What does the Screen Adverse Media skill do?

It screens a person or organization for adverse media coverage, PEP (Politically Exposed Person) status, and sanctions exposure using the Stipple API. Every hit is corroborated across sources before inclusion, and results are framed as "review" rather than guilt, with "nothing found" never presented as a clean record.

When should I use this skill?

Use it for AML/CTF onboarding (mandatory under Tranche 2 reforms for more Australian businesses), vendor or supplier due diligence before signing, investor or LP vetting, or ongoing counterparty monitoring where screens are re-run periodically.

What does the output include?

The output provides an overall rating (such as "review" or "clear"), a hits list with adverse media articles including date, title, source, URL and summary, a PEP list, and a sanctions list—all with fixed framing that emphasizes human review is required.

Can I submit documents directly to this skill?

Yes, you can submit documents such as an ID or company extract over REST using the Stipple API endpoint, or screen a person's or organization's name via an MCP tool call.

How much does it cost to run a screen?

Each screen costs 3 credits against a free weekly allowance, with a free API key available for metering beyond that allowance.

Skill

Screen People and Organisations for Adverse Media & Sanctions

Name: Screen People and Organisations for Adverse Media & Sanctions
Availability: OnlineOnly
Author: Sketchjar

Screen people or organizations for corroborated adverse media, PEP signals, and sanctions exposure with human-review framing.

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Works with stipple

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Spark score

out of 100

Updated last month

Source checked Sep 27, 2026

Version 18.6.0

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Why it matters

Conduct AML/CTF-compliant adverse media, PEP, and sanctions screening for individuals and organisations during onboarding, vendor due diligence, or ongoing counterparty monitoring, returning corroboration-gated results that flag review needs without declaring guilt.

Outcomes

What it gets done

Search adverse media coverage across corroborated sources for a named person or organisation

Check for Politically Exposed Person (PEP) status and sanctions list exposure

Extract and summarise adverse media hits with dates, sources, and URLs for human review

Generate screening reports with compliant framing that distinguishes review flags from determinations

Install

Add it to your toolbox

Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/ag-screen-adverse-media | bash

After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.

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Overview

Screens a person or organization for adverse media, PEP status, and sanctions exposure through Stipple. Results are framed as review signals with bounded coverage, rather than findings of guilt or a clean record. Use for onboarding, vendor due diligence, investor vetting, or recurring counterparty monitoring. Consequential matches require source corroboration and qualified human review.

What it does

Screen Adverse Media uses the Stipple API to look for adverse media coverage, politically exposed person status, and sanctions exposure associated with a person or organization. Hits are corroboration-gated before inclusion. The result supports review rather than a declaration that someone is guilty, and an empty result does not establish a clean record.

Screening combines an overall rating with separate collections of media hits, PEP signals, and sanctions signals. Media entries include dates, titles, sources, URLs, and summaries. These details let a reviewer inspect the underlying coverage instead of treating an aggregate rating as a complete explanation.

When to use - and when NOT to

Use it during AML/CTF onboarding, supplier or vendor due diligence, investor or limited-partner vetting, and ongoing counterparty monitoring. Periodic reruns can compare warrant IDs to support monitoring over time. Name-based screening is suitable when a name is available; document-based screening extracts the target from an uploaded identity document or company extract.

Do not use the result as a legal AML/CTF determination or as sufficient grounds to publish allegations as facts. Coverage is limited by sources and date ranges. Matches may be incomplete, stale, misattributed, or false, including PEP and sanctions signals. Consequential decisions require corroboration with original sources and authoritative registers.

Inputs and outputs

Provide the person's or organization's name, or a PDF or image containing their identifying details. The name route uses an MCP client; REST intake is document-based. The screening response exposes rating, hits, pep, and sanctions collections.

Reports should state that identified articles warrant review. A PEP signal should be framed as a reason enhanced due diligence may apply. When nothing is found, explicitly state that no corroborated adverse media was found within bounded coverage and that this is not a clean record.

The service processes personal data and potentially damaging allegations through a hosted third party. Before transmission, confirm a lawful purpose and any required approval, minimize identifiers, and verify retention, residency, access, and deletion terms. A qualified human reviewer must resolve identity ambiguity, record reasoning, and provide a correction or appeal path before restricting a person or organization.

Integrations

Stipple supports name screening through MCP and document submissions through REST. The document-based example is:

curl -X POST https://www.stipple.sh/v1/adverse-media \
  -F "file=@company-extract.pdf" \
  -H "Authorization: Bearer $STIPPLE_API_KEY"

A free anonymous tier and weekly allowance apply; each screen costs three credits. A free key supports metering beyond the anonymous allowance. For AML flows, the workflow pairs with check-identity-pack for identity checks and verify-document for document genuineness. The skill is licensed under Apache-2.0.

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