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GroundedKit Marketing Stats Checker

Check a marketing stat

check_stat
Read-onlyIdempotent

Paste a marketing or influencer-marketing statistic (a sentence or a whole paragraph), or ask for a reference number (e.g. 'what share of US adults use TikTok'). Returns the best-matching checked claim with its verdict, confidence, primary source, what the source actually says, a safe rephrasing and the claim URL, plus its kind (stat_check or reference_fact), as_of date, last_checked date and stale flag (last checked more than 180 days ago), and close alternatives. Returns match: none when the stat is not in the database.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe statistic as you saw it, e.g. 'influencer marketing returns $5.78 per $1'

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description goes further by disclosing return behavior: verdict, confidence, primary source, kind, as_of/last_checked dates, a stale flag defined as >180 days, and the no-match case ('match: none'), which is genuinely useful context beyond the annotations.

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?

The text is a single dense sentence, but it is front-loaded with the accepted input modes before enumerating return fields, and every clause carries information. It is slightly packed but not padded.

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?

With no output schema present, the description carries the full burden of describing return values and does so thoroughly (match fields, verdict, confidence, source, rephrasing, URL, dates, stale flag, alternatives, and the empty-match case). Nothing critical for correct invocation is missing.

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?

Schema coverage is 100% and there is a single parameter, so the baseline is 3. The description adds real meaning by clarifying that 'text' may be a sentence, a whole paragraph, or phrased as a question requesting a reference number, which is broader than the schema's single example.

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 states a specific verb and resource ('check' a 'marketing or influencer-marketing statistic') and explains the two input modes (paste a stat vs. ask for a reference number). It is clear what the tool does, though it never names or contrasts against the sibling tools (search_claims, verify_text, get_claim).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied through the input examples ('paste a statistic', 'ask for a reference number'), which tells the agent what this tool accepts. However, there is no explicit when-to-use versus when-not, and no sibling alternative (e.g. verify_text or search_claims) is named as the preferred path under some condition.

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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