Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add vyayasan/kyc-analyst --skill screeninggit clone --depth 1 https://github.com/vyayasan/kyc-analystWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/vyayasan/kyc-analyst/screening)<a href="https://agentmods.dev/skills/vyayasan/kyc-analyst/screening"><img src="https://agentmods.dev/badge/skills/vyayasan/kyc-analyst/screening/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/vyayasan/kyc-analyst/screening"><img src="https://agentmods.dev/badge/skills/vyayasan/kyc-analyst/screening.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00044 | $0.00732 |
| Opus 5.5 | $0.00018 | $0.00293 |
| Sonnet 5.5 | $0.00009 | $0.00146 |
| Haiku 4.5 | $0.00004 | $0.00073 |
Grade A, and why
screening scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Screening Skill - v1.0.0
Comprehensive sanctions and PEP screening with multi-database search, false positive assessment, and HITL decision gates.
Overview
Screening is a mandatory component of all KYC workflows. This skill provides standalone screening capability for ad-hoc checks, batch processing, and integration into onboarding/refresh workflows.
Screening Databases (12+ Sources)
Sanctions Lists
- OFAC SDN - US Specially Designated Nationals
- EU Consolidated Sanctions List - European Union
- UK HM Treasury - UK Financial Sanctions
- UN Consolidated List - United Nations Security Council
- Interpol - Red and Yellow Notices
- OpenSanctions - Open-source aggregated sanctions data
PEP Databases
- EveryPolitician - Global political figures
- Wikidata - Political and public figures
- UK Parliament - Register of Members' Interests
- CIA World Factbook - National leadership
- Electoral Commission databases - Candidates and office holders
Criminal/Legal
- UK Court records - Criminal convictions, CCJs
- Companies House - Insolvency records, disqualified directors
Screening Process
Step 1: Identify Screening Targets
- Customer (individual or entity)
- All beneficial owners (>25% threshold)
- Directors and senior management (entities)
- Family members and close associates (PEP cases)
Step 2: Execute Searches
For each target, search against all applicable databases:
- Record search date, platform, and search terms
- Document all matches (including potential false positives)
- Screenshot or save evidence
Step 3: False Positive Assessment [HITL Checkpoint]
When a potential match is found:
| Factor | Assessment |
|---|---|
| Name similarity | Exact / Partial / Common name |
| Date of birth | Match / Mismatch / Unknown |
| Nationality | Match / Mismatch |
| Location | Match / Mismatch |
| Photograph | Match / Mismatch / Not available |
| Context | Supports match / Against match |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 102 lines · 44 tokens per session scan A 2f1412a2f88c
screening is a skill published in the GitHub repository vyayasan/kyc-analyst (59 stars, last pushed 3mo ago), licensed MIT. It adds 44 tokens to every session and 732 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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