A research command that documents what currently exists in a codebase, GitHub issue, or SEC filing. SEC filings are official company reports submitted to the U.S. Securities and Exchange Commission.

Use it to inspect implementation, architecture, component interactions, GitHub issues, or filing structures and explain them clearly.

It creates a factual map of systems and documents without mixing in redesign suggestions, root-cause analysis, or future improvements.

How dgunning/edgartools configures Claude Code

About the project

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.

dgunning/edgartools · 2,837 stars · on GitHub · edgartools.readthedocs.io

Reuse

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.

Copy the file

curl -O https://raw.githubusercontent.com/dgunning/edgartools/main/.claude/commands/research.md

Clone the repo

git clone --depth 1 https://github.com/dgunning/edgartools

Made for: Claude Code.

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/commands/dgunning/edgartools/research/github.svg)](https://agentmods.dev/commands/dgunning/edgartools/research)

Your own site

<a href="https://agentmods.dev/commands/dgunning/edgartools/research"><img src="https://agentmods.dev/badge/commands/dgunning/edgartools/research/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/commands/dgunning/edgartools/research"><img src="https://agentmods.dev/badge/commands/dgunning/edgartools/research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 2,118 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.

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	$0.00000	$0.02118
Opus 5.5	$0.00000	$0.00847
Sonnet 5.5	$0.00000	$0.00424
Haiku 4.5	$0.00000	$0.00212

Measured 2mo ago against content hash 57161142ae55, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

research 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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

research — 100% identical, 0 lines differ

.claude/commands/research.md · 212 lines

How it starts

The opening of the file, as written. The whole thing — 212 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Research

You are tasked with conducting comprehensive research to answer user questions by spawning parallel sub-agents and synthesizing their findings. This is Phase 1 of the Frequent Intentional Compaction (FIC) workflow.

This command adapts to different research contexts:

GitHub Issues (#NNN): Fetches issue, reproduces problem, analyzes affected code
SEC Filings (10-K, XBRL, etc.): Researches filing structures and patterns
Codebase (default): Explores implementation and architecture

CRITICAL: YOUR ONLY JOB IS TO DOCUMENT AND EXPLAIN WHAT EXISTS TODAY

DO NOT suggest improvements or changes unless the user explicitly asks for them
DO NOT perform root cause analysis unless the user explicitly asks for them
DO NOT propose future enhancements unless the user explicitly asks for them
DO NOT critique the implementation or identify problems
DO NOT recommend refactoring, optimization, or architectural changes
ONLY describe what exists, where it exists, how it works, and how components interact
You are creating a technical map/documentation of the existing system

Initial Setup:

When this command is invoked, respond with:

🔍 Starting research (Phase 1 of FIC workflow)

I'll analyze your query and adapt my approach based on the context:
- GitHub issues (#NNN) → Issue reproduction and analysis
- SEC filings (10-K, XBRL) → Filing structure research
- General queries → Codebase exploration

What would you like me to research?

Then wait for the user's research query.

Steps to follow after receiving the research query:

Detect research context and adapt approach:

GitHub Issue Detection (patterns: #NNN, issue NNN, gh-NNN):
- Use gh issue view NNN to fetch issue details and comments
- Focus research on reproduction and affected components
- Include issue metadata in research document
- Save to: docs-internal/issues/research/issue-NNN-research.md
SEC Filing Research (keywords: 10-K, 10-Q, 8-K, XBRL, DEF 14A, etc.):
- Prioritize the researcher agent for filing structures
- Include filing format variations across companies
- Document extraction opportunities
- Save to: docs-internal/research/sec-filings/YYYY-MM-DD-{topic}.md

Read the full file on GitHub · 212 lines

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.

2mo ago First seen · 212 lines · 0 tokens per session scan A 57161142ae55

Subscribe to this mod's changes

research is a command 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 2,118 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.

10-k 10-q Research balance-sheet edgar filings financials

research next to 6 commands from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
researchdgunning/edgartools	Command	2.8k	yesterday	MIT	A	0	Claude Code
checklistgithub/spec-kit	Command	148k	yesterday	MIT	A	13	Claude Code
clarifygithub/spec-kit	Command	148k	yesterday	MIT	A	27	Claude Code
specifygithub/spec-kit	Command	148k	yesterday	MIT	A	13	Claude Code
convergegithub/spec-kit	Command	148k	yesterday	MIT	A	35	Claude Code
implementgithub/spec-kit	Command	148k	yesterday	MIT	A	14	Claude Code
speckit.bug.fixgithub/spec-kit	Command	148k	yesterday	MIT	A	12	Claude Code

edgartools: Command for Claude Code