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regdata_adverse_media

Screen a person or company for adverse media and negative news. Returns LLM-classified hits with severity, source, and false positives removed, for KYC/AML due diligence.

Instructions

Adverse Media Screener - KYC/AML Negative News Check. Screen a person or company for adverse media (negative news) for KYC/AML and due diligence. Returns categorized, LLM-classified hits - fraud, corruption, sanctions, money laundering and more - with the entity's role, a severity score and source provenance. False positives filtered out. Advanced fields beyond this schema are also accepted (regdata_describe lists them).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoOpenRouter model id used for classification. Default is a cheap, accurate model.deepseek/deepseek-chat
aliasesNoAlternative names / transliterations for the entity (only meaningful when screening a single entity).
countryNoISO country code or name to bias the search and aid disambiguation, e.g. "de", "Germany".
maxHitsNoMaximum number of adverse hits to return per entity. 1-50.
maxItemsNoOptional cap on billed dataset items returned.
categoriesNoIf set, only return hits in these risk categories. Leave empty to return all.
entityTypeNoWhether the entities are people or companies (improves disambiguation). Leave on "auto" if mixed.auto
entityNamesNoOne or more person or company names to screen, e.g. ["Wirecard AG", "Jan Marsalek"]. Each entity is billed and returned as its own result.
minSeverityNoOnly return hits at or above this severity.low
serperApiKeyNoOptional. Search is included; provide your own Serper key only to bill search to your own account.
openRouterApiKeyNoOptional. The LLM is included; provide your own OpenRouter key only to bill classification to your own account.
Behavior4/5

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

With no annotations, the description carries full burden. It mentions false positives are filtered out, returns classified hits with severity and provenance, and accepts advanced fields. It does not mention rate limits or authentication requirements beyond API keys.

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 description is a concise paragraph of 4 sentences, front-loaded with purpose. It could be slightly tighter but avoids fluff.

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?

Given 11 optional parameters and no output schema, the description covers the tool's purpose, output structure (categorized hits, severity, provenance), and links to regdata_describe for extended fields. It is sufficiently complete for a screening tool.

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 baseline is 3. The description adds no additional meaning beyond the schema's parameter descriptions, which are already detailed.

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 clearly states it is an 'Adverse Media Screener - KYC/AML Negative News Check' and explains it screens a person or company for adverse media, returning categorized hits with entity role, severity score, and source provenance. This distinguishes it from sibling tools which are registry lookups.

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 implies use for KYC/AML and due diligence but does not explicitly state when to use alternatives or when not to use this tool. The context of sibling names (registry tools) provides indirect differentiation.

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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