smithery/bobmatnyc

sec-edgar-pipeline

SEC EDGAR extraction pipeline: setup, filing discovery by CIK, recipe-driven extraction, and report generation.

Installation

$ npx skills add smithery/bobmatnyc --skill sec-edgar-pipeline

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Skill metadata

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Version1.0.0
LicenseMIT

Package contents

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  • skill md SKILL.md 3,145 B
  • docs SUMMARY.md 137 B

History

  1. First recorded snapshot · 0 installs

SKILL.md

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:

  • OPENROUTERAPIKEY
  • (Optional) JINAAPIKEY
  • EDGAR user agent string ("Name [email protected]")

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/fetchappledef14a.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

Report Generation

edgar/scripts/createcsvreports.py converts JSON results into:

  • executivecompensation<timestamp>.csv
  • top25executives_<timestamp>.csv
  • companysummary<timestamp>.csv

Troubleshooting

  • No filings found: confirm CIK formatting and filing type (DEF 14A vs DEF 14A/A).
  • API errors: slow down requests and confirm user-agent is set.
  • Extraction errors: regenerate code or use manual ground truth in POC scripts.

Related Skills

  • universal/data/reporting-pipelines
  • toolchains/python/testing/pytest