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osint

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

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

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OSINT Investigation

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

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