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SriRamkunamsetty
SriRamkunamsettyCOMMUNITY
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osint-investigation

Cross-reference public records to link entities and generate evidence chains.

Updated May 20, 2026
Search Tags:#cross-reference#osint#evidence-chain#entity-resolution#public-records#python-stdlib
One-click install
npx skills add https://github.com/SriRamkunamsetty/SITA2.0-HermesAgent --skill osint-investigation-sriramkunamsetty
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: osint-investigation
Source: https://github.com/SriRamkunamsetty/SITA2.0-HermesAgent/tree/main/hermes-agent/optional-skills/research/osint-investigation
Command: npx skills add https://github.com/SriRamkunamsetty/SITA2.0-HermesAgent --skill osint-investigation-sriramkunamsetty

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Cross-source OSINT aggregation and entity-resolution across public records, enabling traceable evidence chains that connect people, companies, and events.

Core Features & Use Cases

  • Multi-source OSINT workflow: pulls data from SEC EDGAR, USAspending, Senate lobbying, OFAC SDN, ICIJ Offshore Leaks, NYC ACRIS, OpenCorporates, CourtListener, Wayback, Wikipedia + Wikidata, and GDELT.
  • Entity resolution and cross-linking: normalizes names, resolves candidates, and generates cross_links.csv for attribution and verification.
  • Evidence chain assembly: builds structured findings with traceable sources and confidence levels for investigations or due-diligence reporting.
  • Use in investigations, journalism, compliance, and risk monitoring to surface relationships and timelines.

Quick Start

Run the fetch and resolution scripts to collect data for a target entity and generate a findings.json that encodes an evidence chain.

Frequently Asked Questions about osint-investigation

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I cross-reference public records for OSINT entity resolution?▼

OSINT entity resolution cross-references public records from multiple sources to identify connections between people and companies. This skill normalizes data from sources like SEC EDGAR and OFAC SDN to generate traceable cross-links for verification.

Can I aggregate public records data using only Python standard library?▼

Yes, you can aggregate public records using a stdlib-only Python toolkit. The scripts handle data ingestion and normalization from sources like USAspending and OpenCorporates without requiring external dependencies.

How do I build an evidence chain for due diligence investigations?▼

Building an evidence chain for due diligence involves structuring findings with traceable sources and confidence levels. This skill generates a findings.json file that connects entities, companies, and events through verified cross-references.

What public records sources can I cross-reference for OSINT investigations?▼

OSINT investigations can cross-reference sources including SEC EDGAR, USAspending, Senate lobbying, OFAC SDN, ICIJ Offshore Leaks, NYC ACRIS, OpenCorporates, CourtListener, Wayback, Wikipedia, Wikidata, and GDELT.

Does OSINT cross-referencing work for journalism and compliance risk monitoring?▼

OSINT cross-referencing works for journalism, compliance, and risk monitoring by surfacing relationships and timelines between entities. It resolves candidate names and generates cross_links.csv for attribution and verification across public records.

What's the best way to establish entity links across public records datasets?▼

Establishing entity links across public records datasets requires normalizing names and resolving candidates from multiple sources. This skill generates cross_links.csv to map relationships between entities and their activities for attribution.

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