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edgartools

Python library for accessing, analyzing, and extracting data from SEC EDGAR filings.

Skill by agent-skills-hub

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About

Python library for accessing, analyzing, and extracting data from SEC EDGAR filings. Use when working with SEC filings, financial statements (income statement, balance sheet, cash flow), XBRL financial data, insider trading (Form 4), institutional holdings (13F), company financials, annual/quarterly reports (10-K, 10-Q), proxy statements (DEF 14A), 8-K current events, company screening by ticker/CIK/industry, multi-period financial analysis, or any SEC regulatory filings.

Use cases: spreadsheets, data, finance

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What's inside

Skill name
edgartools
Description
Python library for accessing, analyzing, and extracting data from SEC EDGAR filings. Use when working with SEC filings, financial statements (income statement, balance sheet, cash flow), XBRL financial data, insider trading (Form 4), institutional holdings (13F), company financials, annual/quarterly reports (10-K, 10-Q), proxy statements (DEF 14A), 8-K current events, company screening by ticker/CIK/industry, multi-period financial analysis, or any SEC regulatory filings.
License
MIT
Metadata
skill-author: K-Dense Inc.
Instructions
130 lines in SKILL.md · view on GitHub

Files (8)

  • SKILL.md
  • ai-integration.md · references/
  • companies.md · references/
  • data-objects.md · references/
  • entity-facts.md · references/
  • filings.md · references/
  • financial-data.md · references/
  • xbrl.md · references/

SKILL.md (first lines)

# edgartools — SEC EDGAR Data

Python library for accessing all SEC filings since 1994 with structured data extraction.

## Authentication (Required)

The SEC requires identification for API access. Always set identity before any operations:

```python
from edgar import set_identity
set_identity("Your Name your.email@example.com")
```

Set via environment variable to avoid hardcoding: `EDGAR_IDENTITY="Your Name your@email.com"`.

## Installation

```bash
uv pip install edgartools
# For AI/MCP features:
uv pip install "edgartools[ai]"
```

## Core Workflow

### Find a Company

```python
from edgar import Company, find

company = Company("AAPL")        # by ticker
company = Company(320193)         # by CIK (fastest)
results = find("Apple")           # by name search
```

### Get Filings

```python
# Company filings
filings = company.get_filings(form="10-K")
filing = filings.latest()

# Global search across all filings
from edgar import get_filings
filings = get_filings(2024, 1, form="10-K")

# By accession number
from edgar import get_by_accession_number
filing = get_by_accession_number("0000320193-23-000106")
```

### Extract Structured Data

```python
# Form-specific object (most common approach)
tenk = filing.obj()              # Returns TenK, EightK, Form4, ThirteenF, etc.

# Financial statements (10-K/10-Q)
financials = company.get_financials()     # annual
financials = company.get_quarterly_financials()  # quarterly
income = financials.income_statement()
balance = financials.balance_sheet()
cashflow = financials.cashflow_statement()

# XBRL data
xbrl = filing.xbrl()
income = xbrl.statements.income_statement()
```

### Access Filing Content

```python
text = filing.text()             # plain text
html = filing.html()             # HTML
md = filing.markdown()           # markdown (good for LLM processing)
filing.open()                    # open in browser
```

## Key Company Properties

```python
company.name                     # "Apple Inc."
company.cik                      # 320193
company.ticker                   # "AAPL"
company.industry                 # "ELECTRONIC COMPUTERS"
company.sic                      # "3571"
company.shares_outstanding       # 15115785000.0
company.public_float             # 2899948348000.0
company.fiscal_year_end          # "0930"
company.exchange                 # "Nasdaq"
```

## Form → Object Mapping

| Form | Object | Key Properties |
|------|--------|----------------|
| 10-K | TenK | `financials`, `income_statement`, `balance_sheet` |
| 10-Q | TenQ | `financials`, `income_statement`, `balance_sheet` |
| 8-K | EightK | `items`, `press_releases` |
| Form 4 | Form4 | `reporting_owner`, `transactions` |
| 13F-HR | ThirteenF | `infotable`, `total_value` |
| DEF 14A | ProxyStatement | `executive_compensation`, `proposals` |
| SC 13D/G | Schedule13 | `total_shares`, `items` |
| Form D | FormD | `offering`, `recipients` |

**Important:** `filing.financials` does NOT exist. Use `filing.obj().financials`.

## Common Pitfalls

- `filing.financials` → AttributeError; use `filing.obj().financials`
- `get_filings()` has no `limit` param; use `.head(n)` or `.latest(n)`
- Prefer `amendments=False` for multi-period analysis (amended filings may be incomplete)
- Always check for `None` before accessing optional data

## Reference Files

Load these when you need detailed information:

- **[companies.md](references/companies.md)** — Finding companies, screening, batch lookups, Company API

From agent-skills-hub/agent-skills-hub, MIT.

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Signals

Stars
123
Forks
44
Open issues
6
Last commit (this folder)
Mar 2, 2026 (8 months ago)
Last release
Mar 2, 2026 (8 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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edgartools skill. Agent Mart. https://agentmart.dev/skills/agent-skills-hub-edgartools (last updated 2026-10-24)