longbridge-buffett-moat-stock-screener

Prompt-only Buffett-style screener. Given a market / sector / preference query (no specific ticker), applies Buffett's two-layer model — hard quantitative filter then qualitative moat scoring — and returns a ranked candidate list (3–5 cards) with moat-type tags, Buffett-attitude verdicts, and one-click jumps into

longbridge-buffett-moat-analyzer

for deep diagnostics. Every figure traces to a row in the mandatory Data Source Appendix at the end of the output.

Response language: detect the user's input language (Simplified Chinese / Traditional Chinese / English) and render the entire report — every card, label, narrative paragraph, education block, appendix row, and disclaimer — in that one language. Do not mix languages within a single output. The output template in
references/output.md
is shown in English for reference; translate it as a whole into the user's language using the label-translation lookup in that file. The error/source tables inside this SKILL.md remain 3-column because they document what the skill says under each language — that 3-column form is for the skill's reference docs, not for the user-facing report.

When to use

"帮我找几只巴菲特会买的股票" / "幫我找幾隻巴菲特會買的股票" / "find a few stocks Buffett would buy"
"消费股里巴菲特风格的有哪些" / "消費股裡巴菲特風格的有哪些" / "which consumer names are Buffett-style"
"我想找一只 10 年都不用动的股票" / "我想找一隻 10 年都不用動的股票" / "I want a 10-year-hold stock"
"有没有类似茅台这种定价权强的公司" / "有沒有類似茅台這種定價權強的公司" / "any companies like Moutai with strong pricing power"
"新能源里有没有符合巴菲特标准的" / "新能源裡有沒有符合巴菲特標準的" / "any new-energy names that meet Buffett's criteria"
"ROE 连续 10 年超过 20%、PE 低于 25 的 A 股" / "ROE 連續 10 年超過 20%、PE 低於 25 的 A 股" / "A-shares with 10y ROE > 20% and PE < 25"
"美股里巴菲特真实持仓过的股票" / "美股裡巴菲特真實持倉過的股票" / "US stocks Buffett has actually held"

For single-stock deep diagnostic on a name the user already picked, use

longbridge-buffett-moat-analyzer

. For Graham-style cigar-butt / NCAV screening, use

longbridge-graham-screener

. For broader low-PE / low-PB / high-ROE value (not moat-centric) use

longbridge-value-screen

. For high-dividend screens use

longbridge-dividend-screen

Cognitive frame (do not skip)

Screening is the upstream entry to the Buffett workflow: this skill generates candidates from zero; the downstream

longbridge-buffett-moat-analyzer

verifies a single name in depth. Both share the same moat lens — only the interaction shape differs.

Two principles must surface alongside every leaderboard:

Holding-period expectation — Buffett's reference is "ideally forever, at minimum 3 years." If the user's capital horizon is < 3 years, warn that this framework is the wrong lens regardless of how clean the screen looks.
Quality first, price second — "A great business at a fair price is far better than a fair business at a great price." A passing row tells the user the business is Buffett-grade; whether this price is sane is a Dimension-4 (valuation) check that may downgrade the verdict to "watch and wait for a better price". Never collapse quality and price into one number.

Failure modes the screener must flag honestly:

"Great business, wait for price" → quality passes but valuation 偏贵 / 高估 → 🟡 watchlist with target-price band, not a buy.
"Cheap but no moat" → low PE/PB but moat narrow or absent → not a Buffett candidate; redirect to
```
longbridge-graham-screener
```
/
```
longbridge-graham-stock-analysis
```
.
Sector-disqualified industries (e.g. airlines — Buffett publicly called the industry "value-destroying") → return an honest empty result with redirect to a closer-to-Buffett sector, not a forced top-N.

Workflow

Clarify the query in at most one quick turn. Three input shapes are supported (see §3.2 of the design doc):
- Preference-based (most common): "find me consumer stocks worth long-term holding".
- Sector / theme-based: "Buffett-style names in new energy" / "Buffett's actual US holdings".
- Condition-based (advanced): "A-shares with 10y ROE > 20% and PE < 25". If the user just says "recommend stocks" with no constraint, ask 1–2 framing questions (preferred market: A / HK / US? prefer steady — consumer/healthcare/financials — or growth — tech/new-energy?) before screening.
Resolve the universe:
- Sector / theme query → start from the index or sector universe via
```
longbridge constituent <INDEX>
```
  or
```
longbridge sector-screener
```
  candidate list.
- Preference / condition query without a stated market → default to the market the user most often references (A-share if Mandarin / Cantonese trader signal, US for English, HK if the user mentioned 港股). Echo the chosen universe back in the Market Summary.
- Cap batch size at 300 names per screen.
Sector triage — before any filter:
- Excluded (no scoring, drop with a one-line explanation in the Market Summary): airlines (Buffett: "value-destroying"), pre-revenue / pure-loss biotech (no track record), ST / 退市风险 names, listed < 5 years, pure-shell / negative-equity. If the user explicitly asked for one of these (e.g. "Buffett-style airline"), return an honest empty result with a redirect to the most-similar non-excluded sector (e.g. "consumer staples with pricing power" or "regulated utilities with stable returns").
- Sector-adjusted hard filter: banks / insurance / brokerage — replace FCF / leverage rules with ROA / NIM / NPL / CAR (note the substitution per row).
- Listed 5–10 years: pro-rate the earnings-stability sub-score and flag "history-limited" in the row note.
Fetch raw data via Longbridge CLI first (parallel, ≤20 symbols per wave). See §CLI. MCP fallback if
```
longbridge
```
is missing (see §MCP fallback). WebSearch only for items genuinely outside Longbridge: industry outlook / disruption signals, brand-strength surveys, Buffett's own 13F holdings disclosure, qualitative management track record. Every WebSearch hit gets a publisher + URL + access-date row in the appendix.
Layer 1 — Hard quantitative filter (binary pass/fail). Symbols failing ≥ 2 filters drop out by default. See §Filters for the table; full thresholds in
```
references/criteria.md
```
.
Per-row reconciliation gate: if balance-sheet sum / current-assets sum / shares×price mismatches the reported total by >3%, drop the row from the leaderboard with a "数据异常" note in the data-anomaly footer. Do not silently smooth.
Layer 2 — Qualitative moat scoring on every name that passed Layer 1 plus reconciliation. Five-dimension weighted composite (0–100):
- Moat type & width (35%) · Capital allocation (20%) · Earnings predictability (20%) · Valuation reasonableness (15%) · Long-term industry runway (10%). Full rubric in
```
references/criteria.md
```
  . Each dimension also gets a 1–5 star rating shown on the candidate card.
Verdict matrix — combine Layer 2 quality stars (moat + financials) with valuation tier. See
```
references/criteria.md
```
§Verdict matrix. Maps to one of three card verdicts:
- 🟢 大概率会买 / Likely buy — wide moat + clean financials + price 充足/一般.
- 🟡 可能会考虑 / Maybe — wait for price — wide moat + clean financials + price 偏贵.
- 🔴 目前估值不合适 / Not at this price — wide moat but price 高估, OR moat narrow at any price (redirect to Graham).
Holding-period mapping — derive expected min hold from moat width (★★★★★ → 5y+, ★★★★ → 3–5y, ★★★ → 1–3y, ★★ or below → not a Buffett candidate). See
```
references/criteria.md
```
.
Rank and emit 3–5 candidate cards (not a giant leaderboard — the design doc's deliberate cap). Follow the candidate-card template in
```
references/output.md
```
.
Mandatory closing blocks (every output, no exceptions):
- Selection rationale (2–3 sentences on why these names, current market caveat, deep-dive priority).
- Holding-period & user-education block (Buffett-style vs short-term expectations table — rendered in the user's language only).
- Data Source Appendix — every figure on every card traceable; every WebSearch row carries publisher + URL + date.
- Trilingual disclaimer from
```
references/output.md
```
  .
Deep-dive CTA on every card, rendered in the user's input language only (e.g. "Deep-dive → run
longbridge-buffett-moat-analyzer <CODE>
" for English, "深度诊断 → 运行
longbridge-buffett-moat-analyzer <CODE>
" for 简体, "深度診斷 → 執行
longbridge-buffett-moat-analyzer <CODE>
" for 繁體). Pick one.

CLI

Run

longbridge <subcommand> --help

to verify exact flags before each call — the CLI is the source of truth; do not hard-code flag spellings from memory.

bash

# Universe
longbridge constituent <INDEX>   --format json     # e.g. 000300.SH, HSI.HK, SPX.US

# Per-symbol snapshot (run in parallel, batches of ≤20)
longbridge calc-index   <SYMBOL> --format json     # PE / PB / market cap / ROE / dividend yield / sector tag
longbridge quote        <SYMBOL> --format json     # current price + suspended flag
longbridge basicinfo    <SYMBOL> --format json     # listing date / industry classification

# Per-symbol fundamentals (run in parallel)
longbridge financial-report <SYMBOL> --kind BS --report af --format json   # 5–10y annual — leverage, equity, debt ratio
longbridge financial-report <SYMBOL> --kind IS --report af --format json   # 5–10y annual — ROE, gross margin, earnings stability
longbridge financial-report <SYMBOL> --kind CF --report af --format json   # 5–10y annual — FCF = OCF − Capex
longbridge financial-report <SYMBOL> --kind BS --report qf --format json   # last 4Q — recent trajectory
longbridge financial-report <SYMBOL> --kind IS --report qf --format json
longbridge financial-report <SYMBOL> --kind CF --report qf --format json

# Long-window history for valuation-vs-history percentile (Layer 2 Dimension 4)
longbridge kline <SYMBOL> --period day --count 2500 --format json          # ~10 years

# Dividend & buyback (capital allocation track record — Layer 2 Dimension 2)
longbridge dividend  <SYMBOL> --format json
longbridge corporate <SYMBOL> --format json                                 # buyback / split / spin-off

# Ownership & insider flow (management alignment)
longbridge ownership   <SYMBOL> --format json
longbridge insresearch <SYMBOL> --format json

# Company profile (moat-type hypothesis seed)
longbridge company-profile <SYMBOL> --format json

# Peer set for moat / margin / ROE benchmarking
longbridge peer-comparison <SYMBOL> --format json

# Optional pre-narrowing if the user gave a sector / theme phrase
longbridge sector-screener --industry "<industry>" --format json

WebSearch fallback — only for items not available from Longbridge

Missing data	WebSearch query pattern
Industry runway / disruption risk	`"<industry> 2025 outlook"` , `"<industry> disruption risk"`
Brand / pricing-power signals	`"<company> price increase 2024 2025"` , `"<brand> brand value ranking"`
Buffett's actual disclosed holdings (for "13F" / "Berkshire holdings" queries)	`"Berkshire Hathaway 13F <year>"` , `"Warren Buffett portfolio holdings <year>"`
Management qualitative track record	`"<CEO name> capital allocation"` , `"<CEO name> shareholder letter"`
Regulatory / policy overhangs	`"<sector> regulation <region> 2025"`
Latest insider transactions if `ownership` is stale	`"<ticker> insider selling 2025"`

Every WebSearch-sourced figure must be tagged

[Source: WebSearch — <publisher>, <date>, <url>]

in the appendix; never silently mix it with Longbridge data.

Filters

User-overridable. Defaults from Buffett's publicly stated reference points. Threshold detail and the Layer-2 composite weights live in

references/criteria.md

Layer 1 — Hard quantitative filter (pass / fail gate)

Filter	Buffett threshold	Source field	Sector adjustment
ROE (5y avg)	≥ 15%	derived from `financial-report --kind IS` (NI) ÷ avg equity from BS	Banks: use ROA ≥ 1.0% + NIM stability
Debt-to-asset ratio	≤ 50%	BS — total liabilities ÷ total assets	Banks / insurance / brokers: substitute CAR / leverage-adjusted equity
Free cash flow	positive every year for last 3 years	`financial-report --kind CF` (OCF − Capex)	Banks: substitute operating-cash-flow proxy from interest income
Years listed	≥ 5 years	`basicinfo.listing_date`	None — strict, pro-rate at 5–10y window
Gross margin (TTM)	≥ 30%	`financial-report --kind IS` (gross profit ÷ revenue)	Heavy industry / utilities: relax to ≥ 20% with note

Symbols that fail ≥ 2 filters drop out by default; user can relax to "fail ≤ 3" on request. Any override is echoed back in the Market Summary.

Layer 2 — Qualitative moat scoring (weighted composite, 0–100)

Applied only to Layer-1 passers. Five dimensions, weights below. Full sub-criteria, evidence rules, and star mapping in

references/criteria.md

Dimension	Weight	Plain-language framing
Moat type & width	35%	Brand / network / cost / switching / regulatory / resource — wide / narrow / none
Capital allocation	20%	Dividend & buyback discipline, M&A track record, insider stake
Earnings predictability	20%	Earnings-volatility, cyclicality, revenue-mix stability
Valuation reasonableness	15%	PE / PB / dividend-yield percentile vs 10y history, simplified DCF concept band
Long-term industry runway	10%	Industry ceiling, disruption, regulatory exposure

Default rank key = Layer-2 composite (high to low). User can override to: moat-stars-only, ROE desc, valuation-tier (cheapest first), or "Berkshire holdings only".

Special handling

Cohort	Treatment
Airlines	Excluded — Buffett publicly called the industry "value-destroying". If the user explicitly asked for "Buffett-style airline", return an honest empty result and redirect to the nearest non-excluded sector (e.g. regulated utilities, consumer staples) with one-line rationale.
Pre-revenue / pure-loss biotech / hot-IPO concept names	Excluded — Buffett framework needs a track record. Redirect to `longbridge-fundamental` for an early-stage view.
ST / 退市风险 / listed < 5 years	Excluded from default top-N; show on request with the row prepended ⚠️ and a "history-limited" note.
Listed 5–10 years	Pro-rate earnings-stability sub-score on available years; mark row "history-limited".
Banks / insurance / brokers	Included with the sector-adjusted hard filter (ROA / NIM / NPL / CAR). Note substitution per row and in the Market Summary.
Reconciliation fail >3%	Drop from leaderboard; surface in "数据异常待复核" footer with the failing check named.
"最便宜的巴菲特风格股票" / "cheapest Buffett-style" query	Surface the distinction between cheap and margin of safety. Show Layer-2 valuation tier (充足 / 一般 / 偏贵 / 高估) prominently; rank by valuation tier inside the wide-moat cohort, not by raw PE.
"巴菲特真实持仓" / "Buffett's actual holdings" query	Pull Berkshire's latest 13F via WebSearch (publisher + URL + filing date in the appendix), then run Layer 2 on the holdings as a secondary lens — note that 13F lag (≥45 days) can be material.

Output

3–5 candidate cards, not a giant leaderboard. Full card template, selection rationale block, holding-period education table, and the mandatory Data Source Appendix structure live in

references/output.md

. Minimum card fields:

Name (Code) · Market · Sector              Quality stars: ★★★★★
Moat type: {brand / network / cost / switching / regulatory / resource}
Top-3 highlights (quantitative first): {ROE x%}, {Gross margin x%}, {FCF / capex intensity}
Buffett verdict: 🟢 大概率会买 / 🟡 可能会考虑 / 🔴 目前估值不合适
Valuation read: {充足 / 一般 / 偏贵 / 高估} — current price vs 10y band
Min. holding period: {5y+ / 3–5y / 1–3y}
[深度诊断这只股票 → longbridge-buffett-moat-analyzer <CODE>]

After the cards, every output must include:

Selection rationale — 2–3 sentences on (a) why these names together, (b) market caveats right now, (c) which one to deep-dive first.
Holding-period & user-education block — single-language table (in the user's input language) comparing Buffett-style expectations vs short-term/speculative expectations (holding time / entry pattern / drawdown tolerance / position logic / action frequency).
Data Source Appendix (MANDATORY) — every field on every card, every Longbridge endpoint hit, every WebSearch hit (publisher + URL + access date). The final line is a per-row reconciliation summary (clean pass / within-tolerance residuals / per-row drops).
Disclaimer — disclaimer variant matching the user's input language only, picked from
```
references/output.md
```
§Disclaimer variants. Never print multiple language variants.

Error handling

Situation	简体回复	繁體回覆	English reply
`command not found: longbridge`	回退到 MCP；若不可用，请安装 longbridge-terminal。	回退到 MCP；若不可用，請安裝 longbridge-terminal。	Fall back to MCP; if unavailable install longbridge-terminal.
stderr `not logged in` / `unauthorized`	请运行 `longbridge auth login` 。	請執行 `longbridge auth login` 。	Run `longbridge auth login` .
`constituent` / `sector-screener` returns empty	未能获取候选池，请确认指数或行业关键词。	未能獲取候選池，請確認指數或行業關鍵詞。	Cannot fetch universe; verify the index or sector keyword.
User-named sector is on the excluded list (e.g. 航空 / pre-revenue biotech)	该行业整体不符合巴菲特选股逻辑（已说明原因），推荐改看 {替代行业}；如仍想分析，可改用 `longbridge-fundamental` 。	該行業整體不符合巴菲特選股邏輯（已說明原因），推薦改看 {替代行業}；如仍想分析，可改用 `longbridge-fundamental` 。	The sector does not fit Buffett's framework (reason given); suggest {alternative sector}; for early-stage analysis use `longbridge-fundamental` .
BS / IS / CF partial fetch for a symbol	该标的数据不完整，跳过并在「数据异常」脚注列出。	該標的數據不完整，跳過並於「數據異常」腳註列出。	Symbol has incomplete fundamentals; skipped and listed in the data-anomaly footer.
Industry runway / qualitative data missing (Longbridge + WebSearch both empty)	维度评分仅用财务证据，标注「定性数据缺失」。	維度評分僅用財務證據，標註「定性數據缺失」。	Score the dimension on financial evidence only and tag "qualitative data unavailable".
Per-row reconciliation gap >3%	从候选卡片剔除并在「数据异常」附录列出失败项及差异。	自候選卡片剔除並於「數據異常」附錄列出失敗項及差異。	Drop from candidate cards; list failing check + gap in data-anomaly appendix.
User gave no market / preference at all	触发引导式提问：偏好市场（A/HK/美）？稳健（消费/医药/金融）还是有成长性（科技/新能源）？	觸發引導式提問：偏好市場（A/HK/美）？穩健（消費/醫藥/金融）還是有成長性（科技/新能源）？	Ask one framing turn: preferred market (A / HK / US)? Steady (consumer / healthcare / financials) or growthier (tech / new-energy)?
Other stderr	原样透传错误，不静默重试。	原樣透傳錯誤，不靜默重試。	Surface stderr verbatim; never silently retry.

MCP fallback

longbridge

CLI is not installed, use MCP tools (

claude mcp add --transport http longbridge https://openapi.longbridge.com/mcp

quote

scope):

MCP tool	CLI equivalent
`mcp__longbridge__constituent`	`longbridge constituent`
`mcp__longbridge__calc_indexes`	`longbridge calc-index`
`mcp__longbridge__quote`	`longbridge quote`
`mcp__longbridge__basicinfo`	`longbridge basicinfo`
`mcp__longbridge__financial_report`	`longbridge financial-report`
`mcp__longbridge__kline`	`longbridge kline`
`mcp__longbridge__dividend`	`longbridge dividend`
`mcp__longbridge__corporate`	`longbridge corporate`
`mcp__longbridge__ownership`	`longbridge ownership`
`mcp__longbridge__insresearch`	`longbridge insresearch`
`mcp__longbridge__company_profile`	`longbridge company-profile`
`mcp__longbridge__peer_comparison`	`longbridge peer-comparison`
`mcp__longbridge__sector_screener`	`longbridge sector-screener`

Related skills

Single-stock Buffett deep diagnostic →
```
longbridge-buffett-moat-analyzer
```
(the natural next step from every card)
Graham cigar-butt screener →
```
longbridge-graham-screener
```
Graham single-stock view →
```
longbridge-graham-stock-analysis
```
Broader value (PE / PB / ROE) screen →
```
longbridge-value-screen
```
High-dividend screen →
```
longbridge-dividend-screen
```
DCF intrinsic value →
```
longbridge-dcf
```
Industry runway / sector view →
```
longbridge-industry-overview
```
Method selection guide →
```
longbridge-valuation-methodology
```

File layout

longbridge-buffett-moat-stock-screener/
├── SKILL.md
└── references/
    ├── criteria.md   # Layer-1 hard filters, Layer-2 weighted scoring, verdict matrix, holding-period mapping, excluded cohorts
    └── output.md     # candidate-card template, selection rationale, user-education block, data-source appendix, disclaimer

longbridge-buffett-moat-stock-screener

NPX Install

Tags

SKILL.md Content

longbridge-buffett-moat-stock-screener

When to use

Cognitive frame (do not skip)

Workflow

CLI

WebSearch fallback — only for items not available from Longbridge

Filters

Layer 1 — Hard quantitative filter (pass / fail gate)

Layer 2 — Qualitative moat scoring (weighted composite, 0–100)

Special handling

Output

Error handling

MCP fallback

Related skills

File layout