compare-peers

Compare a target company's financial ratios with industry peers and generate hypotheses for statistical outliers.

Updated Feb 18, 2026
One-click install
npx skills add https://github.com/tcole333/ithildin --skill compare-peers
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: compare-peers
Source: https://github.com/tcole333/ithildin/tree/main/.claude/skills/compare-peers
Command: npx skills add https://github.com/tcole333/ithildin --skill compare-peers

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires uv, python, json, yaml, and includes scripts (resource) and references (resource) components.

What problem does it solve?

The compare-peers skill addresses the challenge of comparing a target company's financial profile against a set of industry peers, identifying outliers, and generating hypotheses for further investigation.

Core Features & Use Cases

  • Financial Ratio Comparison: Compare a target company's financial ratios with 3-8 industry peers.
  • Outlier Detection: Identify statistical outliers in the financial data.
  • Hypothesis Generation: Create forensic hypotheses for each statistical outlier.
  • Use Case: Analyze a company's financial ratios and compare them to its peers to uncover anomalies that could indicate business concerns.

Quick Start

To start a financial comparison, use the command: /compare-peers "Target Company Name" --peers "Peer 1, Peer 2, Peer 3"

Frequently Asked Questions about compare-peers

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I compare a company's financial ratios against industry peers?

You can compare financial ratios against industry peers by specifying 3 to 8 peer companies, allowing the tool to calculate profile deviations, detect statistical outliers, and generate forensic hypotheses.

What is financial outlier detection and when is it needed?

Financial outlier detection identifies statistical anomalies in a company's financial ratios compared to its industry peers, needed when analyzing business profiles to uncover potential concerns or anomalies for further investigation.

How do I generate forensic hypotheses from financial data anomalies?

You generate forensic hypotheses from financial data anomalies by comparing a target company's financial ratios against peer benchmarks, which automatically creates investigative hypotheses for each statistical outlier detected.

Does this peer benchmarking approach require specific dependencies?

Yes, this peer benchmarking approach requires specific dependencies including uv, python, json, and yaml to query financial data, perform calculations, and store structured results.

Can I use this for company profiling with a small peer group?

Yes, you can use this for company profiling by comparing a target company's financial ratios against a small peer group of 3 to 8 industry peers to detect anomalies.

Why does industry benchmarking help uncover business concerns?

Industry benchmarking helps uncover business concerns by comparing a target company's financial ratios against peer profiles, highlighting statistical outliers that indicate potential operational or financial anomalies requiring deeper analysis.