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catqualia-ledger-mcp

Official

what_would_refute

Retrieve pre-registered refutation thresholds for claims to test falsifiability. Enter a query to see what measurement would have disproven each claim before the outcome was known.

Instructions

Return the pre-registered refutation threshold for matching claims: the measurement that would have killed each claim, recorded before the outcome was known. 16,194 of 16,218 ledger records carry one. Use this to test whether a claim is falsifiable at all.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNomax records, default 5
queryNosubstring to match

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses partial data coverage ('16,194 of 16,218 ledger records carry one') and the pre-registration property, which is useful. However, it does not explicitly state read-only behavior, auth requirements, or return format, so it adds only moderate behavioral context.

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

Conciseness5/5

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

Three sentences, with the core definition front-loaded in the first sentence. The coverage statistic and usage guidance each earn their place; there is no redundant or filler content.

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?

The concept of a refutation threshold is well explained, and the usage instruction is clear. However, there is no output schema and the description does not describe the return value shape or behavior when no records match (e.g., empty array, null). For a simple query tool this is a moderate gap, not a severe one.

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

Parameters3/5

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

Schema description coverage is 100%, so the parameters are already fully documented by the schema. The description's 'matching claims' phrase aligns with the query parameter but adds no new semantic detail beyond what the schema provides. Baseline 3 is appropriate.

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?

The description states a specific verb ('Return') and a distinctive resource ('pre-registered refutation threshold for matching claims'). This resource is unique enough that an agent can distinguish this tool from siblings like get_verdict or query_claim without needing an explicit comparison.

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 description gives an explicit use case: 'Use this to test whether a claim is falsifiable at all.' This provides clear context for when to invoke the tool. It does not mention alternatives or exclusions, so it falls short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.