US Market Research Skills

A composable stack of agent skills for rigorous bottom-up equity research on US-listed companies — from idea discovery through primary data (SEC filings + market data), through an analytical framework, to a finished pitch. Each skill stands on its own; together they form a pipeline.

The skills

Layer	Skill	Job
Discovery	signal-sweep	Scan SEC filings and market data across the $50M–$10B universe to surface new investment ideas: insider cluster/rip/dip buys, activist 13D filings, market screens, keyword/theme search, conference discovery.
Data	sec-edgar-skill	Retrieve & extract SEC EDGAR filings (10-K/10-Q/8-K, 20-F/6-K, XBRL financials, ownership, holdings) and 13F institutional holder data (via 13f.info), token-efficiently. Unopinionated.
Data	market-scout	Pull price, returns, peers, sector screens, and earnings call transcripts via Yahoo Finance. Unopinionated.
Analysis	bottom-up-analyst	Turn one ticker into an earned, auditable investment memo — drives the data skills, classifies the archetype, values it, tries to kill it.
Voice	pitch-like-lou	Render a Norbert Lou–style Value Investors Club pitch from a finished thesis.

Salient Features

Composability

  signal-sweep  (surfaces tickers)
       │
       ▼
  bottom-up-analyst  (deep dive on one ticker)
       ├── sec-edgar-skill  (SEC filings)
       ├── market-scout     (price, peers, transcripts)
       ▼
  pitch-like-lou  (finished pitch)

• Discovery feeds analysis. signal-sweep scans the universe and produces shortlists of tickers with reasons. bottom-up-analyst takes one of those tickers and does the deep dive. They are independent — you can skip discovery and hand the analyst a ticker directly.
• The two data skills are independent and swappable. sec-edgar-skill (filings) and market-scout (market data) know nothing of each other; either can be replaced — e.g. point the analyst at a paid data provider instead of market-scout and nothing else changes.
• The analyst is the brain and the conductor. bottom-up-analyst decides what to pull, reasons over it, values the business, and writes the memo. It drives the data skills; they never decide what matters.
• The voice renders from a finished thesis. pitch-like-lou turns the analyst's memo into a pitch; it is not an idea generator.

Production order: signal-sweep → analyst → memo → (optionally) Lou pitches from it.

Progressive discovery at the center of design - lets your model's intelligence shine through

v0.1.0

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File                                        blank        comment           code
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./bottom-up-analyst/SKILL.md                   64              0            308
./pitch-like-lou/SKILL.md                      39              0            164
./sec-edgar-skill/SKILL.md                     36              0            135
./signal-sweep/SKILL.md                        27              0             82
./market-scout/SKILL.md                        19              0             60
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SUM:                                          185              0            749
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Language                     files          blank        comment           code
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Markdown                        34           1704              0           3370
Python                          19            746            627           2919
JSON                             2              0              0            109
YAML                             2             15              2             75
TOML                             1              5              2             30
Text                             3              3              0             17
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SUM:                            61           2473            631           6520
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Install

Install the whole stack, or any single skill on its own - point your agent at this repository, or at a single skill subfolder. Each skill is a self-contained folder with its own SKILL.md.

Setup

SEC identity (required)

The SEC's fair-access policy requires a contact name and email in the User-Agent header. Requests without one are blocked (HTTP 403). Set it once — sec-edgar-skill and signal-sweep both read it automatically:

export EDGAR_IDENTITY="Jane Analyst jane@example.com"     # bash/zsh
$env:EDGAR_IDENTITY = "Jane Analyst jane@example.com"     # PowerShell

Use your real name and email. The SEC uses this only to contact you if your traffic causes problems — it is not authentication.

Per-skill dependencies

• signal-sweep — pip install -r signal-sweep/requirements.txt
• sec-edgar-skill — pip install -r sec-edgar-skill/requirements.txt
• market-scout — install both before use: pip install -r market-scout/requirements.txt and npm install -g agent-browser && agent-browser install. No identity needed.
• bottom-up-analyst — valuation scripts are standard-library only; no install needed.
• pitch-like-lou — documentation and a reference corpus; nothing to install.

Contributing

This repo is agent-maintained. Start at AGENTS.md, then see context/MAP.md (where things live), context/DECISIONS.md (why), and context/CONVENTIONS.md (code rules). Lint with uv run ruff check . and npx markdownlint-cli2 "**/*.md". Work on a branch and open a PR — never commit to main directly.

A note on scope

These skills produce research, not advice. They are tools for doing diligence rigorously and honestly; nothing they output is a recommendation to buy or sell a security. The whole design — filings-first grounding, verified-vs-assumed tagging, the pre-mortem — exists to keep an LLM's fluent prose tethered to auditable evidence so a human can reach their own judgment.