From quant-skills
Generates institutional-grade investment research reports for A-shares, Hong Kong, and US stocks. Produces tear sheets (3-5 pages) or deep dives (≥25 pages) with financial models and DCF valuations.
How this skill is triggered — by the user, by Claude, or both
Slash command
/quant-skills:equity-researcherThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
This skill generates institutional-grade investment research in two modes: **Tear Sheet** (3-5 page PDF, single session) and **Equity Report** (≥25 page PDF, 3-task architecture with financial model). Both modes share the same analytical philosophy — the difference is depth, scope, and delivery structure.
SKILL-equity-task1.mdSKILL-task2-model.mdSKILL-task3-report.mdSKILL-tearsheet.mdanalysis/investment-logic.mdanalysis/projection-assumptions.mdanalysis/revenue-model.mdanalysis/risk-framework.mdanalysis/scenario-deep-dive.mdanalysis/six-dimension-analysis.mdmodules/company-overview.mdmodules/equity-report-charts.mdmodules/industry-chain.mdmodules/stock-chart.mdmodules/tables.mdmodules/valuation.mdoutput/report-layout.mdoutput/report-qa.mdoutput/report.cssoutput/tearsheet-layout.mdThis skill generates institutional-grade investment research in two modes: Tear Sheet (3-5 page PDF, single session) and Equity Report (≥25 page PDF, 3-task architecture with financial model). Both modes share the same analytical philosophy — the difference is depth, scope, and delivery structure.
Your first job: figure out what the user wants. Then carry the Core Principles into the next file.
Detect the user's language from their message. Use that language for ALL follow-up questions and the final report.
| User Language | report_language |
|---|---|
| Chinese (any) | zh |
| English | en |
| Mixed / unclear | Match the dominant language in user's message |
Not every company analysis request needs a full report. Before committing resources, determine what the user actually wants.
| Tier | User Signal Examples | Action |
|---|---|---|
| Tier A: Explicit report keyword | "tear sheet", "one pager", 投资速览, 投资简报, "research report", "deep dive", "equity report", 研报, 深度研究, 深度分析 | → Skip to Step 3 (output type is clear) |
| Tier B: Company analysis — ambiguous depth | "帮我分析一下[公司]", "analyze [company]", "帮我看看[股票]", "look into [stock]", "了解一下[公司]", "what do you think of [company]", 个股分析, 公司分析, or just a stock code (e.g. AAPL, 600519) | → Ask user (Step 2a) |
| Tier C: Simple question | "XX公司是做什么的", "what's [company]'s market cap", "when is [stock]'s next earnings" | → Do NOT trigger this skill. Answer conversationally. No report generation. |
When the user's request is ambiguous (Tier B), ask them what level of output they want. Do not assume they want a full report — that wastes their time and tokens.
Present 3 clear options (in the user's language):
Chinese example:
我可以用以下几种方式帮你分析 [公司名]:
- 投资速览 (Tear Sheet) — 3-5页专业机构级投资简报,包含估值、催化剂、产业链、情景分析等,适合快速决策参考
- 深度研究报告 (Equity Report) — ≥25页机构级深度研报,包含完整财务模型、DCF估值、敏感性分析等,适合深入研究
- 简单回答 — 不生成报告,直接用对话回答你的问题,最节省时间
你想要哪种?
English example:
I can analyze [company] at different levels of depth:
- Tear Sheet — A concise 3-5 page professional investment brief with valuation, catalysts, supply chain, and scenario analysis
- Full Equity Report — An in-depth ≥25 page institutional report with a complete financial model, DCF valuation, and sensitivity analysis
- Quick answer — No report generation, just a conversational response to your question
Which would you prefer?
If user chooses option 3: Answer their question conversationally. Do NOT proceed with this skill. End here.
| User Choice / Signal | Output Type | Variable |
|---|---|---|
| Tear Sheet / 投资速览 / option 1 | Tear Sheet | output_type = TEAR_SHEET |
| Equity Report / 深度研究 / option 2 | Equity Report | output_type = EQUITY_REPORT |
| Explicit "tear sheet", "one pager", 投资速览, 投资简报, 公司一页纸, "quick glance", "investment memo" | Tear Sheet | output_type = TEAR_SHEET |
| Explicit "research report", "full report", "deep dive", "equity report", 研报, 深度研究, 深度分析 | Equity Report | output_type = EQUITY_REPORT |
Once output_type is set, record it. This variable determines which mode-specific file to read next.
output_type = EQUITY_REPORT)When the user wants an equity report, ask one more question before starting analysis. The report can be built at two valuation depths — this significantly affects time and complexity.
Present the choice (in the user's language):
Chinese:
深度研报可以按两种估值深度生成:
- 完整版(含财务模型) — 构建完整的三表财务模型(利润表/资产负债表/现金流表)+ DCF绝对估值 + 可比公司估值 + 敏感性分析 + 历史估值带。适合需要深入研究、精确目标价的场景。大约需要 3 步完成。
- 精简版(Level 1 估值) — 基于可比公司估值(PE/PB/PS 倍数)+ 一致预期 + 情景分析,快速生成专业研报。无复杂 Excel 建模,速度更快。大约需要 2 步完成。
你选哪种?
English:
The equity report can be built at two valuation depths:
- Full version (with financial model) — Complete 3-statement financial model (IS/BS/CF) + DCF absolute valuation + comparable companies + sensitivity analysis + historical valuation band. Best for in-depth research with precise target price. Approximately 3 steps.
- Streamlined version (Level 1 valuation only) — Comparable company valuation (PE/PB/PS multiples) + consensus expectations + scenario analysis, generating a professional report without complex Excel modeling. Faster turnaround. Approximately 2 steps.
Which would you prefer?
Record the user's choice:
| User Choice | Valuation Depth | Variable | Task Architecture |
|---|---|---|---|
| Full version / 完整版 / option 1 | Level 2 (DCF + Comps + Sensitivity) | valuation_depth = L2 | 3 Tasks: Task 1 → Task 2 (Excel model) → Task 3 |
| Streamlined version / 精简版 / option 2 | Level 1 (Comps + Multiples only) | valuation_depth = L1 | 2 Tasks: Task 1 → Task 3 (L1 mode, no Task 2 Excel) |
Key difference:
If output_type = TEAR_SHEET: Skip this step entirely. Tear sheets always use Level 1.
These principles apply to BOTH modes. Read them now. They are NOT repeated in the mode-specific files. If you skip them, you will produce a bad report.
| Principle | Requirement |
|---|---|
| Data Authenticity | All data must have real sources; strictly prohibit fabrication. No placeholders, no "TBD". |
| Data Verification | Critical data cross-verified by 2+ independent sources |
| Timeliness | Must use latest financial reports and real-time market data |
| Recent News Weight | News within past 7 days affecting marginal expectations must be included |
| Authoritative Source Weight | Prioritize official sources and professional financial institutions |
| Source Attribution | All data attributed. API data labels original source |
| Deep Analysis | Mandatory six-dimension framework; each data point answers "so what" |
| Bull/Bear Balance | Both bullish and bearish viewpoints required — no one-sided analysis |
| Analysis First | Complete Phase 2-3 analysis, THEN Phase 4 begins layout — never skip ahead |
| Narrative Consistency | All modules develop around Phase 3 core narrative |
| Default Output | PDF format |
| File Read Confirmation | Must confirm required files read before each Phase (see Hard Gate Table in mode file) |
Prohibit fabricating data, eliminate scaffold/placeholders. See
references/data-sources.md§Data Missing Handling + quality checklist A6-A8.
| Output Type | Valuation Depth | Action |
|---|---|---|
TEAR_SHEET | L1 (fixed) | Read SKILL-tearsheet.md now. Complete single-session workflow. |
EQUITY_REPORT | L2 | Read SKILL-equity-task1.md now. Task 1 → Task 2 (Excel model) → Task 3. |
EQUITY_REPORT | L1 | Read SKILL-equity-task1.md now. Task 1 → Task 3 (no Task 2 Excel). |
Before starting Task 1: Tell the user the full flow and step count:
Chinese (L2):
我将为你生成深度研报(完整版),共 3 步:
- 第 1 步:深度研究分析(数据收集 + 六维分析 + 行业研究)→ 输出研究文档
- 第 2 步:财务建模与估值(Excel 三表模型 + DCF 估值 + 敏感性分析)
- 第 3 步:生成最终 PDF 研报(≥25页)
现在开始第 1 步。
English (L2):
I'll generate the full equity report in 3 steps:
- Step 1: Deep research analysis (data collection + six-dimension analysis + industry research) → Research Document
- Step 2: Financial modeling & valuation (Excel 3-statement model + DCF + sensitivity)
- Step 3: Generate final PDF report (≥25 pages)
Starting Step 1 now.
Chinese (L1):
我将为你生成深度研报(精简版),共 2 步:
- 第 1 步:深度研究分析(数据收集 + 六维分析 + 可比公司估值)→ 输出研究文档
- 第 2 步:生成最终 PDF 研报(≥25页,基于可比公司估值)
现在开始第 1 步。
English (L1):
I'll generate the streamlined equity report in 2 steps:
- Step 1: Deep research analysis (data collection + six-dimension analysis + comps-based valuation) → Research Document
- Step 2: Generate final PDF report (≥25 pages, comparable-company valuation)
Starting Step 1 now.
Stop sequential reading here. The mode-specific file you read next has all execution instructions you need. The REFERENCE SECTION below (Output Type Comparison, Task architecture, File Index, Common Rules) is a look-up resource — consult specific sub-sections when you need to locate a file or confirm a mode detail. Do not read it cover-to-cover.
You do not need to read this section sequentially. It is reference material for when you need to look up mode details, task architecture, or file locations. The mode-specific files will tell you which files to read and when.
| Dimension | Tear Sheet | Equity Report |
|---|---|---|
| Pages | 3-5 A4 | ≥25 A4 (25-40 pages) |
| Layout | Compact dual-box side-by-side | Full-width, flexible single/dual-column |
| Module Count | 11 fixed modules | 21 mandatory modules |
| Content Style | Condensed bullets, max info density | Fully developed paragraphs with data |
| Valuation Depth | Level 1 (comparable + multiples + consensus) | Level 2 (L1 + DCF + historical band + sensitivity + synthesis) |
| CSS | output/tearsheet.css | output/report.css |
| Target Audience | Quick reference for decision-makers | In-depth research for institutional investors |
| Phase 4 File | output/tearsheet-layout.md | output/report-layout.md |
| Phase 5 File | output/tearsheet-qa.md | output/report-qa.md |
A concise 3-5 page PDF produced entirely within one session.
Phase 0 → Phase 1 → Phase 2 → Phase 3 → Phase 4 → Phase 5 → PDF delivered
(Router) (Data) (Analysis) (Synthesis) (Layout) (QA)
SKILL-tearsheet.mdreferences/analysis-brief-template.mdoutput/tearsheet-layout.md → output/tearsheet.cssoutput/tearsheet-qa.mdAn in-depth ≥25 page PDF built across 2 or 3 Tasks depending on valuation depth. Both L1 and L2 share the same Task 1.
Task 1 (SKILL-equity-task1.md): Phase 0 → Phase 1 → Phase 2 → Phase 3 → Research Document (.md)
↓
Task 2 (SKILL-task2-model.md): Financial Model (.xlsx) + Valuation Analysis (.md)
↓
Task 3 (SKILL-task3-report.md): Final PDF Report (≥25 pages)
Task 1 (SKILL-equity-task1.md): Phase 0 → Phase 1 → Phase 2 → Phase 3 → Research Document (.md)
↓
Task 3 (SKILL-task3-report.md): Final PDF Report (≥25 pages, L1 mode)
| Task | Entry File | Input | Output | Acceptance Gate |
|---|---|---|---|---|
| Task 1 | SKILL-equity-task1.md | User request + stock code | Research Document (≥6,000 words) | 13 completeness + 4 data quality checks |
| Task 2 (L2 only) | SKILL-task2-model.md | Task 1 Research Document | Excel Model (8+ tabs) + Valuation Analysis | 10 model integrity checks |
| Task 3 | SKILL-task3-report.md | Task 1 doc (+ Task 2 Excel + Valuation for L2) | PDF equity report (≥25 pages) | ≥10 number cross-checks vs Excel (L2) / research doc cross-check (L1) |
All paths are relative to this skill's root directory.
| File | Mode / Task | Purpose |
|---|---|---|
SKILL.md | Router | Determines output type, routes to mode-specific file |
SKILL-tearsheet.md | Tear Sheet | Complete single-session workflow (Phase 0.1 → 5 → PDF) |
SKILL-equity-task1.md | Equity Report Task 1 | Research + Analysis → produces Research Document |
SKILL-task2-model.md | Equity Report Task 2 | Financial Model + Valuation → produces Excel model + Valuation Analysis |
SKILL-task3-report.md | Equity Report Task 3 | Report Generation → produces final PDF equity report |
| File | Content |
|---|---|
analysis/six-dimension-analysis.md | 六维分析 complete framework |
analysis/investment-logic.md | Investment logic + thesis table spec |
Moat classification, earnings-quality checks, management assessment, TAM/SAM/SOM, and competitive deep dive are all defined inline in the two handoff templates (
references/research-document-template.mdfor equity reports,references/analysis-brief-template.mdfor tear sheets). No separate per-framework files.
| File | Content |
|---|---|
analysis/revenue-model.md | Segment-level revenue decomposition, volume × price buildup |
analysis/projection-assumptions.md | Margin bridge, CapEx/WC, assumption sensitivity tags |
analysis/scenario-deep-dive.md | Quantified Bull/Base/Bear with probability weighting |
analysis/risk-framework.md | 8-12 categorized risks with probability × impact scoring |
| File | Level | Content |
|---|---|---|
valuation/comparable.md | L1 (both) | Comparable companies + metric selection |
valuation/dcf-and-sensitivity.md | L2 only | DCF methodology + historical valuation band + sensitivity matrix (single consolidated reference) |
| File | Content |
|---|---|
modules/stock-chart.md | 52-week stock chart + trading data spec |
modules/company-overview.md | Company overview module spec |
modules/valuation.md | Valuation + catalyst calendar spec |
modules/industry-chain.md | Supply chain + upstream/downstream spec |
modules/tables.md | Table styles + data source attribution |
modules/equity-report-charts.md | Chart specs for 5 data charts (revenue, margins, market share, PE band, scenarios) |
| File | Content |
|---|---|
references/data-sources.md | Data source priority + API overview |
references/data-sources-detail.md | API detailed parameters |
references/output-schema.md | Output interface contract |
references/analysis-brief-template.md | Analysis brief template (tear sheet handoff to Phase 4) |
references/research-document-template.md | Research Document template (Task 1 output) — acceptance criteria + quality gate |
references/financial-model-spec.md | Excel financial model specification — tab structure, line items, formulas, integrity checks |
| File | Content |
|---|---|
output/tearsheet-layout.md | Tear Sheet layout, modules, HTML, PDF generation |
output/tearsheet-qa.md | Tear Sheet QA (8mm/12mm margins, 3-5 pages) |
output/tearsheet.css | Compact dual-box CSS (tear sheet sole source) |
output/report-layout.md | Equity Report layout, modules, PDF generation |
output/report-qa.md | Equity Report QA (18mm/20mm margins, ≥25 pages) |
output/report.css | Full-width research report CSS (equity report sole source) |
| File | Content |
|---|---|
scripts/stock_chart_generator.py | 52-week stock chart generator |
scripts/report_validator.py | Report structure validator |
scripts/chart_generator.py | Matplotlib chart generator (5 chart types: revenue_segment, margin_trends, market_share, pe_band, scenario_comparison) |
scripts/embed_charts.py | Chart embedding + chart counter |
npx claudepluginhub lzwme/finance-quant-skills --plugin quant-data-apiCreates institutional-quality equity research initiation reports via a 5-task workflow: company research, financial modeling, valuation, chart generation, and report assembly. Each task must be executed individually with prerequisite verification.
Automates equity research: downloads concalls and presentations from screener.in, uploads to NotebookLM, generates tailored analysis queries by company and sector, outputs professional PDF deep-dive reports.
Generates audience-specific company tear sheets using S&P Capital IQ data, formatted as professional Word documents. Supports equity research, M&A, corporate development, and sales/BD audiences.