure, but it offers almost nothing. It hints at some concept of 'honest' data and a 'high-confidence subset' but does not explain what the tool does internally, whether it is read-only, what data it accesses, or what the response shape is. This is a critical gap.

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?

The description is very short, which is good for conciseness, but it sacrifices clarity and structure. It reads as a list of features rather than a sentence with a clear subject-verb-object. Key information is missing, so the brevity is not effective.

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?

The description is severely incomplete. There is no output schema, no annotations, and no parameters, so the description is the only source of information. It fails to explain what 'honest settled record' means, what 'high-confidence subset' entails, or what 'CLV' stands for, nor does it describe the response format. An agent would be guessing on how to interpret the result.

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

Parameters4/5

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

The tool has zero parameters, so the description is not required to explain param semantics. The baseline for 0 parameters is 4, and the description does not contradict or confuse. However, it also does little to clarify what inputs might be expected (none), so it remains at baseline.

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 fragment listing components ('Honest settled record + high-confidence subset + CLV') rather than a clear statement of action. It essentially restates the tool's name ('settled record' ≈ 'track record') and adds ambiguous terms without explaining their function. An agent cannot confidently determine what the tool returns or how to use it.

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?

The description provides no context on when to use this tool versus its many siblings (e.g., get_predictions, get_value_bets). It does not state use cases, prerequisites, or alternatives, leaving the agent to guess.

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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