Financial Deep Research
Run institutional-style financial research with SEC-first sources, triangulation, and packaged reports from Claude Code.
Overview
financial-deep-research is an agent skill most often used in Idea (also Validate, Grow) that runs an 8.5-phase financial research pipeline with SEC-prioritized sources and critique/refine packaging.
Install
npx skills add https://github.com/eng0ai/eng0-template-skills --skill financial-deep-researchWhat is this skill?
- 8.5-phase financial pipeline: Scope, Plan, Retrieve, Triangulate, Outline Refinement, Synthesize, Critique, Refine, Pack
- Research modes: Quick, Standard, Deep, and UltraDeep
- Tier 1 source priority: SEC EDGAR, Federal Reserve, company IR before general web
- Financial credibility scoring and SEC filing verification in the critique path
- Outputs oriented to investment-grade reports (HTML/PDF under research_output per project layout)
- Four research modes: Quick, Standard, Deep, UltraDeep
Adoption & trust: 528 installs on skills.sh; 5 GitHub stars; 2/3 security scanners passed (skills.sh audits).
What problem does it solve?
You need diligence-quality answers on companies, markets, or regulation but default web search mixes blogs with filings and never triangulates financial facts.
Who is it for?
Solo founders researching competitors, macro context, or issuer fundamentals before building or pitching a finance-adjacent product.
Skip if: Live trading execution, personalized investment advice, or tasks that only need a single known 10-K URL opened without synthesis.
When should I use this skill?
User asks for financial, market, regulatory, or issuer research that needs multi-source retrieval and packaged reporting.
What do I get? / Deliverables
You receive a structured, critique-refined research package grounded in tiered financial sources suitable for decisions, memos, or downstream planning.
- Packaged research report
- Scoped outline and synthesized memo artifacts in research_output
Recommended Skills
Journey fit
Spans multiple journey phases - primary shelf plus alternate fits below.
Deep financial research most often starts in Idea when evaluating markets and competitors, but the same pipeline supports validate pricing and grow content strategy. The skill is scoped to research retrieval and synthesis, not building trading code or deploying infra.
Where it fits
Map a niche fintech’s competitors using 10-K segments and Fed macro series.
Compare public SaaS peers’ unit economics language from recent filings.
Ground a pricing hypothesis in disclosed ARPU and segment reporting.
Produce a cited brief for a launch post on regulatory trends.
How it compares
Skill package for terminal research pipelines, not a Bloomberg terminal API or live market data MCP server.
Common Questions / FAQ
Who is financial-deep-research for?
Indie builders and operators who want SEC- and regulator-aware research workflows inside Claude Code without standing up a separate research stack.
When should I use financial-deep-research?
In Idea for market and competitor research, in Validate when pricing or regulatory scope needs evidence, or in Grow when content and lifecycle messaging need cited financial context.
Is financial-deep-research safe to install?
Check the Security Audits panel on this page; the skill expects network retrieval and may write research_output artifacts—review outputs before sharing externally.
SKILL.md
READMESKILL.md - Financial Deep Research
# Python __pycache__/ *.py[cod] *$py.class *.so .Python *.egg-info/ .eggs/ *.egg # Virtual environments venv/ ENV/ env/ # IDE .vscode/ .idea/ *.swp *.swo # OS .DS_Store Thumbs.db # Research outputs (generated during runtime) /research_output/ *.pdf *.html # Temporary files *.tmp *.temp *.log # Financial Deep Research Skill for Claude Code A comprehensive financial research engine that brings institutional-quality financial analysis capabilities to Claude Code terminal. ## Overview This skill is specialized for financial services research, building on the deep-research skill with: - **Financial data source prioritization**: SEC filings, Bloomberg, Reuters, S&P, Morningstar - **Regulatory compliance awareness**: SEC, FINRA, Federal Reserve, OCC sources - **Financial credibility scoring**: Tiered source evaluation for financial data - **Investment-grade output**: Professional reports suitable for institutional use ## Features ### Core Research Pipeline - **8.5-Phase Financial Pipeline**: Scope > Plan > Retrieve (Parallel) > Triangulate > Outline Refinement > Synthesize > Critique > Refine > Package - **Multiple Research Modes**: Quick, Standard, Deep, and UltraDeep - **Financial-Specific Verification**: SEC filing verification, financial data cross-checking ### Financial Data Sources (Priority Order) **Tier 1 - Primary/Regulatory (Highest Credibility):** - SEC EDGAR (10-K, 10-Q, 8-K, proxy statements) - Federal Reserve (FRED data, monetary policy) - Company IR (investor relations, earnings calls) - Exchange filings (NYSE, NASDAQ disclosures) **Tier 2 - Financial Data Providers:** - Bloomberg, Reuters, S&P Global - Moody's, Fitch (credit ratings) - FactSet, Morningstar, PitchBook **Tier 3 - Financial News & Research:** - Wall Street Journal, Financial Times, Barron's - Institutional research (Goldman, Morgan Stanley) **Tier 4 - General Business Sources:** - CNBC, Yahoo Finance (verify with primary sources) - Seeking Alpha (user-generated, verify claims) ### 2025 Enhancements - **Auto-Continuation System**: TRUE UNLIMITED length via recursive agent spawning - **Progressive File Assembly**: Section-by-section generation with quality safeguards - **Parallel Search Execution**: 5-10 concurrent searches + parallel agents - **Financial Citation Validation**: SEC filing verification, data accuracy checks - **McKinsey-Style HTML Reports**: Professional financial dashboards ## Installation The skill should be installed in `~/.claude/skills/financial-deep-research/` No additional dependencies required for basic usage. ## Usage ### In Claude Code Simply invoke the skill: ``` Use financial deep research to analyze Apple's investment thesis ``` Or specify a mode: ``` Use financial deep research in ultradeep mode for M&A due diligence on Nvidia ``` ### Example Queries **Company Analysis:** ``` Use financial deep research to evaluate Tesla's financial health and valuation ``` **Sector Analysis:** ``` Use financial deep research to analyze the fintech sector landscape 2024-2025 ``` **Competitive Analysis:** ``` Use financial deep research to compare cloud providers: AWS vs Azure vs GCP ``` **Due Diligence:** ``` Use financial deep research in deep mode for due diligence on Stripe pre-IPO ``` **Earnings Analysis:** ``` Use financial deep research to analyze Microsoft's Q3 2024 earnings and outlook ``` ## Research Modes | Mode | Phases | Duration | Best For | |------|--------|----------|----------| | **Quick** | 3 phases | 2-5 min | Market snapshot, earnings preview | | **Standard** | 6 phases | 5-10 min | Most financial analysis [DEFAULT] | | **Deep** | 8 phases | 10-20 min | Investment decisions, detailed analysis | | **UltraDeep** | 8+ phases | 20-45 min | M&A due diligence, comprehensive reports | ## Output Financial research reports are saved to organized folders in `/code/[Topic]_Financial_Research_[Date]/` Each report includes: - Executive Summary with Investment Thesis - Company/Topic Overview - Financi