sec-edgar-pipeline

name	sec-edgar-pipeline
description	SEC EDGAR extraction pipeline: setup, filing discovery by CIK, recipe-driven extraction, and report generation.
user-invocable	false
disable-model-invocation	true
version	1.0.0
category	universal
author	Claude MPM Team
license	MIT
progressive_disclosure	{"entry_point":{"summary":"EDGAR pipeline: configure keys + user-agent, find filings by CIK, extract data via recipes/scripts, and export CSV/JSON reports.","when_to_use":"Building SEC EDGAR extraction flows, running edgar-analyzer CLI, or generating compensation/filing reports from DEF 14A and related filings.","quick_start":"1. edgar-analyzer setup 2. edgar-analyzer analyze-project projects/<name> 3. edgar-analyzer generate-code 4. edgar-analyzer run-extraction"}}
tags	["sec","edgar","filings","cik","def14a","extraction"]

SEC EDGAR Pipeline

Overview

This pipeline is centered on edgar-analyzer and the EDGAR data sources. The core loop is: configure credentials, create a project with examples, analyze patterns, generate code, run extraction, and export reports.

Setup (Keys + User Agent)

Use the setup wizard to configure required keys:

python -m edgar_analyzer setup
# or
edgar-analyzer setup

Required entries:

• OPENROUTER_API_KEY
• (Optional) JINA_API_KEY
• EDGAR user agent string ("Name [e-mail]")

End-to-End CLI Workflow

# 1. Create project
edgar-analyzer project create my_project --template minimal

# 2. Add examples + project.yaml
# projects/my_project/examples/*.json

# 3. Analyze examples
edgar-analyzer analyze-project projects/my_project

# 4. Generate extraction code
edgar-analyzer generate-code projects/my_project

# 5. Run extraction
edgar-analyzer run-extraction projects/my_project --output-format csv

Outputs land in projects/<name>/output/.

EDGAR-Specific Conventions

• CIK values are 10-digit, zero-padded (e.g., 0000320193).
• Rate limit: SEC API allows 10 requests/sec. Scripts use ~0.11s delays.
• User agent is mandatory; include name + email.

Scripted Example (Apple DEF 14A)

edgar/scripts/fetch_apple_def14a.py shows the direct flow:

1. Fetch latest DEF 14A metadata
2. Download HTML
3. Parse Summary Compensation Table (SCT)
4. Save raw HTML + extracted JSON + ground truth

Recipe-Driven Extraction

edgar/recipes/sct_extraction/config.yaml defines a multi-step pipeline:

• Fetch DEF 14A filings by company list
• Extract SCT tables with SCTAdapter
• Validate with sct_validator
• Write results to output/sct