OSINT Investigation

SkillDev tools

OSINT investigation — discover, track, and report on people, companies, and technologies

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the OSINT Investigation skill

What this skill tells your AI

The instructions your AI receives, as published by wingedguardian/genesis-agi in src/genesis/skills/osint/SKILL.md and read by ahel’s review.

Purpose

Conduct open-source intelligence gathering on specific targets — people, companies, technologies, or markets. Discover publicly available information, track changes over time, assess source reliability, and produce structured intelligence reports.

This is NOT the awareness loop (which monitors Genesis's own systems). This is outward-facing investigation — finding information about external entities.

When to Use

  • User requests research on a person, company, or competitive entity.
  • Lead generation identifies a prospect needing deeper enrichment.
  • Strategic reflection flags a competitor or technology to monitor.
  • A scheduled monitoring task triggers a collection cycle.
  • An inbox item references an entity worth investigating.

Investigation Pipeline

Phase 1: Target Initialization

Define the target clearly:

  • Type: person | company | technology | market | competitor
  • Identity: name, aliases, known associations
  • Scope: what specifically to find (general profile, funding history, team composition, technology stack, competitive positioning)
  • Depth: surface (headlines only) | deep (full articles + sources) | exhaustive (multi-hop research across connected entities)

Phase 2: Query Construction

Build 10-20 search queries tailored to target type:

Person:

  • "[name]" [company] — basic association
  • "[name]" site:linkedin.com — public LinkedIn profile
  • "[name]" [industry] interview OR podcast OR keynote
  • "[name]" [company] announcement OR appointed OR promoted
  • "[name]" github OR gitlab — technical contributions

Company:

  • "[company]" funding OR "series A" OR "series B" OR acquisition
  • "[company]" hiring OR careers OR "we're hiring"
  • site:crunchbase.com "[company]" — Crunchbase profile
  • site:stackshare.io "[company]" OR site:builtwith.com "[company]" — tech stack
  • "[company]" review OR glassdoor — employee sentiment
  • "[company]" revenue OR valuation OR growth

Technology:

  • "[technology]" benchmark OR comparison OR vs
  • "[technology]" production OR deployment OR "in production"
  • "[technology]" github stars OR contributors OR releases
  • "[technology]" adoption OR migration OR "switched to"

Phase 3: Collection Sweep

For each query:

  1. Search (SearXNG / web search)
  2. Fetch top 3-5 results
  3. Extract structured data: names, dates, numbers, relationships
  4. Tag each data point with: source URL, timestamp, confidence, relevance

Source quality heuristics:

  • Official sources (filings, gov data, press releases) = Very High
  • Institutional (Reuters, AP, established publications) = High
  • Professional (industry pubs, analyst reports) = Medium-High
  • Community (forums, social media, reviews) = Medium
  • Anonymous/unverified = Low

Phase 4: Entity Extraction

For each data point, extract entities and relationships:

Entity types: Person, Organization, Product, Event, Financial, Technology, Location

Relationship types: works_at, founded, invested_in, competes_with, partnered_with, launched, acquired, uses_technology, located_in, reports_to

Store as structured records:

entity:
  name: <canonical name>
  type: <entity type>
  attributes:
    title: <if person>
    industry: <if company>
    founded: <if company>
    headcount: <if known>
  sources:
    - url: <source URL>
      reliability: <very_high | high | medium_high | medium | low>
      date_accessed: <YYYY-MM-DD>
  first_seen: <YYYY-MM-DD>
  confidence: high | medium | low

Phase 5: Change Detection (for ongoing monitoring)

If this is a follow-up cycle on a previously investigated target:

  1. Compare current findings against previous snapshot
  2. Classify changes:
    • CRITICAL (immediate attention): Leadership change, acquisition, major funding (>$10M), product discontinuation, legal action, security breach
    • IMPORTANT (include in next report): New product launch, partnership, hiring surge (>5 roles), pricing change, competitor move
    • MINOR (note in report): Blog post, minor update, conference appearance
  3. Flag critical changes for immediate surfacing

Phase 6: Report Generation

Produce a structured intelligence report:

# OSINT Report: [Target Name]

**Date:** YYYY-MM-DD
**Depth:** surface | deep | exhaustive
**Sources consulted:** N

## Summary
<3-5 sentence overview of key findings>

## Entity Profile
<structured profile data>

## Key Findings
1. <finding with source>
2. <finding with source>

## Changes Since Last Report (if applicable)
- [CRITICAL] <change>
- [IMPORTANT] <change>

## Relationships
<entity → relationship → entity map>

## Source Quality
| Source | Reliability | Data Points |
|--------|------------|-------------|

## Confidence Assessment
<overall confidence in findings, gaps identified>

## Recommended Follow-Up
- <what to investigate next>
- <what to monitor>

Phase 7: State Persistence

  • Store entity data as observations via MemoryStore
  • Update existing observations if entity already tracked
  • Record investigation metadata for future cycles

Source Evaluation Checklist

Before trusting any data point, check:

  • Recency — Is this from the last 12 months?
  • Primary vs Secondary — Is this the original source?
  • Corroboration — Can a second independent source confirm?
  • Bias — Does the source have an incentive to distort?
  • Specificity — Are claims specific and verifiable?
  • Track record — Has this source been reliable before?

If 3+ checks fail, downgrade confidence to "low."

Compliance Rules

  • Only use publicly available information
  • Do NOT attempt to bypass login walls, paywalls, or CAPTCHAs
  • Do NOT scrape behind authentication barriers
  • LinkedIn discovery uses site:linkedin.com via search engines only
  • Respect robots.txt and rate limits
  • Label all speculation as speculation

Output Format

investigation_id: <OSINT-YYYY-MM-DD-NNN>
target: <name>
target_type: <person | company | technology | market | competitor>
date: <YYYY-MM-DD>
depth: <surface | deep | exhaustive>
sources_consulted: <count>
entities_extracted: <count>
key_findings:
  - finding: <description>
    confidence: high | medium | low
    sources:
      - <URL>
    significance: critical | important | minor
changes_detected:
  - change: <description>
    significance: critical | important | minor
recommended_actions:
  - <next step>
monitoring_schedule: <none | weekly | daily>

References

  • src/genesis/skills/research/SKILL.md — General research methodology
  • src/genesis/memory/ — MemoryStore for persistence
  • docs/reference/gemini-routing.md — For video content during investigation

Signals

GitHub stars
96
Forks
23
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
osint-wingedguardian
Source
github.com/wingedguardian/genesis-agi