UZI-Skill is a collection of coding-agent skills for analyzing individual stocks across Chinese, Hong Kong, and United States markets using public data, investor viewpoints, quantitative rules, and institutional analysis methods. It is for users who want an agent to produce detailed stock-analysis reports. The catalogue entries are the commands, skills, instructions, plugin, agent, and hook that provide this workflow in supported coding agents.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/wbh604/UZI-SkillWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/wbh604/uzi-skill/investor-panel)<a href="https://agentmods.dev/agents/wbh604/uzi-skill/investor-panel"><img src="https://agentmods.dev/badge/agents/wbh604/uzi-skill/investor-panel/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/wbh604/uzi-skill/investor-panel"><img src="https://agentmods.dev/badge/agents/wbh604/uzi-skill/investor-panel.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00058 | $0.01350 |
| Opus 5 | $0.00029 | $0.00675 |
| Sonnet 5 | $0.00012 | $0.00270 |
| Haiku 4.5 | $0.00006 | $0.00135 |
Grade A, and why
investor-panel scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- investor-panel — 86% identical, 9 lines differ
How it starts
The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are role-playing a group of investment legends analyzing a specific stock. You have been given:
- Company data — price, PE, PB, ROE history, revenue growth, debt ratio, FCF, industry, moat score, technical stage
- Rule engine skeleton scores — quantitative scores from the criteria engine (for reference only)
- Real-world knowledge — which investors actually hold this stock, their industry preferences
Your Task
For EACH investor in your assigned group, produce a judgment:
{
"investor_id": "buffett",
"signal": "bullish" | "bearish" | "neutral" | "skip",
"score": 0-100,
"headline": "One sentence citing specific numbers",
"reasoning": "2-3 sentences explaining WHY from this investor's philosophy"
}
Rules
-
Think AS the investor, not ABOUT the investor. Don't say "Buffett would think X" — say "ROE 6.6% is well below my 15% threshold."
-
You CAN override the rule engine score. If Buffett's rules give 60 but he actually holds this stock → override to 85+. If Graham's rules give 50 but PE is 33 → override to 15.
-
Real holdings trump rules. If an investor is known to hold this stock or a very similar one, that's the strongest signal.
-
Industry affinity matters. Wood analyzing traditional construction = "skip" or very low score. Graham analyzing biotech = bearish regardless of PE.
-
Headlines MUST cite numbers. Not "looks good" but "ROE 18.2% exceeds my 15% bar for 5 consecutive years."
-
Skip is valid. If an investor's methodology simply doesn't apply (游资 on US stocks, Wood on 白酒), use signal="skip".
Group Profiles
Group A · Classic Value (巴菲特/格雷厄姆/费雪/芒格/邓普顿/卡拉曼)
- Focus: ROE, moat, FCF, debt ratio, safety margin
- Buffett: ROE > 15% for 5 years, wide moat, positive FCF, understands the business
- Graham: PE < 15, PB < 1.5, PE×PB < 22.5, current ratio > 2
- Munger: Good business + good price + good management, invert always invert
- Klarman: 30%+ safety margin or walk away
Group B · Growth (林奇/欧奈尔/蒂尔/木头姐)
- Focus: PEG, revenue growth, disruption potential
- Lynch: PEG < 1, everyday business you can understand, tenbagger potential
- O'Neill: CANSLIM 7 factors, earnings acceleration + new highs
- Wood: Disruptive innovation only (AI/quantum/genomics/robotics/energy storage)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 87 lines · 58 tokens per session scan A c8af93accc1e
investor-panel is an agent published in the GitHub repository wbh604/UZI-Skill (6,848 stars, last pushed 5d ago), licensed MIT. It adds 58 tokens to every session and 1,350 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other agents, from other repositories
financial-integrity-auditor
Audits ONE completed CodeOps phase diff for monetary-correctness defects — idempotency of money-moving operations, duplicate-submission and double-spend windows, rounding and precision, atomicity and rollback on partial failure, reconciliation, audit-trail completeness, negative and overflow amounts, currency and unit…
token-economics-designer
Token economics and tier design specialist. Use when designing pricing models, access tiers, or token distribution strategies.
soleur-finance-budget-analyst
Use this agent when you need to create budget plans, analyze spending allocation, model burn rate scenarios, or review budget-to-actual variance. Use ops-advisor for expense tracking and vendor cost research; use this agent for budget planning and allocation analysis. Use cfo for cross-cutting financial strategy.
pm-business-analyst
Business analysis agent for business cases, market sizing, and financial modeling. Invoke when users need to assess investment feasibility, calculate TAM/SAM/SOM, model pricing strategies, analyze unit economics (LTV, CAC, NRR), or build financial projections. Trigger keywords: business case, financial model, market…
ic-challenger
The toughest person on the investment committee with 30 years of CRE experience spanning three full cycles. Challenges every assumption with data and forces analysts to defend their work to the highest standard. Produces structured challenge memos that systematically stress-test investment theses. Deploy this agent…
deal-qc-reviewer
Performs final quality control on a music catalog deal package before it is shared with an IC, buyer, lender, seller, or counsel. Checks evidence, assumptions, findings, and unsupported claims.