A Python library for finding and extracting structured information from SEC EDGAR filings, the public company reports database maintained by the U.S. Securities and Exchange Commission.

Use it to search filings, retrieve company financial statements, analyze XBRL data, and inspect reported company or insider information.

It saves you from manually downloading and parsing filings such as annual reports, quarterly reports, insider trading forms, and institutional ownership reports.

edgartools — Skill for Claude Code and Codex by LeonChaoX

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add LeonChaoX/qinyan-academic-skills --skill edgartools

Clone the repo

git clone --depth 1 https://github.com/LeonChaoX/qinyan-academic-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/leonchaox/qinyan-academic-skills/edgartools/github.svg)](https://agentmods.dev/skills/leonchaox/qinyan-academic-skills/edgartools)

Your own site

<a href="https://agentmods.dev/skills/leonchaox/qinyan-academic-skills/edgartools"><img src="https://agentmods.dev/badge/skills/leonchaox/qinyan-academic-skills/edgartools/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/leonchaox/qinyan-academic-skills/edgartools"><img src="https://agentmods.dev/badge/skills/leonchaox/qinyan-academic-skills/edgartools.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 110 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,350 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00110	$0.01350
Opus 5	$0.00055	$0.00675
Sonnet 5	$0.00022	$0.00270
Haiku 4.5	$0.00011	$0.00135

Measured 7d ago against content hash ca9a2f2fb442, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

edgartools scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

edgartools — 100% identical, 0 lines differ

skills/15-金融与经济数据/edgartools/SKILL.md · 137 lines

How it starts

The opening of the file, as written. The whole thing — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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:

from edgar import set_identity
set_identity("Your Name [email protected]")

Set via environment variable to avoid hardcoding: EDGAR_IDENTITY="Your Name [email protected]".

Installation

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

Core Workflow

Find a Company

from edgar import Company, find

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

Get Filings

# 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

# 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

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

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"

Read the full file on GitHub · 137 lines

Files

What ships with it

7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

7d ago First seen · 137 lines · 110 tokens per session scan A ca9a2f2fb442

Subscribe to this mod's changes

edgartools is a skill published in the GitHub repository LeonChaoX/qinyan-academic-skills (880 stars, last pushed 1mo ago), licensed MIT. It adds 110 tokens to every session and 1,350 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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edgartools