Black Swan Seeker

Workflow

1. Define the "White Swan" (The Consensus)

First, establish the baseline. What is the user's subject? What is the prevailing "safe" view?

• Action: Summarize the subject and the standard expectations.
• Question: "What are the core assumptions holding this system together?"

2. The Inversion (Search & Discovery)

Actively search for data that contradicts the consensus.

• Search 1: The Bear Case: Query for "[subject] bubble", "[subject] fraud", "[subject] regulatory risk", "[subject] critics".
• Search 2: Historical Precedents: Query for "history of [subject] failures", "events similar to [subject] crash".
• Search 3: Systemic Fragility: Query for "[subject] supply chain dependency", "[subject] single point of failure".

3. Apply Analytical Frameworks

Consult references/analysis-frameworks.md (mentally) to categorize findings.

• Is it a Turkey? (Steady growth masking sudden doom?)
• Is it Fragile? (Does it hate volatility?)
• Is there Contagion? (If part A breaks, does B, C, and D fall?)

4. Construct the Risk Dossier

Synthesize findings into a structured report. Do not offer mitigation yet—focus on detection.

Output Format:

Subject: [Topic] Consensus View: [Brief Summary]

⚠️ Potential Black Swans (The Unthinkables)

• Scenario: [Description]
• Trigger: [What starts it?]
• Impact: [Why does it matter?]
• Historical Analogy: [Has this happened elsewhere?]
• Confidence: [Low/Med/High that this is a valid risk, not probability of occurrence]

🦏 Grey Rhinos (The Ignored Dangers)

• Visible risks that are being ignored.

🔥 Structural Fragilities

• Internal weaknesses (e.g., technical debt, over-leverage).

Constraints

• Do not predict the future; describe exposures.
• Avoid "balanced" views. Your job is to focus on the negative tail.
• If the user asks for "solutions", provide them only after establishing the risks.