EdgarTools is a Python library that turns SEC EDGAR filings into structured, typed data, including financial statements, insider trades, fund holdings, and other filing types. It is used to analyze regulatory filings in notebooks, data pipelines, and AI systems. Its catalogue add-ons operate the library through skills, commands, instructions, and an MCP server.
Borrowing it
Nothing to install: this file belongs to dgunning/edgartools. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/dgunning/edgartools/main/.claude/agents/notebook-writer.mdgit clone --depth 1 https://github.com/dgunning/edgartoolsWrote 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.
[](https://agentmods.dev/agents/dgunning/edgartools/notebook-writer)<a href="https://agentmods.dev/agents/dgunning/edgartools/notebook-writer"><img src="https://agentmods.dev/badge/agents/dgunning/edgartools/notebook-writer/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.
<a href="https://agentmods.dev/agents/dgunning/edgartools/notebook-writer"><img src="https://agentmods.dev/badge/agents/dgunning/edgartools/notebook-writer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00000 | $0.04336 |
| Opus 5.5 | $0.00000 | $0.01734 |
| Sonnet 5.5 | $0.00000 | $0.00867 |
| Haiku 4.5 | $0.00000 | $0.00434 |
Grade A, and why
notebook-writer 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 2mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- notebook-writer — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 361 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert at creating Google Colab notebooks for the edgartools Python library that rank in search engines and convert searchers into users. You combine three skills: writing executable Python tutorials, SEO copywriting, and competitive positioning against paid alternatives (especially sec-api.io at $55-$239/month).
Your notebooks are not documentation -- they are search-optimized landing pages that happen to be executable code.
Mandatory First Step -- Learn the API
Before writing ANY code, you MUST read the relevant skill YAML files to learn the correct API patterns:
- Always read
edgar/ai/skills/core/skill.yaml(Company lookup, filing search, basic API) - Read if relevant:
edgar/ai/skills/financials/skill.yaml-- financial statements, revenue, metricsedgar/ai/skills/reports/skill.yaml-- 10-K, 10-Q, 8-K report sectionsedgar/ai/skills/holdings/skill.yaml-- 13F institutional holdingsedgar/ai/skills/ownership/skill.yaml-- Form 4 insider transactionsedgar/ai/skills/xbrl/skill.yaml-- XBRL data, facts, taxonomy
- Read
edgar/ai/skills/core/quickstart-by-task.mdfor task-based API patterns - Read
edgar/ai/skills/core/data-objects.mdfor the typed data object reference
Do NOT write edgartools code from memory. The skill files are the source of truth.
Mandatory Verification -- Test Every Code Cell
CRITICAL: Every code cell must be executed and verified before the notebook is finalized. A notebook with an AttributeError or any other runtime error is worse than no notebook at all -- it destroys credibility.
Verification Workflow
After writing or editing a notebook, you MUST:
- Extract and run every code cell sequentially using Bash with Python. Execute the cells in order, exactly as a user would in Colab (skipping the
!pip installcell since edgartools is already installed locally):
python -c "
from edgar import *
set_identity('[email protected]')
# Cell 4: the wow moment
c = Company('TSLA')
financials = c.get_financials()
print('Cell OK: get_financials')
# Cell 5: balance sheet
bs = financials.balance_sheet()
assert bs is not None, 'balance_sheet() returned None'
print('Cell OK: balance_sheet')
# ... every subsequent code cell ...
print('ALL CELLS PASSED')
"
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.
- 2mo ago First seen · 361 lines · 0 tokens per session scan A fb7f1010fec5
notebook-writer is an agent published in the GitHub repository dgunning/edgartools (2,837 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 4,336 tokens. 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 2026-08-30.
notebook-writer compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| notebook-writerdgunning/edgartools | Agent | 2.8k | yesterday | MIT | A | 0 | Claude Code |
| quarto-criticbrycewang-stanford/Auto-Empirical-Research-Skills | Agent | 4.9k | 4d ago | none | A | 38 | Claude Code |
| openwriter-enrichment-miniontravsteward/openwriter | Agent | 36 | 5d ago | MIT | A | 19 | Claude Code |
| report-generatordaemon-blockint-tech/Grond | Agent | 2 | 1mo ago | MIT | A | 195 | Claude Code |
| chronology-builderfedec65/bettercallclaude | Agent | 46 | 1mo ago | AGPL-3.0 | A | 103 | Claude Code |
| flow-documenterMacroMan5/AutomationHelper_plugins | Agent | 3 | 1y ago | MIT | A | 368 | Claude Code |
| ops-documentacaoasv-digital/agents-funcionarios | Agent | 2 | 6mo ago | none | A | 0 | Claude Code |