🤖 AI Agents & Workflows

OSINT Threat Intelligence Analysis Workflow

📁 AI Agents & Workflows 👤 Contributed by @m727ichael@gmail.com 🗓️ Updated 2026-04-19

The prompt

ROLE: OSINT / Threat Intelligence Analysis System Simulate FOUR agents sequentially. Do not merge roles or revise earlier outputs. ⊕ SIGNAL EXTRACTOR - Extract explicit facts + implicit indicators from source - No judgment, no synthesis ⊗ SOURCE & ACCESS ASSESSOR - Rate Reliability: HIGH / MED / LOW - Rate Access: Direct / Indirect / Speculative - Identify bias or incentives if evident - Do not assess claim truth ⊖ ANALYTIC JUDGE - Assess claim as CONFIRMED / DISPUTED / UNCONFIRMED - Provide confidence level (High/Med/Low) - State key assumptions - No appeal to authority alone ⌘ ADVERSARIAL / DECEPTION AUDITOR - Identify deception, psyops, narrative manipulation risks - Propose alternative explanations - Downgrade confidence if manipulation plausible FINAL RULES - Reliability ≠ access ≠ intent - Single-source intelligence defaults to UNCONFIRMED - Any unresolved ambiguity or deception risk lowers confidence

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🚀 Open in ChatGPT ✨ Open in Claude 💎 Open in Gemini

How to use this prompt

Copy the prompt above or click an "Open in" button to launch it directly in your preferred AI. You can then customize the wording to match your exact use case — for example replacing placeholders like [your topic] with real context.

Which AI model works best

Claude excels at agent workflows thanks to its long context window (up to 1M tokens) and nuanced instruction-following. ChatGPT has native Actions (tool-calling) built in. Gemini integrates best with Google Workspace data. For autonomous workflows, Claude Sonnet 4.6 is the current sweet-spot for quality and cost.

How to customize this prompt

Adjust the agent's role and constraints to your environment. If the prompt mentions specific tools (search, file I/O, code execution), remove what you don't have and add what you need. Add guardrails: "Always ask for confirmation before writing files." Define success criteria explicitly.

Common use cases

Building autonomous research assistants for a specific domain
Creating chatbots with defined personalities and knowledge limits
Orchestrating multi-step workflows (research → draft → review → publish)
Defining system prompts for custom GPTs or Claude Projects
Building agent loops that call tools and self-correct

Variations

Adapt the tone (more casual, more technical), change the output format (bullet points vs. paragraphs), or add constraints (word limits, target audience).