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Scamchecker.nl

Controleer een verdacht bericht

check_message
Read-only

Check a suspicious email, SMS, WhatsApp message, link or screenshot for scam signals. Controleer een verdachte mail, sms, WhatsApp-bericht, link of screenshot op signalen van oplichting. Documentation: https://scamchecker.nl/hoe-het-werkt

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNo
textNo
image_mimeNo
image_base64No

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
spansYes
channelYes
signalsYes
summaryYes
verdictYes
next_stepsYes
checked_textYes
country_hintYes
impersonatesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, and destructiveHint=false, so safety behavior is covered upstream. The description adds only that it looks for 'signalen van oplichting' and points to external documentation; it says nothing about what the analysis returns or latency, and with an output schema present the return-format gap is acceptable.

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 core purpose is front-loaded in a single clear sentence. However, the description is duplicated verbatim in Dutch and then appends a bare documentation URL, roughly tripling length without adding distinct information for the agent.

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?

With an output schema handling return values and annotations covering the safety profile, the description only needs to convey the input modes and purpose, which it does reasonably. The remaining shortfall is the unexplained anyOf exclusivity and image payload mechanics.

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 0%, so the description must carry the burden. It partially does: the enumerated input types (text message, link, screenshot) map onto the three anyOf branches (text / url / image_base64+image_mime). However, it never explains the exclusivity of those branches, the base64 encoding requirement, the mime enum, or the length limits, leaving real gaps.

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?

States a specific verb (check) and resource (suspicious email, SMS, WhatsApp message, link, or screenshot) and names the exact artifact being analyzed (scam signals). An agent immediately knows what the tool does and which input kinds it accepts, even without siblings to differentiate from.

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?

The description implies when to use it (when a message looks suspicious) but never states prerequisites, exclusions, or what to do instead. There are no sibling tools to route against, so the omission is less costly, but no explicit usage guidance is given.

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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