| 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/<slug>/scores.json (required)- All available dimension files in
memory/ideas/<slug>/
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
- Load scores.json, identify dimensions scoring below threshold.
- For each weak dimension, read the source file to understand why.
- Classify the root cause (structural / situational / knowledge gap / addressable).
- Describe the failure mode if the idea proceeded without fixing this weakness.
Output
Write to memory/ideas/<slug>/weaknesses.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
