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us-stock-researcher美国股票研究员

Agent Skill

us-stock-researcher 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

1,769

周安装

76

GitHub Stars

33

下载量

620
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:us-stock-researcher(美国股票研究员)
来源仓库:https://github.com/skindhu/skind-skills
仓库路径:skills/us-stock-researcher
安装命令:
npx skills add https://github.com/skindhu/skind-skills --skill us-stock-researcher
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/skindhu/skind-skills --skill us-stock-researcher

简介

美国股票研究员用于查找、检索和筛选相关信息,适合在主流 AI 编程工具中快速定位候选结果。

  • 适用于需要根据关键词或任务场景进行信息检索的股票研究类工作流。
  • 通过 npx 命令从 GitHub 仓库安装,支持 Codex、Claude、Cursor 等宿主环境。
  • 安装前需确认权限范围和维护状态,注意可能触发联网或文件读写操作。
  • 建议结合原始 README 文档核验具体用法和功能边界。

SKILL.md

US Stock Researcher

Institutional-grade deep analysis of US stock SEC filings, outputting professional investment reports.

Research Mode Selection

ModeWhen to UseRequirements
Gemini ModeDefault when GEMINI_API_KEY is configuredGEMINI_API_KEY environment variable
Claude Native ModeWhen no Gemini API or user requestsWebSearch 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

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):

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):

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):

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-rules.md, save to <project_root>/investment-research/{TICKER}/


Mode 1: Gemini Deep Research

User Input → Download Filing → Framework Generation → Local: Filing Analysis → Web: Market Research → Integration → Final Report
                                                              ↓                         ↓
                                                      (Gemini Deep Research)    (Gemini Deep Research)
  • Local phase (--phase local): Upload filing via Files API, Gemini analyzes comprehensively
  • Web phase (--phase web): Web search for competitors, trends, management verification
  • Integration: Claude merges local + web results per <skill_dir>/prompts/report-merge-prompt.md

Mode 2: Claude Native Deep Research

Uses 7-Phase Deep Research + Graph of Thoughts (GoT) methodology.

For complete execution details, see: <skill_dir>/prompts/claude-deep-research-protocol.md

7-Phase Overview

PhaseNameDescription
1Question ScopingDefine goals, download filing
2Retrieval PlanningIdentify industry, create research plan
3Iterative QueryingGoT branches: Financial, Competitive, Industry, Management, Risk
4Source TriangulationCross-validate findings
5Knowledge SynthesisStructure report per framework
6Quality AssuranceChain-of-Verification
7Output PackagingFormat and save

GoT Research Branches

BranchMethodFocus
ARead filingFinancial data analysis
BWebSearchCompetitive landscape
CWebSearchIndustry trends
DWebSearchManagement verification
EWebSearchRisk factors

Reference Documents

DocumentPurpose
financial-analysis-framework.mdBase analysis framework
industry-analysis-modules.mdIndustry-specific modules
markdown-formatter-rules.mdReport formatting rules
prompts/claude-deep-research-protocol.mdClaude Native 7-phase guide
prompts/report-merge-prompt.mdGemini mode report integration

Output Location

<project_root>/investment-research/{TICKER}/
├── tmp/
│   ├── sec_filings/cleaned.txt
│   ├── analysis-framework-YYYY-MM-DD.md
│   ├── phase1-YYYY-MM-DD.md             # Local phase (--phase local) output
│   └── phase2-YYYY-MM-DD.md             # Web phase (--phase web) output
└── {TICKER}-Investment-Report-YYYY-MM-DD.md

Usage Examples

  • "Analyze AAPL's latest 10-K annual report"
  • "Deep research MSFT's 10-K filing"
  • "Analyze JPM's latest annual report" (auto-selects Financial module)
  • "Research PFE's financial report" (auto-selects Pharma module)

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

34.06%
按下载量换算211

Claude

30.64%
按下载量换算190

Cursor

18.2%
按下载量换算113

Gemini CLI

8.09%
按下载量换算50

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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