--- name: weakness-detection description: Analyzes idea-scoring output to identify the weakest dimensions, root causes of low scores, and probable failure modes if the idea were pursued as-is. --- # Skill: weakness-detection ## Purpose Before triggering the pivot engine, understand WHY dimensions are weak. A low distribution score might mean "no viral loop" (fixable) or "fundamentally wrong category for organic growth" (structural). Surface the root cause, not just the symptom. ## Input - Idea slug - `memory/ideas//scores.json` (required) - All available dimension files in `memory/ideas//` ## Weakness Classification | Root Cause Type | Description | Fix Type | |---|---|---| | Structural | Inherent to the idea, can't be pivoted away | Drop or major pivot | | Situational | Weak due to user's current constraints | Fixable (more time, budget) | | Knowledge gap | Weak because data is missing | Run more research | | Addressable | Weak but has a clear fix | Targeted pivot | ## Process 1. Load scores.json, identify dimensions scoring below threshold. 2. For each weak dimension, read the source file to understand why. 3. Classify the root cause (structural / situational / knowledge gap / addressable). 4. Describe the failure mode if the idea proceeded without fixing this weakness. ## Output Write to `memory/ideas//weaknesses.json`: ```json { "weak_dimensions": [ { "dimension": "", "score": 0, "root_cause_type": "structural | situational | knowledge-gap | addressable", "root_cause_description": "", "failure_mode": "" } ], "critical_weaknesses": [], "addressable_weaknesses": [], "overall_weakness_severity": "fatal | major | minor" } ``` ## Notes