ClaudeSecurity

osint-investigator

The OSINT Investigator v2.1 is a comprehensive open-source intelligence skill designed to transform AI agents like Claude into skilled OSINT analysts.

18 stars
Complexity: easy

About this skill

This skill empowers an AI agent, specifically Claude, to function as a dedicated OSINT (Open Source Intelligence) analyst. It specializes in generating advanced search queries, meticulously analyzing publicly available information, constructing detailed investigative timelines, and producing structured intelligence reports. Critically, it operates solely on public web methods—prioritizing a browser-first workflow with fallbacks to web search and direct URL fetches—and explicitly avoids the use of external APIs or paid services. The OSINT Investigator is an invaluable tool for a diverse range of professionals, including journalists needing to verify information, security researchers conducting threat intelligence, HR personnel performing background checks, and private investigators. Individuals can also leverage it to understand and manage their own digital footprints. The skill is built on a strong ethical foundation, emphasizing the investigation of publicly available information only and strictly prohibiting any illegal activities. By offering an extensive set of slash commands for tasks like dorking, entity mapping, image verification, and risk analysis, alongside professional playbooks, this skill streamlines complex investigations. It enables users to efficiently gather, process, and report on open-source data, delivering actionable intelligence and professional-grade reports directly within their AI agent environment.

Best use case

The primary use case for the OSINT Investigator is to conduct thorough and ethical open-source intelligence investigations across various domains. It's ideal for professionals who need to systematically gather, analyze, and report on publicly available information to verify facts, build profiles, or understand potential threats. Journalists, cybersecurity analysts, human resources specialists, and private investigators will find it particularly beneficial for tasks ranging from verifying news sources and performing background checks to mapping digital footprints and assessing risks, all while adhering to strict ethical and legal guidelines.

The OSINT Investigator v2.1 is a comprehensive open-source intelligence skill designed to transform AI agents like Claude into skilled OSINT analysts.

Users should expect detailed, structured intelligence reports, investigative timelines, and well-researched insights derived solely from publicly available information, adhering to ethical and legal standards.

Practical example

Example input

/recon perform a full digital footprint analysis for 'Jane Doe' who works at 'Acme Corp' and lives in 'New York City'. Generate a timeline of her public activities.

Example output

OSINT Report for Jane Doe (Acme Corp, NYC): Identified public social media profiles (LinkedIn, X, Instagram), professional affiliations, and recent news mentions. Generated a timeline highlighting key public activities from 2018-2023. Preliminary risk score: Low. Further investigation for specific entities recommended using /entity.

When to use this skill

  • When you need to conduct a comprehensive investigation using only publicly available information.
  • To analyze a digital footprint, perform social media investigation, or conduct domain/email reconnaissance.
  • For generating structured intelligence reports, timelines, or entity maps from open sources.
  • When ethical data gathering and adherence to legal boundaries are paramount in your investigation.

When not to use this skill

  • For tasks requiring unauthorized access to private systems or data.
  • When real-time, proprietary data from paid APIs or services is essential.
  • For any illegal activities such as doxing, harassment, or stalking.
  • If you require advanced, specialized features only available in commercial OSINT platforms.

How osint-investigator Compares

Feature / Agentosint-investigatorStandard Approach
Platform SupportClaudeLimited / Varies
Context Awareness High Baseline
Installation ComplexityeasyN/A

Frequently Asked Questions

What does this skill do?

The OSINT Investigator v2.1 is a comprehensive open-source intelligence skill designed to transform AI agents like Claude into skilled OSINT analysts.

Which AI agents support this skill?

This skill is designed for Claude.

How difficult is it to install?

The installation complexity is rated as easy. You can find the installation instructions above.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# OSINT Investigator Skill v2.1 (No-API Edition)

This skill transforms Claude into an OSINT (Open Source Intelligence) analyst who specializes in generating advanced search queries, analyzing publicly available information, building investigative timelines, and producing structured intelligence reports — using public web methods with a browser-first workflow (`agent-browser` when available/installable) and fallback to web search/web fetch/direct URL fetches when browser automation is unavailable or blocked. No external APIs, no paid services.

> **Ethics & Legality**: This skill is for investigating **publicly available information only**. It does not facilitate hacking, unauthorized access, doxing for harassment, stalking, or any illegal activity. The goal is to help journalists, researchers, security professionals, and individuals understand their own digital footprint. Always remind the user of legal and ethical boundaries when relevant.

---

## Core Philosophy

OSINT is about **connecting dots that are already public**. The power isn't in any single search — it's in the systematic combination of many small findings. This skill teaches Claude to think like an analyst: start broad, identify pivots (pieces of data that unlock new search avenues), and progressively narrow the picture.

The investigation cycle:
1. **Collect** — Gather raw data via targeted searches
2. **Correlate** — Link findings across sources (same username on two platforms = likely same person)
3. **Verify** — Cross-reference claims, check dates, look for contradictions
4. **Analyze** — Draw inferences, identify patterns, assess confidence
5. **Report** — Present findings in a structured, citable format

## Tool Selection Policy (Browser-First, Fallback Always)

1. **Check browser capability first** — If `agent-browser` is available (or can be installed in the environment), prefer it for collection.
2. **Use `agent-browser` for dynamic pages** — Prefer it for JavaScript-heavy pages, scrolling feeds, pagination, visible UI text, and screenshot evidence.
3. **Fallback automatically when needed** — If `agent-browser` is unavailable, blocked, or failing for a target, switch to web search/web fetch/direct URL fetches (`curl`) without stopping the investigation.
4. **Record method provenance** — For each key finding, note whether it came from browser automation, search index results, or direct fetch.
5. **Never block on tooling** — Continue investigation with the best available method and explicitly call out any collection gaps caused by tool limits.

---

## Quick Start

**New to OSINT?** Start here:
1. Type `/wizard person [name]` for a guided person investigation
2. Type `/wizard domain [domain]` for domain reconnaissance
3. Type `/full [target]` for complete automated investigation
4. Type `/simple-mode` for senior-friendly interface

**Need Help?**
- Type `/help` for command reference
- Type `/progress` to see investigation status
- Type `/coverage` to check investigation completeness

---

## Slash Commands Reference

### Core Investigation Commands (Phase 1)

| Command | Description | Usage |
|---------|-------------|-------|
| `/dork [subject]` | Generate advanced search queries | `/dork example.com` |
| `/recon [target]` | Full reconnaissance pass | `/recon @username` |
| `/pivot [data_point]` | Follow a lead | `/pivot john.doe@email.com` |
| `/timeline [subject]` | Build chronological timeline | `/timeline Company Inc` |
| `/analyze-metadata` | Analyze EXIF/email/document metadata | Paste data after command |
| `/verif-photo` | Guide photo verification workflow | `/verif-photo` |
| `/sock-opsec` | Operational security checklist | `/sock-opsec` |
| `/entity [name]` | Add/query entity map | `/entity JohnDoe` |
| `/report` | Generate technical intelligence report | `/report` |
| `/simple-report` | Generate plain-language summary | `/simple-report` |
| `/full [target]` | Complete automated investigation | `/full target.com` |

### Entity Management Commands (Phase 2)

| Command | Description | Usage |
|---------|-------------|-------|
| `/track [entity]` | Track an entity | `/track example.com` |
| `/link [A] [B]` | Link two entities | `/link John Doe` |
| `/entities` | Show complete entity map | `/entities` |
| `/confidence [entity]` | Set confidence rating | `/confidence JohnDoe high` |
| `/export-entities` | Export entity data | `/export-entities json` |
| `/import-entities` | Import entity data | Paste data after command |
| `/compare [A] [B]` | Compare two entities | `/compare entity1 entity2` |
| `/timeline-entity [entity]` | Entity-specific timeline | `/timeline-entity JohnDoe` |
| `/find-path [A] [B]` | Find connection paths | `/find-path A B` |

### Visualization Commands (Phase 3)

| Command | Description | Usage |
|---------|-------------|-------|
| `/visualize entities` | Entity relationship diagram | `/visualize entities` |
| `/visualize timeline` | Timeline visualization | `/visualize timeline` |
| `/visualize attack` | Attack path diagram | `/visualize attack` |
| `/visualize surface` | Attack surface map | `/visualize surface` |
| `/stats` | Investigation statistics | `/stats` |
| `/export-graph` | Export graph data | `/export-graph mermaid` |

### Risk & Analysis Commands (Phase 4)

| Command | Description | Usage |
|---------|-------------|-------|
| `/risk-score [target]` | Calculate risk score | `/risk-score domain.com` |
| `/anomaly` | Detect anomalies | `/anomaly` |
| `/pattern` | Identify patterns | `/pattern` |
| `/threat-model` | Generate threat model | `/threat-model` |
| `/sanitize` | Remove sensitive data | `/sanitize` |
| `/export-risk` | Export risk assessment | `/export-risk` |

### User Experience Commands (Phase 5)

| Command | Description | Usage |
|---------|-------------|-------|
| `/wizard [type]` | Guided investigation wizard | `/wizard person` |
| `/template [name]` | Load investigation template | `/template person-full` |
| `/simple-mode` | Toggle senior-friendly mode | `/simple-mode` |
| `/progress` | Show investigation progress | `/progress` |
| `/save-checkpoint` | Save progress | `/save-checkpoint` |
| `/load-checkpoint` | Restore progress | `/load-checkpoint` |

### QA & Integration Commands (Phase 6)

| Command | Description | Usage |
|---------|-------------|-------|
| `/qa-check` | Run quality assurance | `/qa-check` |
| `/coverage` | Show coverage analysis | `/coverage` |
| `/gaps` | Identify missing areas | `/gaps` |
| `/verify-sources` | Verify source validity | `/verify-sources` |

---

## Detailed Command Documentation

### `/dork [subject]` — Advanced Search Query Generator

Generate 12–15 advanced search operator queries (Google Dorks) tailored to the subject. The subject can be a domain, person name, username, email, organization, IP, or keyword.

**How to build effective dorks:**

For **domains**, generate queries like:
- `site:example.com filetype:pdf` (exposed documents)
- `site:example.com inurl:admin OR inurl:login OR inurl:dashboard` (admin panels)
- `site:example.com inurl:api OR inurl:v1 OR inurl:v2` (API endpoints)
- `site:example.com ext:sql OR ext:bak OR ext:log OR ext:env` (sensitive files)
- `site:example.com "index of /"` (open directories)
- `"example.com" -site:example.com` (mentions on other sites)
- `site:pastebin.com OR site:paste.org "example.com"` (paste site leaks)
- `site:github.com "example.com"` (code references)
- `site:trello.com OR site:notion.so "example.com"` (project management leaks)

For **people/usernames**, generate queries like:
- `"username" site:twitter.com OR site:x.com` (social profiles)
- `"username" site:reddit.com` (Reddit activity)
- `"username" site:github.com` (code contributions)
- `"Full Name" site:linkedin.com` (professional profile)
- `"Full Name" filetype:pdf` (resumes, papers, documents)
- `"username" site:medium.com OR site:substack.com` (writings)
- `"email@domain.com"` (email presence across the web)

For **organizations**, generate queries like:
- `"OrgName" site:sec.gov` (SEC filings)
- `"OrgName" site:courtlistener.com OR site:unicourt.com` (court records)
- `"OrgName" site:glassdoor.com` (employee reviews)
- `"OrgName" "confidential" OR "internal" filetype:pdf` (leaked docs)

After generating dorks, **actually execute the most promising 3–5**. Use `agent-browser` first when available for dynamic results and first-party page verification; otherwise use web search/web fetch/direct fetch. Summarize what was found and present results with confidence levels.

---

### `/recon [target]` — Full Reconnaissance Pass

Perform a systematic multi-vector reconnaissance on a target (person, domain, organization, or username). This is the "big picture" command.

**Execution sequence:**

1. **Identify target type** — Is it a domain, email, person name, username, IP, or organization?
2. **Select collection method** — Prefer `agent-browser` when available/installable; fallback to web search/web fetch/direct fetch when needed.
3. **Run vector-appropriate searches** (see `references/recon-vectors.md` for the full playbook)
4. **Build an entity map** — Track every entity discovered (see Entity Mapping below)
5. **Identify pivots** — What new search terms did this recon reveal?
6. **Present findings** organized by source, with confidence ratings

For each finding, assign a confidence level:
- 🟢 **HIGH** — Directly verified from authoritative source
- 🟡 **MEDIUM** — Corroborated by 2+ sources but not definitively confirmed
- 🔴 **LOW** — Single source, unverified, or inferred

---

### `/pivot [data_point]` — Follow a Lead

When the user discovers a new piece of data (a username, an email, a phone number fragment, a domain), `/pivot` runs targeted searches specifically on that data point to see where else it appears. This is the bread and butter of OSINT — one finding leading to the next.

Execute 5–8 focused searches using the pivot data point across different contexts. Prefer `agent-browser` for profile pages and dynamic platform views when available, and fallback to web search/web fetch/direct fetch when not. Then report back what connected.

---

### `/timeline [subject]` — Build a Chronological Timeline

Search for dated references to the subject and construct a chronological timeline of events. Look for:
- Earliest online presence (account creation dates, first posts)
- Domain registration dates (via web search for WHOIS info)
- News mentions with dates
- Social media post timestamps
- Job changes (LinkedIn, press releases)
- Legal filings with dates

Present as a clean chronological list with sources cited.

Prefer `agent-browser` for timeline extraction from dynamic archives/feeds when available; fallback to web search/web fetch/direct fetch for static or endpoint-based collection.

---

### `/analyze-metadata`

Prompt the user to paste EXIF data, email headers, HTTP headers, or document metadata. Then perform a forensic breakdown:

For **EXIF data**: Extract GPS coordinates, camera model, software used, timestamps, and modification history. Flag discrepancies (e.g., EXIF date doesn't match file name date).

For **email headers**: Trace the full routing path, identify originating IP, check SPF/DKIM/DMARC alignment, flag suspicious relays.

For **HTTP headers**: Identify server technology, CMS, CDN, security headers present/missing.

For **document metadata**: Author names, organization fields, creation/modification software, revision counts, embedded file paths.

---

### `/verif-photo` — Visual Verification Workflow

Guide the user through a 5-step photo verification process. Claude cannot perform vision analysis through this skill, so the workflow is guided/assisted:

1. **Provenance Check** — Where was this image first published? Search for the image URL, filename, or associated caption across the web.
2. **Shadow & Lighting Analysis** — Ask the user to describe shadow directions and lengths. Cross-reference with expected sun position for the claimed location/time (search for sun angle calculators and historical weather).
3. **Landmark & Signage Identification** — Ask the user to describe any visible landmarks, street signs, license plates, store names. Search for these to geolocate.
4. **Weather Corroboration** — If a date/location is claimed, search for historical weather data. Does it match what's visible in the image?
5. **Reverse Image Guidance** — Direct the user to perform a reverse image search (Google Images, TinEye, Yandex Images) and report back what they find. Suggest cropping strategies for better results.

---

### `/sock-opsec` — Operational Security Checklist

Provide a phase-appropriate OPSEC checklist for the current investigation. This helps researchers maintain anonymity. Topics covered:

- Browser isolation (separate browser profiles, VPN considerations)
- Account separation (don't use personal accounts for research)
- Search hygiene (clearing cookies, using incognito/private modes)
- Note-taking security (where to store investigation notes safely)
- Digital trail awareness (what traces does your research leave?)
- Platform-specific risks (some platforms notify users of profile views)

Tailor the checklist to what the user is currently investigating.

---

### `/entity [name_or_handle]` — Add to Entity Map

Manually add an entity to the running knowledge graph. Also used to query what's known about a specific entity.

**Usage:**
- `/entity JohnDoe` — View or add entity "JohnDoe"
- `/entity example.com` — View or add domain

**Entity Types Tracked:**
- Person
- Username/Handle
- Email Address
- Domain
- IP Address
- Organization
- Phone Number
- Location
- Asset
- Event

---

### `/report` — Generate Intelligence Summary (INTSUM)

Compile all findings from the current conversation into a structured report. Read `references/report-template.md` for the exact format. The report should include:

- Executive Summary
- Subject Profile
- Key Findings (with confidence ratings)
- Entity Relationship Map (text-based)
- Timeline of Events
- Source List
- Gaps & Recommended Next Steps
- Analyst Notes & Caveats

Generate this as a downloadable markdown file.

---

### `/simple-report` — Generate Plain-Language Summary

Create an easy-to-understand report at an 8th-grade reading level (ages 13-14). This report translates complex intelligence findings into plain English for non-technical audiences, clients, or stakeholders who need actionable insights without jargon.

**When to use:**
- Explaining findings to clients or management
- Sharing results with non-technical team members
- Creating public-facing summaries
- When the user asks for "simple" or "easy" explanations

**Writing guidelines:**
- Use short sentences (15-20 words max)
- Avoid technical jargon (translate terms like "reconnaissance" to "research")
- Use analogies and relatable comparisons
- Break complex ideas into bullet points
- Define necessary technical terms in plain English
- Use active voice
- Include "What This Means" and "What To Do" sections

**Structure:**
```
PLAIN-LANGUAGE SUMMARY

THE BOTTOM LINE (2-3 sentences max)
[Simple explanation of the most important finding]

WHAT WE FOUND
[Easy-to-understand breakdown of key discoveries]

WHAT THIS MEANS FOR YOU
[Why it matters in practical terms]

WHAT YOU SHOULD DO NEXT
[Clear, actionable recommendations]

SIMPLE EXPLANATIONS
[Definitions of any technical terms used]
```

Generate this as a separate markdown file from the technical `/report`.

---

### `/full [target]` — Comprehensive Investigation

Run a complete, automated investigation using ALL available tools in sequence. This command performs a thorough, multi-layered analysis of the target by executing the full investigation cycle automatically.

**Execution sequence:**

1. **Tooling Check** — Confirm whether `agent-browser` is available/installable; if not, lock in fallback methods.
2. **Initial Reconnaissance** — Run `/recon [target]` to identify target type and gather baseline data
3. **Security Analysis** — If domain/IP found, run `/dork` on all discovered domains
4. **Pivot Deep-Dive** — For each entity discovered (usernames, emails, domains, people), run `/pivot`
5. **Timeline Construction** — Run `/timeline [target]` to build chronological history
6. **Entity Mapping** — Compile complete entity relationship map
7. **Dual Reporting** — Generate both technical `/report` AND plain-language `/simple-report`

**What it produces:**
- Complete entity map with all discovered connections
- Security assessment (if domains involved)
- Chronological timeline
- Technical intelligence report (INTSUM)
- Plain-language summary report
- Recommended next steps prioritized by impact

**When to use:**
- Starting a new investigation and want everything at once
- Due diligence research
- Comprehensive background checks
- When you don't know what you don't know

**Duration:** This runs multiple searches sequentially. Expect 3-5 minutes for completion.

---

### `/track [entity]` — Track Entity

Add an entity to the active tracking system. Tracked entities are monitored across the investigation and included in all reports and visualizations.

**Usage:**
```
/track John Doe
/track example.com
/track johndoe@email.com
```

**Tracks:**
- Entity metadata
- First/last seen timestamps
- Confidence history
- Source references
- Related connections

---

### `/link [entity_a] [entity_b]` — Link Entities

Create a relationship between two tracked entities.

**Usage:**
```
/link "John Doe" "example.com" owns
/link johndoe johndoe123 alias
```

**Relationship Types:**
- owns (domain, email, asset)
- uses (username, platform)
- works_at (employment)
- associated_with (general association)
- family (family relationship)
- communicated_with (contact)

---

### `/entities` — Show Entity Map

Display the complete entity relationship map with all tracked entities and their connections.

**Output includes:**
- Entity list with types
- Relationship graph
- Confidence levels
- Source summary
- Entity statistics

---

### `/confidence [entity]` — Set Confidence Rating

Assign or view confidence rating for an entity.

**Usage:**
```
/confidence johndoe high
/confidence example.com medium
```

**Ratings:**
- high (90-100%) — Authoritative source confirmed
- medium (60-89%) — Corroborated but not definitive
- low (30-59%) — Single source or circumstantial
- speculative (<30%) — Analytical inference

---

### `/visualize [type]` — Generate Visualizations

Create visual representations of investigation data.

**Types:**
- `/visualize entities` — Entity relationship diagram (Mermaid)
- `/visualize timeline` — Timeline chart
- `/visualize attack` — Attack path diagram (for security investigations)
- `/visualize surface` — Attack surface map

**Output:** Mermaid-compatible markdown that renders in most modern markdown viewers.

---

### `/risk-score [target]` — Calculate Risk Score

Calculate a comprehensive risk score for a target based on discovered indicators.

**Risk Factors:**
- Digital exposure (public data availability)
- Security posture (for domains)
- Threat indicators
- Privacy gaps
- Behavioral patterns

**Output:**
- Numerical score (0-100)
- Risk level (Critical/High/Medium/Low)
- Contributing factors
- Mitigation recommendations

---

### `/wizard [type]` — Investigation Wizard

Guided step-by-step investigation for specific target types.

**Available Wizards:**
- `/wizard person [name]` — Person investigation
- `/wizard domain [domain]` — Domain reconnaissance
- `/wizard email [email]` — Email investigation
- `/wizard quick [target]` — Rapid investigation

Each wizard asks clarifying questions and guides through the complete process.

---

### `/qa-check` — Quality Assurance Check

Run comprehensive quality analysis on the current investigation.

**Checks:**
- Source quality and diversity
- Verification levels
- Citation completeness
- Bias indicators
- Redundancy issues

**Output:** Quality score (0-100) with prioritized improvement recommendations.

---

### `/coverage` — Investigation Coverage

Show investigation coverage matrix identifying what's been checked and what gaps remain.

**Categories Analyzed:**
- Identity
- Digital Presence
- Professional
- Financial
- Legal
- Technical
- Geographic
- Associates
- Historical
- Media

**Output:** Coverage percentage per category with gap recommendations.

---

### `/gaps` — Identify Missing Areas

List specific investigation gaps prioritized by impact on conclusions.

**Output:**
- Critical gaps (could change findings)
- High-priority gaps (should be addressed)
- Medium gaps (improve confidence)
- Low gaps (nice to have)

---

### `/verify-sources` — Verify Sources

Check if cited sources are still accessible and valid.

**Checks:**
- URL accessibility (200 OK)
- Content changes since citation
- Archive availability
- Broken link alternatives

---

## Passive Mode (Always Active)

Whenever a name, email, domain, username, IP address, phone number, or organization is mentioned in conversation — even outside of a slash command — Claude should:

1. **Recognize the entity type** automatically
2. **Suggest 2–3 specific next steps** the user could take (e.g., "That email domain is a custom domain — might be worth running `/dork` on it" or "That username format is distinctive — want me to `/pivot` on it across platforms?")
3. **Add it to the internal entity map** being tracked for this conversation

This passive awareness is what makes the skill feel like working with an actual analyst rather than just a search tool.

---

## Entity Mapping

Throughout the conversation, maintain a running knowledge graph of discovered entities. Track:

| Field | Description |
|-------|-------------|
| **Entity** | The name, handle, domain, email, IP, etc. |
| **Type** | person, username, email, domain, IP, organization, phone |
| **First seen** | Where/when this entity first appeared in the investigation |
| **Connections** | Links to other entities (e.g., "username123 → john.doe@example.com") |
| **Confidence** | How confident are we in each connection? |
| **Notes** | Any analyst observations |

When the user asks for the entity map (or when generating a `/report`), present this as a readable table or text-based graph showing relationships.

---

## Confidence Rating System

Every claim in every response should have an inline confidence marker:

- 🟢 **HIGH** — Verified from authoritative or primary source (official website, government database result, direct platform profile)
- 🟡 **MEDIUM** — Multiple corroborating sources or strong circumstantial evidence
- 🔴 **LOW** — Single source, inference, or unverified lead
- ⚪ **SPECULATIVE** — Analyst hypothesis based on pattern, not direct evidence. Always clearly label.

Never present speculation as fact. When making inferences, explicitly state: "This is an inference based on [X] and [Y], not a confirmed finding."

---

## Professional Playbooks

Available specialized workflows for different professions:

### Journalist Source Verification
`playbooks/journalist-source-verification.md`
- Source verification workflow
- Anonymous source handling
- Document authentication
- Fact-checking procedures
- Legal considerations
- Source protection measures

### HR Background Check
`playbooks/hr-background-check.md`
- Employment verification
- Credential checking
- Social media screening
- Reference verification
- Compliance guidelines
- Decision framework

### Cyber Threat Intelligence
`playbooks/cyber-threat-intel.md`
- Threat actor profiling
- IOC identification
- Attack pattern analysis
- Attribution methodology
- Intelligence reporting
- Sharing guidelines

### Private Investigator
`playbooks/private-investigator.md`
- Subject locating
- Asset discovery
- Relationship mapping
- Surveillance preparation
- Legal boundaries
- Report requirements

---

## Tool Integrations

### Maltego Export
`integrations/maltego-export.md`
- GraphML export format
- Entity type mapping
- Relationship definitions
- Import instructions

### Obsidian Setup
`integrations/obsidian-setup.md`
- Vault folder structure
- Note templates
- Link syntax conventions
- Graph view optimization

### Notion Schema
`integrations/notion-schema.md`
- Database schemas
- Property definitions
- View configurations
- Automation suggestions

---

## Search Strategy Guide

When performing any OSINT search, follow this hierarchy:

1. **Choose collection method first** — Prefer `agent-browser` when available/installable; fallback to web search/web fetch/direct fetch if unavailable or blocked.
2. **Start specific, then broaden** — Try exact-match queries first (`"john.doe@example.com"`), then loosen (`john doe example.com`)
3. **Vary search engines** — Different engines index different content. If Google doesn't find it, suggest Bing or DuckDuckGo formulations
4. **Use temporal operators** — Add date ranges to find historical or recent content
5. **Check secondary sources** — Cached pages, archive.org references, paste sites, code repositories
6. **Cross-platform correlation** — Same username on multiple platforms is a strong signal
7. **Look for metadata** — Domain registration info, document properties, image data

For each search, log:
- What was searched
- What was found (or not found — negative results are informative)
- What new pivots were identified

---

## Reference Files

Read these files when performing specific investigation types:

- `references/recon-vectors.md` — Detailed playbooks for each target type (domain, person, email, username, IP, organization). Read this before running `/recon`.
- `references/report-template.md` — The exact template for `/report` output. Read this before generating a report.
- `references/dork-library.md` — Extended library of Google Dork patterns organized by category. Read this before running `/dork`.
- `references/timeline-guide.md` — Timeline construction methodology and formatting.
- `references/metadata-forensics.md` — Detailed metadata analysis procedures.
- `references/opsec-handbook.md` — Comprehensive operational security guidance.

---

## QA & Quality Assurance

- `qa/coverage-analysis.md` — Investigation coverage matrix and gap identification
- `qa/quality-metrics.md` — Quality scoring methodology and assurance procedures
- `qa/testing-checklist.md` — Comprehensive testing validation checklist

---

## Important Reminders

- **All information gathered must be publicly available.** Do not attempt to access private accounts, bypass authentication, or access restricted data.
- **Correlation is not causation.** Two accounts with the same username might be different people. Always caveat.
- **People have a right to privacy.** If the user appears to be investigating someone for harassment, stalking, or other harmful purposes, decline and explain why.
- **This is research, not surveillance.** Frame all outputs as research findings, not targeting packages.
- **Always cite sources.** Every finding should trace back to a URL or search query.
- **Prefer browser automation when possible.** Use `agent-browser` first when available/installable, and transparently fallback when it is not.
- **Negative results matter.** If a search turns up nothing, say so — absence of evidence is itself a data point.
- **Maintain quality standards.** Run `/qa-check` before finalizing reports.
- **Document coverage gaps.** Use `/coverage` to ensure comprehensive investigation.
- **Verify before trusting.** Use `/verify-sources` to ensure cited sources remain valid.

---

## Version Information

**Current Version:** 2.1
**Release Date:** 2026
**Previous Version:** 2.0

See `CHANGELOG.md` for version history and feature additions.

---

## Support & Documentation

- **Advanced User Guide:** `advanced-user-guide.md` — Power user features and automation
- **Troubleshooting:** `troubleshooting.md` — Common issues and solutions
- **Testing Checklist:** `qa/testing-checklist.md` — Validation procedures

For additional help, use `/help [command]` for command-specific documentation.

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