Re-evaluate S/O/D scores after mitigation measures are in place. Validates that mitigations actually reduce risk as expected.
Scanned 5/27/2026
Install via CLI
openskills install yogsoth-ai/de-anthropocentric-research-engine---
name: re-scoring
description: Re-evaluate S/O/D scores after mitigation measures are in place. Validates that mitigations actually reduce risk as expected.
execution: subagent
prompt: ./prompt.md
input: failure_modes (string), mitigations (string), original_scores (string)
used-by: [failure-anticipation]
---
# Re-Scoring
Re-evaluates Severity, Occurrence, and Detection scores after mitigations are applied.
## Execution
Subagent — spawned via subagent-spawning/spawn-agent.
## Why Subagent
Re-scoring requires fresh evaluation without anchoring to original scores. Isolated context prevents confirmation bias toward expected improvement.
## Input
- **failure_modes**: Original failure mode descriptions
- **mitigations**: Proposed mitigation measures
- **original_scores**: Pre-mitigation S/O/D scores for comparison
## Output
- **new_scores**: Post-mitigation S, O, D, and RPN for each mode
- **effectiveness**: Comparison with original scores
- **still_high**: Modes that remain H-priority after mitigation
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Universal deep research agent team. 13-agent pipeline for rigorous academic research on any topic. 7 modes: full research, quick brief, paper review, lit-review, fact-check, Socratic guided research dialogue, and systematic review with optional meta-analysis. Covers research question formulation, Socratic mentoring, methodology design, systematic literature search, source verification, cross-source synthesis, risk of bias assessment, meta-analysis, APA 7.0 report compilation, editorial review...