# 游资 (UZI) Skills
*"51 legendary investors review your stock picks — Buffett and a Chinese day-trader finally sit at the same table."*
[](LICENSE)
[](https://python.org)
[](https://claude.com/product/claude-code)
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[](skills/deep-analysis/scripts/lib/self_review.py)
**A-share / HK / US deep-analysis engine — with first-class Chinese-market coverage Western terminals don't touch. v3.4.4: data-quality banner UX (ETF "17% coverage" no longer reads as data failure · WCAG-compliant contrast on orange) · v3.4.3: open-end mutual fund classification + field-level basic fallback · v3.4.2: Windows + Clash Schannel TLS compat · v3.4.1: verdict granularity refinement. 397 pytest pass.**
[Install](#install) · [Usage](#usage) · [Why Western Investors Should Care](#-why-western-investors-should-care) · [Jury Panel](#-51-investor-jury) · [Methods](#-17-institutional-methods) · [Self-Review Gate 🆕](#-mechanical-self-review-gate-new-in-v29) · [Screenshots](#-what-the-report-looks-like) · [FAQ](#-faq)
**English** | [中文](README.md)
---
## 🌏 Why Western Investors Should Care
If you've ever tried to research a Chinese A-share from outside China, you know the pain:
- Bloomberg covers HK and ADRs, but A-share data is thin and the context is missing.
- Reuters / FT give you macro headlines, not per-company fundamentals.
- Anthropic's [financial-services-plugins](https://github.com/anthropics/financial-services-plugins) ships great institutional models (DCF / LBO / Comps) — **US-only**, and gated behind paid FactSet / S&P feeds.
- You end up copy-pasting from Eastmoney through Google Translate, and by the time you've built a DCF in Excel, the name's already moved 8%.
**This plugin fixes the Chinese half of that problem.** It reads A-share / H-share / US markets with the same interface, speaks to 20+ free Chinese data sources (akshare / Eastmoney / XueQiu / CNInfo / HKEXNews / mx妙想 API), and hands Claude enough context to actually reason about a Chinese company — not just translate its ticker.
It's also why this exists: **if legends get Chinese stocks wrong, ordinary investors need every analytical advantage they can get.** Charlie Munger famously loaded up on Alibaba (BABA) through Daily Journal Corp in 2021, then had to cut the position in half in 2022 after a ~70% drawdown. At the 2022 DJCO meeting, [Munger called it "one of the worst mistakes I ever made"](https://www.cnbc.com/2023/02/15/charlie-munger-says-he-regrets-alibaba-investment-one-of-the-worst-mistakes.html) — an estimated nine-figure hit. Even one of the greatest investors of all time underestimated how differently the Chinese regulatory and competitive landscape behaves.
So yes — this plugin helps you understand Chinese names like **Alibaba** (`BABA` / `09988.HK`), **Tencent** (`00700.HK`), **Kweichow Moutai** (`600519.SH`), **CATL** (`300750.SZ`), **BYD** (`002594.SZ`), **Pop Mart** (`09992.HK`), **Pinduoduo** (`PDD`) — the same names that keep showing up in Western portfolios and keep surprising their owners 😉
---
## What It Does
One sentence: give it a ticker, Claude becomes your analyst — pulls **22 dimensions of data**, runs **17 Wall-Street analysis models**, has **52 investors with distinct methodologies** score the stock, and produces a 600 KB Bloomberg-style HTML report.
```
/stock-deep-analyzer:analyze-stock 600519 # Kweichow Moutai (A-share)
/stock-deep-analyzer:analyze-stock 00700.HK # Tencent (HK)
/stock-deep-analyzer:analyze-stock BABA # Alibaba ADR
/stock-deep-analyzer:analyze-stock AAPL # Apple
```
After 5-8 minutes you get:
- **A self-contained HTML report** — opens in any browser, works offline
- **A portrait share card** (1080×1920) for social media
- **A landscape war-report card** (1920×1080)
- **A one-line summary** for chat / Slack / Telegram
---
## 💬 Test Group & Feedback
This is early-stage; forum reports plenty of bugs. If you want to help test or just trade notes, WeChat group QR below (primarily Chinese-speaking — if you prefer English, file issues on GitHub and we'll reply). For the latest features, track the `develop` branch.
---
## Install
No matter which agent you use, **one line does it**:
### Claude Code
```
/plugin marketplace add wbh604/UZI-Skill
/plugin install stock-deep-analyzer@uzi-skill
```
Then say `/stock-deep-analyzer:analyze-stock Tencent` or `/stock-deep-analyzer:analyze-stock 00700.HK`.
> ⚠️ **Always use the `stock-deep-analyzer:` namespace prefix**
>
> After install, all skills/commands live under `stock-deep-analyzer:`. Short names (`/analyze-stock`) don't always resolve in every environment — to be safe, always use the full name:
> - `/stock-deep-analyzer:analyze-stock `
> - `/stock-deep-analyzer:quick-scan `
> - `/stock-deep-analyzer:scan-trap `
> - `/stock-deep-analyzer:dcf ` / `:ic-memo` / `:investor-panel` / `:trap-detector` / ...
>
> Cursor / Gemini CLI / Codex behave the same way — use the full prefixed name.
### Codex
Just tell Codex:
> Please follow https://raw.githubusercontent.com/wbh604/UZI-Skill/main/.codex/INSTALL.md to install UZI-Skill, then deep-analyze Alibaba (BABA).
### OpenClaw / 龙虾
> Install https://github.com/wbh604/UZI-Skill and analyze Tencent (00700.HK) for me.
### Cursor
```
/add-plugin stock-deep-analyzer
```
Then say "analyze BABA".
### Gemini CLI
```bash
gemini extensions install https://github.com/wbh604/UZI-Skill
```
### OpenCode
> Follow https://raw.githubusercontent.com/wbh604/UZI-Skill/main/.opencode/INSTALL.md and analyze Pop Mart (09992.HK).
### Windsurf / Devin / Any Other Agent
Paste this:
> Clone https://github.com/wbh604/UZI-Skill, read `AGENTS.md`, then deep-analyze Alibaba (09988.HK).
### CLI Only
```bash
git clone https://github.com/wbh604/UZI-Skill.git
cd UZI-Skill && pip install -r requirements.txt
python skills/deep-analysis/scripts/run_real_test.py BABA
```
### 📱 Not at your desk?
Tell any agent:
> Analyze 00700.HK in remote mode — generate a public link so I can view it on my phone.
The agent spins up a Cloudflare Tunnel and gives you a `https://xxx.trycloudflare.com` URL.
---
## Usage
### Full deep analysis (5-8 minutes)
```
/stock-deep-analyzer:analyze-stock 600519 # A-share by ticker
/stock-deep-analyzer:analyze-stock 00700.HK # HK
/stock-deep-analyzer:analyze-stock BABA # US ADR
/stock-deep-analyzer:analyze-stock AAPL # US
```
> **Ticker format tips for English users:**
> - A-share: 6-digit + `.SH` (Shanghai) or `.SZ` (Shenzhen) — e.g. `600519.SH`, `002594.SZ`. Bare 6-digit like `600519` also works.
> - HK: 5-digit + `.HK` — e.g. `00700.HK`, `09988.HK`.
> - US: plain symbol — `AAPL`, `BABA`, `PDD`, `NVDA`.
> - Chinese names also resolve: `贵州茅台`, `腾讯控股`. For English input, prefer ticker codes over company names (name-resolution is tuned for Chinese).
### Single-purpose commands
> All commands require the `/stock-deep-analyzer:` prefix for reliable dispatch across environments.
| Command | What It Does |
|---|---|
| `/stock-deep-analyzer:dcf 600519` | DCF valuation · WACC + 5×5 sensitivity table |
| `/stock-deep-analyzer:comps 002273` | Peer comparison · PE / PB percentile ranking |
| `/stock-deep-analyzer:lbo 600519` | LBO stress test · PE-buyer IRR perspective |
| `/stock-deep-analyzer:initiate BABA` | Initiating-coverage report · JPM / GS format |
| `/stock-deep-analyzer:ic-memo BABA` | Investment-committee memo · 3-scenario returns |
| `/stock-deep-analyzer:earnings AAPL` | Earnings beat/miss analysis |
| `/stock-deep-analyzer:catalysts 300750` | Catalyst calendar · next 60 days |
| `/stock-deep-analyzer:thesis 600519` | Investment-thesis tracker · 5 pillars |
| `/stock-deep-analyzer:screen AAPL` | 5 quant screens · value / growth / quality / GARP / short |
| `/stock-deep-analyzer:dd BABA` | Due-diligence checklist · 21 items across 5 workstreams |
| `/stock-deep-analyzer:quick-scan 00700.HK` | 30-second sanity check |
| `/stock-deep-analyzer:panel-only 600519` | Just run the 51-investor jury — no HTML report |
| `/stock-deep-analyzer:scan-trap 600519` | Pump-and-dump / trap detection (8 signals) |
| `/stock-deep-analyzer:segmental-model 300308` | 🆕 Bottom-up segmental revenue model · 3-scenario × 3-year projection · cross-checks top-down DCF |
---
## 🎚️ Three Analysis Depths (new in v2.10.3)
Let users pick how much thinking they want — quick / standard / deep-dive:
```bash
python run.py 600519 --depth lite # ⚡ Quick read (1-2 min)
python run.py 600519 # 📊 Standard (5-8 min) · default
python run.py 600519 --depth deep # 🔬 Institutional (15-20 min)
```
Or via env var:
```bash
export UZI_DEPTH=lite # or medium / deep
python run.py 600519
```
### Differences
| Aspect | ⚡ **lite** | 📊 **medium** | 🔬 **deep** |
|---|---|---|---|
| **Runtime** | 1-2 min | 5-8 min | 15-20 min |
| **Fetchers** | Core 7 dims | All 22 dims | All 22 + reinforced fallback |
| **Investors** | 10 representatives | 51 full panel | 51 + **Bull-Bear structured debate** |
| **Institutional methods** | DCF only | All 17 | All 17 + **Segmental Build-Up** |
| **ddgs qualitative queries** | **all skipped** (saves tokens) | on-demand · budget 30 | full throttle · budget 60 |
| **fund_holders** | Top 5 with full 5Y stats | Top 20 full + rest as listing | Top 100 full |
| **Self-review gate** | critical blocks | critical blocks · warning ack-able | both block |
| **Token cost (Codex)** | minimal | moderate | maximum |
| **Use case** | Quick glance · boss just asked · preview ETF holdings | Daily deep analysis · writing research | Investment committee memo · pre-position deep dive |
### Auto-downgrade
- **First install** / empty `.cache/_global` → auto-switches to lite (saves cold-start time)
- **Network preflight 3+ domains unreachable** → auto lite (prevents hanging)
- Manual `--depth` always overrides auto-detection
### Picking the right depth
| Question | Recommended |
|---|---|
| "Can I buy this stock?" | `medium` (default) |
| "Give me a verdict in 15 minutes" | `lite` |
| "Prepping for investment committee tomorrow" | `deep` (includes Bull-Bear debate + bottom-up segmental) |
| "I typed an ETF code — system asked me to pick a holding" | `lite` (quick verdict on component) |
| "Codex environment / first install" | Don't worry — auto lite |
### Implicit depth per command
| Command | Implicit depth |
|---|---|
| `/stock-deep-analyzer:quick-scan 600519` | lite |
| `/stock-deep-analyzer:panel-only 600519` | lite |
| `/stock-deep-analyzer:analyze-stock 600519` | medium (default) |
| `/stock-deep-analyzer:ic-memo 600519` | deep |
| `/stock-deep-analyzer:initiate 600519` | deep |
---
## 🎭 51 Investor Jury
Not template phrases. Each investor has their own **quantified rule set** (180 rules total) + their own **real quoted voice** + their own **authentic decision profile** (time horizon / position sizing / what-would-change-my-mind).
| Group | Style | Count | Representatives |
|---|---|---|---|
| A | Classic Value | 6 | Buffett · Graham · Munger · Fisher · Templeton · Klarman |
| B | Growth | 4 | Lynch · O'Neil · Thiel · Cathie Wood |
| C | Macro / Hedge | 5 | Soros · Dalio · Howard Marks · Druckenmiller · Julian Robertson |
| D | Technical | 4 | Livermore · Minervini · Darvas · Gann |
| E | China Value | 6 | Duan Yongping (段永平) · Zhang Kun · Zhu Shaoxing · Xie Zhiyu · Feng Liu · Deng Xiaofeng |
| F | A-Share Day Traders (游资) | 23 | Zhang Mengzhu · Zhao Laoge · Foshan Shadowless Kick · Beijing Trader · Xin Duoduo … |
| G | Quant | 3 | Simons · Thorp · David Shaw |
**Every verdict cites the specific rule it hit.** And each investor answers three questions in their own voice:
| Investor | Time Horizon | What Would Change My Mind |
|---|---|---|
| Buffett | 10+ years / forever | ROE below 12% for 2 consecutive years · CEO change + strategic pivot |
| Zhao Laoge (赵老哥) | T+2 to T+5 | Leader breaks the limit-up · volume doesn't confirm |
| Simons | Avg holding < 2 days | Signal Sharpe drops below 0.5 · factor decay |
| Lynch | Until the story plays out, typically 3-5 years | PEG > 2 · inventory growing faster than revenue |
| Soros | One reflexivity cycle, weeks to months, flip anytime | Market stops validating my narrative |
Their quotes are sourced from **real public materials** — Berkshire annual letters, Oaktree memos, *Principles*, *Margin of Safety*, Lost Tree Club speeches, XueQiu / Zhihu columns — each citation links to the original source.
---
## 📐 17 Institutional Methods
Ported from [anthropics/financial-services-plugins](https://github.com/anthropics/financial-services-plugins), adapted with A-share / H-share parameters.
**Valuation (6)**: DCF · Comps · 3-Statement · LBO · Merger Model · Unit Economics
**Research (7)**: Initiating Coverage · Earnings Analysis · Catalyst Calendar · Thesis Tracker · Morning Note · Quant Screen · Sector Overview
**Decision (6)**: IC Memo · Porter 5 Forces + BCG · DD Checklist · Value Creation Plan · Portfolio Rebalance · Trap Detection (unique to this plugin)
---
## 📸 What The Report Looks Like
> All screenshots from a real analysis of Crystal Optech (002273.SZ).
### Score dashboard
### The Great Divide — Bull vs Bear
### 51 Jury Seats
### Chat-room mode
### DCF Sensitivity Heatmap
### IC Memo — 3 Scenarios
### 22-Dimension Deep Cards
### Social Share Card
---
## 🔓 Login-Required Data Sources (optional)
Some sources need login to avoid being sampled out. **All are opt-in** — defaults work without any login, just with limited data.
| Source | What It Unlocks | How to Enable |
|---|---|---|
| **XueQiu** (`cubes_search`) | Dim 19 · real-money portfolios holding this stock + their returns | `export UZI_XQ_LOGIN=1 && python -m lib.xueqiu_browser login` (one-time browser prompt; cookies persisted to `~/.uzi-skill/playwright-xueqiu/`). Or use flag: `python run.py BABA --enable-xueqiu-login`. |
If you don't enable, the dim transparently reports `"⚠️ XueQiu login required, 0 cubes shown"` — no silent data holes.
---
## ❓ FAQ
**Q: How long does it take?**
A: 5-8 minutes per stock. Most time is data fetching. Modeling itself is <1 second.
**Q: Do I need paid data sources?**
A: No. All free (akshare / yfinance / DuckDuckGo / CNInfo / HKEXNews / Eastmoney / XueQiu backend). Zero API keys required. Optional `MX_APIKEY` (mx妙想 API) for enhanced A-share indicators — it's free too.
**Q: Does it work for US / HK stocks?**
A: Yes. `/stock-deep-analyzer:analyze-stock AAPL`, `/stock-deep-analyzer:analyze-stock BABA`, `/stock-deep-analyzer:analyze-stock 00700.HK`. HK now has 4-layer kline fallback (Eastmoney → Sina → yfinance → Yahoo Chart v8) since v2.13.7.
**Q: Can I use English company names?**
A: Best: use ticker codes (`BABA` / `00700.HK` / `600519.SH`). Name-resolution works for Chinese names (`贵州茅台` → `600519.SH`); for English names prefer the ticker.
**Q: Does the 51-investor panel quote real investors?**
A: Yes. The `quotes-knowledge-base.md` contains real published quotes from 45+ investors (22 Western, 23 Chinese), each with source URLs (Berkshire letters, Oaktree memos, books, interviews). Agents are instructed to mimic each investor's voice **using these real quotes**, not fabricate a "Buffett-style" line.
**Q: Is this investment advice?**
A: **No.** This is a research tool, not a fortune teller. The 52 investor opinions are rule-engine simulations, not the real people's views. Don't bet the farm on Claude's Buffett impression.
**Q: I'm behind the Great Firewall, will data sources work?**
A: Most do. `akshare` / `yfinance` / Eastmoney / XueQiu all work from mainland China. Some Western sources (Bloomberg / Reuters) aren't used. DuckDuckGo web search occasionally rate-limits — see `docs/NETWORK-TROUBLESHOOTING.md` if the `3_macro` / `13_policy` / `15_events` dims report empty.
**Q: I'm outside China, will Chinese data sources work?**
A: Yes. akshare / Eastmoney / XueQiu / CNInfo / HKEXNews all serve international IPs. No VPN needed. The mx妙想 API (A-share indicators) requires the free `MX_APIKEY` env var.
**Q: How do I know the report I'm about to read is reliable?**
A: As of v2.9, self-review is **mechanically enforced**. 13 automated checks run before HTML generation; if any critical check fails, the report *physically cannot be shipped*. Check `.cache//_review_issues.json` for any warnings, each with a `suggested_fix`. Every time a new BUG is fixed, a matching check is added — so the same class of bug will be **auto-caught next run, no user feedback needed**.
**Q: Does the plugin auto-notify me about new versions?**
A: Yes, since v2.14.0. Every CLI run or agent session silently polls `api.github.com/.../releases/latest`; if a newer tag is out, you get a 3-option prompt (yes / skip-this-version / no) with the release notes summary. "Skip" suppresses the prompt only for that specific tag — once a newer version drops, you'll be asked again. Disable with `export UZI_NO_UPDATE_CHECK=1` (recommended for CI / Codex). Cached 6h to stay under GitHub's 60-req/h unauthenticated limit.
**Q: I ran analyses on earlier versions — were those reports correct?**
A: If you analyzed "industrial metals / machine tools / industrial machinery" stocks (like Yunnan Aluminum / 云铝股份 `000807.SZ`) before 2026-04-17, the `7_industry` dim was misclassified as "agricultural food processing" (BUG#R10). Clear the cache and re-run:
```bash
rm -rf skills/deep-analysis/scripts/.cache//raw_data.json
python run.py --no-resume
```
---
## 🛠 Architecture in One Diagram
> **v3.0–v3.2 pipeline refactor** (2026-04-23) · Two-file legacy monolith split into a pipeline architecture:
> - `run_real_test.py`: 2105 → 735 lines (-65%) · pure functions moved to `lib/pipeline/score_fns.py`
> - `assemble_report.py`: 2964 → 587 lines (-80%) · split into 5 `lib/report/*` submodules
> - `python run.py ` now defaults to `pipeline.run_pipeline` · `UZI_LEGACY=1` falls back
> - All v2.x public APIs preserved via `re-export` · 332 pytest pass · zero behavioral diff
> See [CODEX.md](CODEX.md) / [AGENTS.md](AGENTS.md) for v3.2 repo layout details.
```
user says "/analyze-stock BABA"
↓
┌──────────────────────────────────────────────┐
│ Task 1 · Stage1 — parallel data fetch │
│ 22 fetchers × 20+ sources │
│ (akshare / yfinance / DDG / mx / cninfo …) │
└──────────────────────────────────────────────┘
↓ raw_data.json
┌──────────────────────────────────────────────┐
│ Task 2 · Rule engine scoring │
│ 22 dims → dimensions.json │
│ 52 investors × 180 rules → panel.json │
└──────────────────────────────────────────────┘
↓ HARD-GATE (agent takes over)
┌──────────────────────────────────────────────┐
│ Task 3 · Agent analysis │
│ reads quotes-knowledge-base.md │
│ writes agent_analysis.json │
│ (dim_commentary · panel_insights · │
│ great_divide · narrative_override …) │
└──────────────────────────────────────────────┘
↓ stage2 merge
┌──────────────────────────────────────────────┐
│ Task 4 · Synthesis · style weighting │
│ 7+1 stock style × 7 investor-school matrix │
│ → synthesis.json │
└──────────────────────────────────────────────┘
↓
┌──────────────────────────────────────────────┐
│ 🛡 v2.9 · Mechanical self-review gate │
│ lib/self_review.py — 13 auto checks │
│ critical > 0 → RuntimeError (BLOCK HTML) │
│ agent must fix issues → re-review → pass │
└──────────────────────────────────────────────┘
↓ only when passed
┌──────────────────────────────────────────────┐
│ Task 5 · Report assembly │
│ → full-report.html (single file, offline) │
│ → share-card.png · war-report.png │
└──────────────────────────────────────────────┘
```
### 🛡 Mechanical Self-Review Gate (new in v2.9)
Previous versions had soft "HARD-GATE-FINAL-CHECK" — agents could skip, forget, or do half of it. BUG#R10 (a Chinese aluminum producer classified as "agricultural food processing") was caught only after reports were already sent to users. **Soft gates aren't enough — v2.9 enforces mechanically.**
`lib/self_review.py` runs **13 automated checks** before any HTML can be generated. Each check corresponds to a historical BUG:
| severity | check | catches |
|---|---|---|
| 🔴 critical | industry mapping sanity | BUG#R10 collision (工业金属 → 农副食品加工) |
| 🔴 critical | all dims present | wave2 timeout dropped `12_capital_flow` |
| 🔴 critical | HK kline has data | BUG#R8 Hong Kong kline no fallback |
| 🔴 critical | HK financials populated | BUG#R7 empty stub |
| 🔴 critical | panel non-empty, scores sane | panel engine glitches |
| 🔴 critical | coverage_pct ≥ 60% | data integrity floor |
| 🔴 critical | no "[PLACEHOLDER]" strings | template leak |
| 🔴 critical | agent_analysis.json exists & reviewed | agent skipped |
| 🟡 warning | DCF / Comps not all zero | valuation pipeline check |
| 🟡 warning | metal stocks have materials data | v2.8.x coverage gap |
| 🟡 warning | no fabricated narratives (e.g. "Apple supply chain" without evidence) | hallucination guard |
`assemble_report::assemble()` runs `review_all(ticker)` automatically. If `critical_count > 0`, it raises `RuntimeError` — **physically impossible to ship a bad report**. Agent must:
```
loop:
1. python review_stage_output.py
2. read .cache//_review_issues.json
3. for each critical: execute suggested_fix (backfill, refetch, override)
4. re-run review
5. only when critical_count == 0 → HTML generation proceeds
```
Every time a new BUG is fixed, a matching `check_*` rule is added to self_review. The same bug class will be **automatically caught on the next run, without needing user feedback.**
---
## ⭐ Star History
Live count: 
> Note: star-history.com caches server-side for 24h, so the chart may lag during fast-growth days. For the true current count, see the shields.io badge above — or click the chart to open the live star-history.com page (that triggers a backend refresh).
---
## ⚠️ Disclaimer
This tool generates analysis reports using AI models on public data. All scores, recommendations, and simulated commentary are algorithm outputs and do **not** represent any real investor's actual views (even if a quote is real, the scoring around it is simulated). **Not investment advice.** Past performance is not indicative of future results. Charlie Munger still lost money on Alibaba, and he actually read the 10-Q. Invest at your own risk.
---
## Thanks
[Linux.do](https://linux.do/) — "Linux.do is all you need to learn AI." Thanks for the testing community.
---
### The Great Divide — Bull vs Bear
### 51 Jury Seats
### Chat-room mode
### DCF Sensitivity Heatmap
### IC Memo — 3 Scenarios
### 22-Dimension Deep Cards
### Social Share Card
---
## 🔓 Login-Required Data Sources (optional)
Some sources need login to avoid being sampled out. **All are opt-in** — defaults work without any login, just with limited data.
| Source | What It Unlocks | How to Enable |
|---|---|---|
| **XueQiu** (`cubes_search`) | Dim 19 · real-money portfolios holding this stock + their returns | `export UZI_XQ_LOGIN=1 && python -m lib.xueqiu_browser login` (one-time browser prompt; cookies persisted to `~/.uzi-skill/playwright-xueqiu/`). Or use flag: `python run.py BABA --enable-xueqiu-login`. |
If you don't enable, the dim transparently reports `"⚠️ XueQiu login required, 0 cubes shown"` — no silent data holes.
---
## ❓ FAQ
**Q: How long does it take?**
A: 5-8 minutes per stock. Most time is data fetching. Modeling itself is <1 second.
**Q: Do I need paid data sources?**
A: No. All free (akshare / yfinance / DuckDuckGo / CNInfo / HKEXNews / Eastmoney / XueQiu backend). Zero API keys required. Optional `MX_APIKEY` (mx妙想 API) for enhanced A-share indicators — it's free too.
**Q: Does it work for US / HK stocks?**
A: Yes. `/stock-deep-analyzer:analyze-stock AAPL`, `/stock-deep-analyzer:analyze-stock BABA`, `/stock-deep-analyzer:analyze-stock 00700.HK`. HK now has 4-layer kline fallback (Eastmoney → Sina → yfinance → Yahoo Chart v8) since v2.13.7.
**Q: Can I use English company names?**
A: Best: use ticker codes (`BABA` / `00700.HK` / `600519.SH`). Name-resolution works for Chinese names (`贵州茅台` → `600519.SH`); for English names prefer the ticker.
**Q: Does the 51-investor panel quote real investors?**
A: Yes. The `quotes-knowledge-base.md` contains real published quotes from 45+ investors (22 Western, 23 Chinese), each with source URLs (Berkshire letters, Oaktree memos, books, interviews). Agents are instructed to mimic each investor's voice **using these real quotes**, not fabricate a "Buffett-style" line.
**Q: Is this investment advice?**
A: **No.** This is a research tool, not a fortune teller. The 52 investor opinions are rule-engine simulations, not the real people's views. Don't bet the farm on Claude's Buffett impression.
**Q: I'm behind the Great Firewall, will data sources work?**
A: Most do. `akshare` / `yfinance` / Eastmoney / XueQiu all work from mainland China. Some Western sources (Bloomberg / Reuters) aren't used. DuckDuckGo web search occasionally rate-limits — see `docs/NETWORK-TROUBLESHOOTING.md` if the `3_macro` / `13_policy` / `15_events` dims report empty.
**Q: I'm outside China, will Chinese data sources work?**
A: Yes. akshare / Eastmoney / XueQiu / CNInfo / HKEXNews all serve international IPs. No VPN needed. The mx妙想 API (A-share indicators) requires the free `MX_APIKEY` env var.
**Q: How do I know the report I'm about to read is reliable?**
A: As of v2.9, self-review is **mechanically enforced**. 13 automated checks run before HTML generation; if any critical check fails, the report *physically cannot be shipped*. Check `.cache/