Classifies discovered weaknesses into severity tiers (fatal/major/minor/cosmetic) with structured justification and exploitability assessment.
Scanned 5/27/2026
Install via CLI
openskills install yogsoth-ai/de-anthropocentric-research-engine---
name: weakness-classification
description: Classifies discovered weaknesses into severity tiers (fatal/major/minor/cosmetic) with structured justification and exploitability assessment.
execution: subagent
prompt: ./prompt.md
input: raw_finding (string), artifact_context (string)
used-by: multiagent-debate, red-teaming, adversarial-stress-testing
---
# Weakness Classification
Classifies discovered weaknesses into severity tiers.
## Execution
Subagent — spawned via subagent-spawning/spawn-agent.
## Why Subagent
Classification requires careful reasoning about impact scope and exploitability — dedicated context prevents bias from the discovery process.
## Input
- **raw_finding**: The weakness finding with context from discovery
- **artifact_context**: The original artifact being validated
## Output
- **severity**: `fatal` | `major` | `minor` | `cosmetic`
- **category**: type of weakness (logical, evidential, methodological, scope, assumption, implementation)
- **justification**: why this severity level
- **exploitability**: how easily this weakness could be exploited/triggered in practice
## Classification Scheme
- **fatal**: Invalidates the core claim — artifact cannot be used as-is
- **major**: Significantly undermines validity but not fatal — requires substantial revision
- **minor**: Weakens periphery — addressable without fundamental changes
- **cosmetic**: Presentation/clarity issue only — does not affect validity
## Budget
One unit = one classification. Called per finding.
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