wingedguardian/genesis-agi/osint
Claude Code and agent skill by wingedguardian/genesis-agi
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Checking that the SKILL.md file is still in the repository.
OSINT investigation — discover, track, and report on people, companies, and technologies
Install
npx vskill@latest install wingedguardian/genesis-agi/osintSKILL.md
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 profilesite:stackshare.io "[company]"ORsite: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:
- Search (SearXNG / web search)
- Fetch top 3-5 results
- Extract structured data: names, dates, numbers, relationships
- 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:
Phase 5: Change Detection (for ongoing monitoring)
If this is a follow-up cycle on a previously investigated target:
- Compare current findings against previous snapshot
- Classify changes:
- CRITICAL (immediate attention): Leadership change, acquisition,
major funding (over 10M USD), 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
- Flag critical changes for immediate surfacing
Phase 6: Report Generation
Produce a structured intelligence report:
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.comvia search engines only - Respect robots.txt and rate limits
- Label all speculation as speculation
Output Format
References
src/genesis/skills/research/SKILL.md— General research methodologysrc/genesis/memory/— MemoryStore for persistencedocs/reference/gemini-routing.md— For video content during investigation
Security
- Security scanPassed, 90 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingsrc/genesis/skills/osint/SKILL.md
Popularity
- 7-day trend score
- 0
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