Elite analyst methodology and frameworks, coded into a SKILL

Alpha Insights is a professional business analysis AI assistant for Claude Code compatible runtimes and Codex Desktop. It produces in-depth, decision-ready research reports — the kind a senior analyst would deliver.
Alpha Insights enforces the research workflow with runtime checks, not only instructions:
html_write_guard prevents premature report writing before required artifacts are ready.resume_check catches broken or inconsistent run state before continuing.Why Alpha Insights?
| Typical AI Analysis | Alpha Insights |
|---|---|
| Generic, surface-level | Framework-driven — 19 professional analysis frameworks |
| No source tracing | Evidence chain — every conclusion tagged with source & confidence |
| Single data source | Multi-track parallel search with triangulation |
| One-shot output | Interactive iteration — progressively deeper insights |
| Skips steps silently | Harness-enforced — script-based gates, not just prompt instructions |
View Demo Report (HTML) — A competitive analysis of China’s EV charging industry. Compact public demo with executive summary, Porter’s Five Forces, competitive positioning charts, evidence-graded findings, and strategic recommendations — generated in one session. It is a Tier 2 topic-brief sample, not a full Tier 3 deep report.
Read the V4.1 launch note — Why Alpha Insights treats serious AI research as a harness-enforced workflow, not another prompt pack.
Core Value:
Prompt instructions are probabilistic — AI tends to skip steps as context fills up. V4 invests in the execution environment instead of just prompts:
| MECE | Issue Tree | Hypothesis-Driven | Pyramid Principle | Triangulation | Pre-Mortem | First Principles | ACH (Analysis of Competing Hypotheses) | Expert Interview |
Original:
Classic:
| Scenario | Coverage |
|---|---|
| 🎯 Industry Research | Market size, growth drivers, value chain, key players |
| ⚔️ Competitive Analysis | Landscape, rival strategies, differentiation, response |
| 📱 Product Analysis | Features, UX, comparison, positioning, iteration |
| 💼 Business Model | Model teardown, revenue logic, unit economics |
| 🔍 Opportunity Discovery | Value gaps, unmet needs, emerging trends |
| 🌍 Market Entry | New market feasibility, entry path, go-to-market |
| 💰 Investment Decision | Due diligence, valuation, investment thesis |
| 📈 Strategic Planning | Annual/3-year plan, goals, roadmap |
| 🔒 Due Diligence | Risk review, compliance, background check |
| ❓ Ad-hoc Advisory | Policy impact, trend analysis, event assessment |
Recommended — ask your AI coding agent:
Install Alpha Insights from this repository. Follow INSTALL_FOR_AGENTS.md exactly.
Codex Desktop direct install:
git clone https://github.com/Ericyoung-183/alpha-insights.git
cd alpha-insights
python3 scripts/install_codex.py --verify
Claude Code compatible install:
Install this repository as the alpha-insights skill package. For the standard
Claude Code skill directory:
git clone https://github.com/Ericyoung-183/alpha-insights.git
mkdir -p ~/.claude/skills
rm -rf ~/.claude/skills/alpha-insights
cp -R alpha-insights ~/.claude/skills/alpha-insights
python3 ~/.claude/skills/alpha-insights/scripts/verify_cloudcode.py --skill-root ~/.claude/skills/alpha-insights
Keep the root SKILL.md frontmatter hooks intact. If your runtime uses a
different skill root, copy the same package directory there and run the verifier
with that path.
After installation, ask a business analysis question:
User: Analyze the competitive landscape of the EV charging industry in China
Alpha Insights will automatically:
| Source | Description | How |
|---|---|---|
| Public channels | Industry reports, analyst research, filings, news, policy docs | Search engine + web scraping |
| Expert interviews | Custom interview guides, recording templates, analysis guidance | Built-in methodology |
| Source | Description | Required Setup |
|---|---|---|
| Xiaohongshu (RedNote) | Consumer sentiment, product feedback, trend signals | Public web search or a separately installed private adapter; the GitHub package does not bundle provider-specific collection scripts |
| Knowledge base | Historical reports, industry notes | Knowledge-base CLI, Notion connector, or another available knowledge-base tool |
| Internal data | Business metrics, user behavior | Available database or data warehouse tool |
Unconfigured data sources are automatically skipped — core functionality is not affected.
SQL examples in SKILL files use {project}.{table_name} placeholders. Once you configure a database or data-processing tool, the AI will discover available tables through the current environment’s table search/query capability — no manual replacement needed.
alpha-insights/
├── SKILL.md # Main file (workflow orchestration, V4.1.4)
├── INSTALL_FOR_AGENTS.md # Agent-first installation contract
├── CHANGELOG.md # Version history
├── README.md # This file
├── frameworks/ # 19 analysis frameworks
│ ├── _index.md # Framework routing table
│ ├── 3a_8steps_strategy.md
│ ├── porters_five_forces.md
│ └── ...
├── methodology/ # 9 methodologies
│ ├── mece.md
│ ├── hypothesis_driven.md
│ └── ...
├── resources/ # Execution resources (Stage 3-5 input)
│ ├── data_sources.md
│ ├── research_engine.md
│ ├── judgment_rules.md
│ ├── quality_review.md # Independent Quality Review (IQR)
│ └── anti_patterns.md
├── references/ # Report standards (Stage 6-7 output)
│ ├── report_standards.md
│ └── report_template.html
└── scripts/
├── install_codex.py # Codex Desktop installer
├── verify_codex.py # Codex Desktop verifier
├── verify_cloudcode.py # Claude Code compatible verifier
├── report_helper.py # ReportBuilder for HTML generation
├── codex_hooks/ # Codex hook wrappers
├── harness/ # V4 Harness Engineering
│ ├── state_manager.py
│ ├── stage_gate.py
│ ├── dashboard.py
│ ├── resume_check.py
│ ├── validators/ # 7-stage + Stage 3.5 gate validators
│ └── hooks/ # automation hooks
Reports generated by Alpha Insights follow this structure:
📊 Research Report
├── Executive Summary (1 page)
├── Key Findings (3-5)
├── Detailed Analysis
│ ├── Industry Overview
│ ├── Competitive Landscape
│ ├── Key Player Profiles
│ └── Opportunities & Risks
├── Strategic Recommendations
└── Appendix
├── Source List (A/B/C/D graded)
└── Evidence Base
Data Quality Grading:
| Grade | Standard | Confidence |
|---|---|---|
| A | 3+ independent sources cross-validated | ✅ High |
| B | 2 sources cross-validated | ⚠️ Moderate |
| C | Single authoritative source | ⚠️ Suggest further validation |
| D | Single source, questionable reliability | ❌ Reference only |
Contributions welcome!
git checkout -b feature/amazing-feature)git commit -m 'Add amazing feature')git push origin feature/amazing-feature)Areas to contribute:
MIT License
Classic frameworks by:
Author: Eric Young Original framework: ★ 3A-8 Steps Strategy Core philosophy: Encode methodology into code