Skill detail
us-stock-researcher
Deep research limited to US stock and SEC-filing analysis.
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SKILL.md
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---
name: us-stock-researcher
description: US Stock Investment Research Assistant. Supports Gemini Deep Research or Claude Native Deep Research (7-Phase + GoT). Use when analyzing 10-K/10-Q reports or generating investment research reports.
allowed-tools: Read, Write, WebSearch, Bash(python3.11:*)
---
# US Stock Researcher
Institutional-grade deep analysis of US stock SEC filings, outputting professional investment reports.
## Research Mode Selection
| Mode | When to Use | Requirements |
|------|-------------|--------------|
| **Gemini Mode** | Default when GEMINI_API_KEY is configured | GEMINI_API_KEY environment variable |
| **Claude Native Mode** | When no Gemini API or user requests | WebSearch tool access |
---
## Quick Start Workflow
### Path Variables
Before starting, determine these two paths:
- `<project_root>`: The user's current working directory (where the agent session started). All output files go here.
- `<skill_dir>`: The directory containing this SKILL.md file. Use its absolute path to reference scripts.
**IMPORTANT: Always use absolute paths when running scripts. Never `cd` into the skill directory.**
### Step 1: Determine Filing Period
**If user did NOT specify a period**, use WebSearch to find the latest filing:
```
WebSearch: "{company_name} latest 10-K 10-Q SEC filing"
```
**IMPORTANT: Always analyze the MOST RECENT filing by date, regardless of type (10-K or 10-Q).**
Example decision logic:
- If latest 10-K is 2024-12-31 and latest 10-Q is 2025-09-30 → Use 10-Q (more recent)
- If latest 10-K is 2025-01-15 and latest 10-Q is 2024-09-30 → Use 10-K (more recent)
Inform user: "根据搜索,{TICKER} 最新的财报是 {10-K/10-Q}(截至 {period}),将分析该期财报"
### Step 2: Download Filing
```bash
python3.11 <skill_dir>/scripts/download_sec_filings.py --ticker <TICKER> --type <10-K|10-Q|6-K> --limit 1 --project-root <project_root>
```
Output: `<project_root>/investment-research/{TICKER}/tmp/sec_filings/cleaned.txt`
### Step 3: Dynamic Framework Generation
1. Read first 5000 characters of filing
2. Identify company industry
3. Select modules from `<skill_dir>/industry-analysis-modules.md`
4. Merge with `<skill_dir>/financial-analysis-framework.md`
5. Save to `<project_root>/investment-research/<TICKER>/tmp/analysis-framework-YYYY-MM-DD.md`
### Step 4: Execute Deep Research
**Gemini Mode (full two-phase analysis):**
```bash
python3.11 <skill_dir>/scripts/gemini_deep_research.py \
--input <project_root>/investment-research/<TICKER>/tmp/sec_filings/cleaned.txt \
--prompt <project_root>/investment-research/<TICKER>/tmp/analysis-framework-YYYY-MM-DD.md \
--output-dir <project_root>/investment-research/<TICKER> \
--ticker <TICKER> \
--company <Company Name> \
--phase all
```
**Gemini Mode (local filing analysis only):**
```bash
python3.11 <skill_dir>/scripts/gemini_deep_research.py \
--input <project_root>/investment-research/<TICKER>/tmp/sec_filings/cleaned.txt \
--prompt <project_root>/investment-research/<TICKER>/tmp/analysis-framework-YYYY-MM-DD.md \
--output-dir <project_root>/investment-research/<TICKER> \
--ticker <TICKER> \
--company <Company Name> \
--phase local
```
**Gemini Mode (web research only, requires local phase output):**
```bash
python3.11 <skill_dir>/scripts/gemini_deep_research.py \
--input <project_root>/investment-research/<TICKER>/tmp/sec_filings/cleaned.txt \
--prompt <project_root>/investment-research/<TICKER>/tmp/analysis-framework-YYYY-MM-DD.md \
--output-dir <project_root>/investment-research/<TICKER> \
--ticker <TICKER> \
--company <Company Name> \
--phase web \
--phase1-output <project_root>/investment-research/<TICKER>/tmp/phase1-YYYY-MM-DD.md
```
**IMPORTANT: `--phase` only accepts three values: `all`, `local`, `web`. Do NOT use numeric values like `1` or `2`.**
**Claude Native Mode:**
Follow `<skill_dir>/prompts/claude-deep-research-protocol.md` for complete 7-phase execution.
### Step 5: Format and Save
Format per `<skill_dir>/markdown-formatter-rRead the full source on GitHub (opens external page)