research-note

research-note is a skill for Claude Code, Codex from daloopa/investing. It costs 10 tokens per session (3,735 once invoked), scanned A, original, Apache-2.0.

A workflow for producing a professional company research report as a Word document. It gathers company information, market data, financial results, and cost details before rendering the document.

In plain words
What is it for?
Use it to create a research note with company setup, stock information, valuation inputs, historical financials, and cost-structure analysis.
Why use it?
It brings the research and document creation into one process, reducing the need to collect figures and format the report separately.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/daloopa/investing/research-note
Any agent
npx skills add daloopa/investing --skill research-note
Clone the repo
git clone --depth 1 https://github.com/daloopa/investing

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.

agentmods badge for research-note

README.md
[![agentmods](https://agentmods.dev/badge/skills/daloopa/investing/research-note.svg)](https://agentmods.dev/skills/daloopa/investing/research-note)
Your own site
<a href="https://agentmods.dev/skills/daloopa/investing/research-note"><img src="https://agentmods.dev/badge/skills/daloopa/investing/research-note.svg" alt="Measured on agentmods" height="20"></a>
Per session 10 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,735 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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.

ModelPer sessionOnce invoked
Fable 5 $0.00010 $0.03735
Opus 5 $0.00005 $0.01868
Sonnet 5 $0.00002 $0.00747
Haiku 4.5 $0.00001 $0.00374

Measured 5d ago against content hash 02c9e064851b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

research-note 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 5d 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.

.claude/skills/research-note/SKILL.md · 284 lines

How it starts

The opening of the file, as written. The whole thing — 284 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Generate a professional research note (.docx) for the company specified by the user: $ARGUMENTS

Before starting, read ../data-access.md for data access methods and ../design-system.md for formatting conventions. Follow the data access detection logic and design system throughout this skill.

This is an orchestrator skill that gathers comprehensive data, then renders a Word document. Work through each phase sequentially, building up a context object that gets written to JSON and rendered.

Phase A — Company Setup

Look up the company by ticker using discover_companies. Capture:

  • company_id
  • latest_calendar_quarter — anchor for all period calculations (see ../data-access.md Section 1.5)
  • latest_fiscal_quarter
  • Firm name for report attribution (default: "Daloopa") — see ../data-access.md Section 4.5

Get current stock price, market cap, shares outstanding, beta, and trading multiples for {TICKER} (see ../data-access.md Section 2 for how to source market data).

Initialize context: context = {company_name, ticker, date, price, market_cap, firm_name, ...}

Phase B — Core Financials + Cost Structure

Calculate 8 quarters backward from latest_calendar_quarter. Pull Income Statement metrics:

  • Revenue, Gross Profit, Operating Income, Net Income, Diluted EPS
  • EBITDA (compute as Op Income + D&A if not direct, label "(calc.)")
  • Operating Expenses (SG&A, R&D where available)

Pull Cash Flow & Balance Sheet:

  • Operating Cash Flow, CapEx, Free Cash Flow (OCF - CapEx, label "(calc.)")
  • Cash, Total Debt, Net Debt
  • D&A

For every value returned by get_company_fundamentals, record its fundamental_id (the id field). Store each data point as {value, fundamental_id} so citations can be rendered in the final document.

Compute margins and YoY growth rates for each quarter. Build context.financials with tables. Every Daloopa-sourced number must include its citation link: [$X.XX million](https://daloopa.com/src/{fundamental_id}).

Cost Structure & Margin Analysis (NEW)

After the core financial pull, add:

Read the full file on GitHub · 284 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.

  1. 5d ago First seen · 284 lines · 10 tokens per session scan A 02c9e064851b

Subscribe to this mod's changes

research-note is a skill published in the GitHub repository daloopa/investing (487 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 10 tokens to every session and 3,735 once invoked, about $0.0001 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 2026-08-30.

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