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Checks $TICKER numeric claims in financial writing against SEC EDGAR XBRL data from the latest 10-K.

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Status
Healthy
Last Tested
Transport
Streamable HTTP · MCP 2025-11-25
URL

TDQS

A3.9/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of confusion between tools. The single tool has a clearly defined purpose: checking financial numbers against SEC filings.

Naming Consistency3/5

The name 'check_financial_numbers' is descriptive and follows a verb_noun pattern, but with only one tool there is no broader pattern to evaluate. It is readable and conventional, though consistency across a set cannot be demonstrated.

Tool Count2/5

A single tool is quite thin for a server that appears to cover a meaningful domain (financial fact-checking). While the tool is substantial, the server would likely benefit from additional tools such as retrieving company context or checking other filing types.

Completeness2/5

The tool covers one specific verification workflow, but the domain of financial number checking has obvious gaps: no way to fetch raw company facts, compare multiple filings, or handle non-10-K documents. Agents are limited to a single, narrow operation.

Available Tools

1 tool
check_financial_numbersA
Read-only
Inspect

Check $CASHTAG-style ticker mentions (e.g. $AAPL) in a piece of financial writing against SEC EDGAR's own XBRL company-facts data for that company's most recent 10-K -- EPS, book value per share, revenue, market cap, total assets, total liabilities. Flags numeric claims that don't match the filed figures.

ParametersJSON Schema
NameRequiredDescriptionDefault
textYesThe draft text to check, with $TICKER cashtags for each company mentioned.

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds useful behavioral context: it compares against SEC EDGAR's XBRL data, implying an external network dependency, and states which specific metrics are validated. This goes beyond the annotations without contradicting them.

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?

The description is a single, dense sentence that front-loads the action and target, then lists the relevant metrics and the tool's outcome. No filler, redundant phrasing, or unnecessary background. Every clause adds useful information.

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

Completeness5/5

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

Given a single simple parameter, no output schema, and annotations covering read-only behavior, the description is fully sufficient for an agent to invoke the tool correctly. It explains the input format, the data source, the comparison set, and what the tool does with mismatches.

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% for the single 'text' parameter, so the schema already fully documents it. The description re-emphasizes the $CASHTAG convention but adds no new format details or additional parameter semantics 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 names a specific action ('Check'), a specific resource (financial writing with $TICKER mentions), and a specific data source (SEC EDGAR XBRL company-facts for the most recent 10-K). It also lists the exact metrics involved and the outcome (flagging numeric claims that don't match). No ambiguity about what this tool does.

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?

There are no sibling tools, so alternative routing is not applicable. However, the description clearly implies when to use it: when someone has a draft containing $CASHTAG tickers and wants to verify financial figures against official filings. It does not explicitly state exclusions, but the use case is evident and concrete.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool update
    • First observedcheck_financial_numbers

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