weakness-detection

<!-- version: 0.1.0 | outputs: memory/ideas/<slug>/weaknesses.json -->

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

<!-- TODO: Add failure mode library by app category -->

<!-- TODO: Define threshold for "weak" (e.g., dimension score < 40) -->

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/<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

<!-- TODO: Define "fatal" vs "major" vs "minor" by combination of weak dimensions -->