FPEF Evidence Analyzer

FPEF Evidence Analyzer is a skill for Claude Code from aegntic/cldcde. It costs 40 tokens per session (2,786 once invoked), scanned A, original, MIT.

A structured method for investigating complex technical or business problems by finding issues, proving their causes with evidence, and applying targeted fixes. It is intended for failures, incidents, performance problems, and system optimisation.

In plain words
What is it for?
Analysing logs, metrics, and code; building root-cause hypotheses; validating findings; and checking whether an intervention worked.
Why use it?
It reduces guesswork by separating possible causes from verified causes and requiring evidence before a fix is chosen.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

Not installable on its own: it runs a file from its repository that does not travel with it. Clone the repository, or install whatever ships that file. The line is ./scripts/fpef-find.sh --scope-analysis.

Install

Getting it into your agent

There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for FPEF Evidence Analyzer

README.md
[![agentmods](https://agentmods.dev/badge/skills/aegntic/cldcde/fpef-analyzer.svg)](https://agentmods.dev/skills/aegntic/cldcde/fpef-analyzer)
Your own site
<a href="https://agentmods.dev/skills/aegntic/cldcde/fpef-analyzer"><img src="https://agentmods.dev/badge/skills/aegntic/cldcde/fpef-analyzer.svg" alt="Measured on agentmods" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,786 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00040 $0.02786
Opus 5 $0.00020 $0.01393
Sonnet 5 $0.00008 $0.00557
Haiku 4.5 $0.00004 $0.00279

Measured 6d ago against content hash cdf16e8595fb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

FPEF Evidence Analyzer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/fpef-analyze.sh), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/skills/fpef-analyzer/SKILL.md · 376 lines

How it starts

The opening of the file, as written. The whole thing — 376 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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

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

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"
}

Read the full file on GitHub · 376 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 376 lines · 40 tokens per session scan A cdf16e8595fb

Subscribe to this mod's changes

FPEF Evidence Analyzer is a skill published in the GitHub repository aegntic/cldcde (11 stars, last pushed 9d ago), licensed MIT. It adds 40 tokens to every session and 2,786 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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