Agent Skills › wbh604/UZI-Skill › uzi

uzi

GitHub

UZI是面向A股、港股及美股的深度研究与分析报告生成技能，涵盖估值、资金流向、陷阱检测及HTML报告。

SKILL.md wbh604/UZI-Skill

Trigger Scenarios

股票深度研究估值分析 IC备忘录生成 Bloomberg风格报告

Install

npx skills add wbh604/UZI-Skill --skill uzi -g -y

More Options

Use without installing

npx skills use wbh604/UZI-Skill@uzi

指定 Agent (Claude Code)

npx skills add wbh604/UZI-Skill --skill uzi -a claude-code -g -y

安装 repo 全部 skill

npx skills add wbh604/UZI-Skill --all -g -y

预览 repo 内 skill

npx skills add wbh604/UZI-Skill --list

SKILL.md

Frontmatter

{
    "name": "uzi",
    "author": "FloatFu-true",
    "license": "MIT",
    "version": "3.9.4",
    "metadata": {
        "tags": [
            "finance",
            "stocks",
            "a-share",
            "hong-kong",
            "us-stocks",
            "dcf",
            "valuation",
            "investor-panel",
            "youzi",
            "lhb",
            "trap-detection"
        ],
        "related_skills": [
            "deep-analysis",
            "investor-panel",
            "lhb-analyzer",
            "trap-detector"
        ]
    },
    "description": "A-share, Hong Kong, and US stock analysis skill for deep research, quick scans, investor panel review, hot-money\/LHB analysis, trap detection, valuation, IC memos, and Bloomberg-style HTML reports."
}

UZI Skill Root

This root file is the top-level entry for agents that expect a SKILL.md at the repository root.

Use the narrowest matching workflow:

Full stock research, valuation, IC memo, initiation, catalysts, earnings review, or HTML report: read skills/deep-analysis/SKILL.md.
Investor jury, "which investors would buy", panel-only voting, or persona review: read skills/investor-panel/SKILL.md.
Hot-money, LHB, seat recognition, or A-share short-term trader analysis: read skills/lhb-analyzer/SKILL.md.
Trap detection, pump-and-dump checks, "teacher/group/friend recommended this stock", or safety review: read skills/trap-detector/SKILL.md.
Command-specific requests: read the matching file under commands/.

Default Execution

From the repository root:

python3 run.py <ticker> --no-browser

For remote/mobile reports:

python3 run.py <ticker> --remote

For a single investor school, such as A-share hot-money:

python3 run.py <ticker> --school F --no-browser

Agent Rules

Treat scripts as data and scoring tools, not as final analyst judgment.
Do not invent numbers. Use script outputs, cached JSON, or current public evidence.
For serious deep-analysis requests, complete the agent review loop described in skills/deep-analysis/SKILL.md before final report assembly.
For hot-money analysis, apply LHB seat matching and is_in_range() before making a short-term judgment.
For trap detection, scan all eight signals and include concrete evidence when risk is non-trivial.
For report template or UI changes, update tests, version metadata, and release notes together.