cldcde: Skill for Claude Code

FPEF Evidence Analyzer

Overview

Rigorous evidence-based analysis framework that systematically finds problems, proves root causes, gathers supporting evidence, and implements targeted fixes for complex technical and business systems.

Prerequisites

• System or problem description
• Access to relevant data sources (logs, metrics, code)
• Basic understanding of the domain being analyzed

What This Skill Does

1. Find: Systematic identification of anomalies and potential issues
2. Prove: Causal analysis to establish root cause relationships
3. Evidence: Comprehensive evidence collection and validation
4. Fix: Targeted interventions with verification of effectiveness

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Quick Start (60 seconds)

Rapid Analysis

# FPEF Interactive Analysis
1. Describe the problem: [e.g., "API response times increased 300%"]
2. Timeframe: [e.g., "Last 24 hours"]
3. Affected systems: [e.g., "Payment processing API"]
4. Available data: [e.g., "CloudWatch logs, database metrics"]

→ FPEF generates comprehensive analysis framework

Immediate Output

Analysis framework includes:

• ✅ Problem statement with clear scope definition
• ✅ Hypothesis tree with potential root causes
• ✅ Evidence collection plan with data sources
• ✅ Investigation timeline with critical path
• ✅ Fix validation strategy and success criteria
• ✅ Prevention measures for future incidents

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Configuration

Analysis Parameters

Edit resources/fpef-config.json:

{
  "problem_description": "Clear description of the issue",
  "scope": "Systems, components, or processes affected",
  "timeline": "When the problem started and duration",
  "severity": "critical|high|medium|low",
  "business_impact": "Revenue, users, operations affected",
  "data_sources": ["logs", "metrics", "traces", "code"],
  "constraints": ["time", "budget", "access", "expertise"]
}

Analysis Settings

{
  "depth": "comprehensive|focused|rapid",
  "certainty_threshold": "0.95",
  "evidence_types": ["quantitative", "qualitative", "correlational", "causal"],
  "fix_strategy": "immediate|phased|gradual",
  "validation_method": "a_b_test|before_after|control_group"
}