mcpbeat

Osint Investigation

hezaohezao/osint-investigation

Public-records OSINT: SEC, sanctions, courts, property.

1k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
117
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/HezaoHezao/poirot --skill osint-investigation

What it tells the agent to use

found in the instruction text
Bash runs shell commands — read the instruction before connecting

The instruction itself

14 sections, as written by the author

OSINT Investigation — Public Records Cross-Reference

Investigative framework for public-records OSINT: government contracts,

corporate filings, lobbying, sanctions, offshore leaks, property records,

court records, web archives, knowledge bases, and global news. Resolve

entities across heterogeneous sources, build cross-links with explicit

confidence, and produce structured evidence chains.

Python stdlib only. Zero install. Most sources work with no API key.

When to Use

Use when the user asks for:

  • "follow the money" — government contracts, lobbying → legislation, sanctions
  • Corporate due diligence — who controls company X, where incorporated, board

members, filings

  • Sanctions screening — is entity X on OFAC SDN, ICIJ offshore leaks
  • Property ownership — find recorded deeds/mortgages by name or address
  • Litigation history — find federal + state court opinions
  • Multi-source entity resolution where naming varies (LLC suffixes, abbreviations)
  • Evidence-chain construction with explicit confidence levels
  • "what's been said about X" — international news + Wikipedia + Wayback Machine

Core Sources

Corporate & Financial

| Source | What | Access |

|--------|------|--------|

| SEC EDGAR | US public company filings (10-K, 10-Q, 8-K, 13F) | curl to https://efts.sec.gov/LATEST/search-index?q=... |

| USAspending.gov | Federal contracts and grants | curl to https://api.usaspending.gov/api/v2/... |

| Senate Lobbying | Lobbying Disclosure Act filings | curl to https://lda.senate.gov/api/v1/... |

| OFAC SDN | Sanctions list | curl to https://www.treasury.gov/ofac/... |

| ICIJ Offshore Leaks | Panama Papers, Paradise Papers, etc. | browse_page to https://offshoreleaks.icij.org/... |

| OpenCorporates | Corporate registry (optional free token) | curl to https://api.opencorporates.com/... |

Property & Courts

| Source | What | Access |

|--------|------|--------|

| NYC ACRIS | NYC property records (deeds, mortgages) | browse_page to https://a836-acris.nyc.gov/... |

| CourtListener | Federal + state court opinions | curl to https://www.courtlistener.com/api/... |

Archives & Knowledge

| Source | What | Access |

|--------|------|--------|

| Wayback Machine | Archived web pages | browse_page to https://web.archive.org/web/... |

| Wikipedia/Wikidata | Encyclopedia + structured data | bash with curl to Wikipedia API |

| GDELT | Global news monitoring | bash with curl to https://api.gdeltproject.org/... |

Methodology

1. Entity Resolution

Before cross-referencing, resolve the entity across sources:

  • Normalize names (LLC suffixes, abbreviations, DBA aliases)
  • Identify unique identifiers (EIN, LEI, CIK, OpenCorporates ID)
  • Build a canonical entity record with all known aliases

2. Source-by-Source Query

For each relevant source, query by entity name or identifier:

# SEC EDGAR — search for company filings
curl -s "https://efts.sec.gov/LATEST/search-index?q=%22Company+Name%22" | python3 -c "..."

# USAspending — federal contracts to entity
curl -s -X POST "https://api.usaspending.gov/api/v2/search/spending_by_award/" -d '{"filters":{...}}'

# OFAC SDN — check sanctions list
curl -s "https://www.treasury.gov/ofac/downloads/sdn.csv" | grep -i "entity name"

Build explicit cross-links between sources:

  • Same entity appearing in multiple sources
  • Timing correlation (contract award → lobbying registration → legislation)
  • Shared addresses, phone numbers, officers across entities

4. Confidence Scoring

For each finding, assign confidence:

  • High: Official government record, multiple corroborating sources
  • Medium: Single official source, or multiple unofficial sources
  • Low: Single unofficial source, unverified

5. Evidence Chain

Construct an evidence chain showing how findings connect:

[Source A: fact 1] → [Source B: fact 2] → [Inference: conclusion]
  confidence: High      confidence: Medium     confidence: Medium

Output

Produce a structured investigation report:

# OSINT Investigation: [Entity / Topic]

## Executive Summary
[2-3 paragraph overview of findings]

## Entity Profile
- **Canonical Name**: ...
- **Aliases**: ...
- **Identifiers**: EIN, LEI, CIK, etc.
- **Known Addresses**: ...

## Findings by Source

### SEC EDGAR
[Findings with dates, filing types, key data]

### USAspending
[Contract awards, amounts, dates, agencies]

### OFAC SDN
[Sanctions status: CLEAR / MATCH (with details)]

### [Other sources...]

## Cross-Link Analysis
[Explicit connections between findings across sources]

## Evidence Chain
[Step-by-step reasoning from raw data to conclusions]

## Confidence Assessment
[Summary of confidence levels for key conclusions]

## Sources
[All URLs queried, with access dates]

Save to .poirot/outputs/osint-{entity}-{YYYYMMDD}.md.

Pitfalls

  • Name variants: "Acme LLC", "Acme L.L.C.", "Acme" may be different

entities. Normalize but don't assume.

  • Stale data: Public records may lag. Note the record's date.
  • False positives: Sanctions list partial name matches need full record

review. Don't report a match without verifying the full entry.

  • Rate limits: Government APIs may rate-limit. Add delays between requests.
  • Legal caution: OSINT findings are leads, not proof. Frame as "evidence

suggests" not "proven".

How to use it

Copy the folder

Take hezaohezao/osint-investigation from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.