SuperAPI AI Directory

equity-researcher

Writing & research

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Updated 10-16 00:03

About this skill

Equity Research 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.

Your first job: figure out what the user wants. Then carry the Core Principles into the next file.


Phase 0.0: Router — Intent Clarification + Output Type Detection

Step 1: Detect Language

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

Step 2: Classify Intent (3 Tiers)

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", investment snapshot, investment brief, "research report", "deep dive", "equity report", research report, in-depth research, in-depth analysis → Skip to Step 3 (output type is clear)
Tier B: Company analysis — ambiguous depth "help me analyze [company]", "analyze [company]", "help me look at [stock]", "look into [stock]", "learn about [company]", "what do you think of [company]", individual stock analysis, company analysis, or just a stock code (e.g. AAPL, 600519) → Ask user (Step 2a)
Tier C: Simple question "what does XX company do", "what's [company]'s market cap", "when is [stock]'s next earnings" → Do NOT trigger this skill. Answer conversationally. No report generation.

Step 2a: Clarify Intent (Tier B only)

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:

I can help you analyze [company name] in the following ways:

  1. Investment Snapshot (Tear Sheet) — 3-5 page professional institutional-grade investment brief, including valuation, catalysts, industry chain, scenario analysis, etc., suitable for quick decision-making reference
  2. In-depth Research Report (Equity Report) — ≥25 page institutional-grade in-depth research report, including a complete financial model, DCF valuation, sensitivity analysis, etc., suitable for in-depth research
  3. Simple answer — Do not generate a report; answer your question directly in conversation, saving the most time

Which one would you like?

English example:

I can analyze [company] at different levels of depth:

  1. Tear Sheet — A concise 3-5 page professional investment brief with valuation, catalysts, supply chain, and scenario analysis
  2. Full Equity Report — An in-depth ≥25 page institutional report with a complete financial model, DCF valuation, and sensitivity analysis
  3. 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.

Step 3: Determine Output Type

User Choice / Signal Output Type Variable
Tear Sheet / Investment Snapshot / option 1 Tear Sheet output_type = TEAR_SHEET
Equity Report / In-depth Research / option 2 Equity Report output_type = EQUITY_REPORT
Explicit "tear sheet", "one pager", investment snapshot, investment brief, company one-pager, "quick glance", "investment memo" Tear Sheet output_type = TEAR_SHEET
Explicit "research report", "full report", "deep dive", "equity report", research report, in-depth research, in-depth analysis Equity Report output_type = EQUITY_REPORT

Once output_type is set, record it. This variable determines which mode-specific file to read next.


Step 3a: Equity Report Valuation Depth Selection (only when 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:

The in-depth research report can be generated at two valuation depths:

  1. Full version (including financial model) — Build a complete three-statement financial model (income statement/balance sheet/cash flow statement) + DCF absolute valuation + comparable company valuation + sensitivity analysis + historical valuation band. Suitable for scenarios requiring in-depth research and precise target prices. Takes about 3 steps to complete.
  2. Streamlined version (Level 1 valuation) — Based on comparable company valuation (PE/PB/PS multiples) + consensus estimates + scenario analysis, quickly generate a professional research report. No complex Excel modeling, faster. Takes about 2 steps to complete.

Which one do you choose?

English:

The equity report can be built at two valuation depths:

  1. 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.
  2. 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 / Full version / option 1 Level 2 (DCF + Comps + Sensitivity) valuation_depth = L2 3 Tasks: Task 1 → Task 2 (Excel model) → Task 3
Streamlined version / Streamlined version / option 2 Level 1 (Comps + Multiples only) valuation_depth = L1 2 Tasks: Task 1 → Task 3 (L1 mode, no Task 2 Excel)

Key difference:

  • L2: Task 2 produces a real Excel model (8+ tabs) with DCF. Task 3 reads numbers from Excel via openpyxl.
  • L1: Skip Task 2 entirely. Task 1's research document contains all valuation inputs. Task 3 generates valuation tables directly from the research document (no Excel model needed).

If output_type = TEAR_SHEET: Skip this step entirely. Tear sheets always use Level 1.


⚠️ Core Principles — CARRY THESE INTO THE NEXT FILE

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)

Data Authenticity Rule

Prohibit fabricating data, eliminate scaffold/placeholders. See references/data-sources.md §Data Missing Handling + quality checklist A6-A8.


Step 4: Route NOW

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):

I will generate an in-depth research report (full version) for you, in 3 steps:

  • Step 1: In-depth research analysis (data collection + six-dimensional analysis + industry research) → output research document
  • Step 2: Financial modeling and valuation (Excel three-statement model + DCF valuation + sensitivity analysis)
  • Step 3: Generate the final PDF research report (≥25 pages)

Now start Step 1.

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):

I will generate an in-depth research report (streamlined version) for you, in 2 steps:

  • Step 1: In-depth research analysis (data collection + six-dimensional analysis + comparable company valuation) → output research document
  • Step 2: Generate the final PDF research report (≥25 pages, based on comparable company valuation)

Now begin Step 1.

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.



REFERENCE SECTION

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.


Output Type Comparison

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

Mode A: Tear Sheet / Investment Snapshot (Single Session)

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)
  • Entry file: SKILL-tearsheet.md
  • Output document: Analysis Brief → references/analysis-brief-template.md
  • Layout: output/tearsheet-layout.md → output/tearsheet.css
  • QA: output/tearsheet-qa.md

Mode B: Equity Report / In-Depth Research (Multi-Task Architecture)

An in-depth ≥25 page PDF built across 2 or 3 Tasks depending on valuation depth. Both L1 and L2 share the same Task 1.

L2 (Full Version — 3 Tasks)

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)

L1 (Streamlined Version — 2 Tasks)

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)

Universal Task Rules (Apply to Both L1 and L2)

  1. Never chain Tasks automatically. Each Task ends with delivery + STOP.
  2. User continues with a single word: "Next step", "continue", or "continue" — no file uploads needed.
  3. Session context carries files. The agent maintains the file list internally. When the user says "continue", the agent reads the previously generated files from the session automatically.
  4. Data flows via files, not memory. Task 2 reads Task 1's document. Task 3 reads Task 2's Excel (L2) or Task 1's document (L1). All financial numbers in Task 3's PDF must tie back to either the Excel model (L2) or the research document (L1).

File Index

All paths are relative to this skill's root directory.

Entry Points

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

Analysis Frameworks (read on-demand per Hard Gate)

File Content
analysis/six-dimension-analysis.md Six-Dimensional Analysis 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.md for equity reports, references/analysis-brief-template.md for tear sheets). No separate per-framework files.

Deep Research Modules (Equity Report Only — Phase 2.7)

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

Valuation Methods

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)

Report Module Specs

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)

References

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

Output Layer (Phase 4 layout + Phase 5 QA + CSS)

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)

Scripts

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