screen-targets

Screen public companies for financial red flags using SEC EDGAR data.

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

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires uv, python, sqlite3, yaml, json, db, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the screening of public companies for financial red flags, providing a scored anomaly matrix and leads for companies warranting further investigation.

Core Features & Use Cases

  • Automated Ratio Analysis: Scan multiple public companies for red flags using structured financial data from SEC EDGAR.
  • Scoring and Ranking: Score anomalies and rank companies based on severity, generating leads for those that warrant further analysis.
  • Use Case: Use this Skill to quickly identify potential red flags in the financials of public companies, streamlining the process of due diligence and investment analysis.

Quick Start

Scan financial red flags for companies 'PLTR, SMCI, RKLB, ASTS' using the screen-targets skill.

Frequently Asked Questions about screen-targets

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

FAQPage Schema
How do I automate financial red flag screening for public companies?

Automate financial red flag screening by analyzing structured financial data from SEC EDGAR, scoring anomalies, and generating leads for further investigation. The Skill scans multiple public companies, calculates ratios, and ranks them based on anomaly severity to streamline due diligence.

What financial ratios are used to detect anomalies in public company analysis?

Financial ratio analysis detects anomalies by scanning structured SEC EDGAR data to identify inconsistencies and red flags. The mechanism scores these anomalies and ranks companies by severity, generating leads for deeper investment analysis and due diligence.

Do I need Python and SQLite to run financial screening on SEC EDGAR data?

Yes, you need Python and SQLite to run financial screening on SEC EDGAR data. The workflow requires a Python environment with uv, yaml, json, and db dependencies to extract structured financial data, execute ratio analysis, and store the resulting anomaly scores.

What's the best way to rank public companies by financial anomaly severity?

The best way to rank public companies by financial anomaly severity is using an automated scoring matrix that evaluates structured SEC EDGAR financial data. This approach calculates ratio anomalies, scores them, and outputs a ranked list of leads for further investigation.

Can I scan multiple public companies for red flags at the same time?

Yes, you can scan multiple public companies for red flags simultaneously by passing a list of ticker symbols to the screening script. The tool processes structured SEC EDGAR data for each company, scores anomalies, and generates a consolidated list of leads.