Portfolio Optimization
NVIDIA/skills
A skill your agent uses when a user asks to build, optimize, backtest, rebalance, or analyze a stock portfolio with Mean-CVaR, Mean-Variance/SOCP variance caps, efficient frontiers, scenario…
Structured, multi-dimensional company investment research framework for AI agents and human analysts.
$ npx skills add aAAaqwq/AGI-Super-Team --skill company-investment-research -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aAAaqwq/AGI-Super-Team company-investment-research --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/company-investment-research .claude/skills/company-investment-research && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "company-investment-research" agent skill from https://github.com/aAAaqwq/AGI-Super-Team/tree/main/skills/company-investment-research into .claude/skills/company-investment-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "company-investment-research", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/aAAaqwq/AGI-Super-Team/tree/main/skills/company-investment-researchType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add aAAaqwq/AGI-Super-Team --skill company-investment-research -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aAAaqwq/AGI-Super-Team company-investment-research --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/company-investment-research .agents/skills/company-investment-research && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "company-investment-research" agent skill from https://github.com/aAAaqwq/AGI-Super-Team/tree/main/skills/company-investment-research into .agents/skills/company-investment-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "company-investment-research", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aAAaqwq/AGI-Super-Team --skill company-investment-research -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aAAaqwq/AGI-Super-Team company-investment-research --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/company-investment-research .cursor/skills/company-investment-research && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "company-investment-research" agent skill from https://github.com/aAAaqwq/AGI-Super-Team/tree/main/skills/company-investment-research into .cursor/skills/company-investment-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "company-investment-research", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/aAAaqwq/AGI-Super-Team.git --path skills/company-investment-research--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add aAAaqwq/AGI-Super-Team --skill company-investment-research -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aAAaqwq/AGI-Super-Team company-investment-research --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/company-investment-research .gemini/skills/company-investment-research && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "company-investment-research" agent skill from https://github.com/aAAaqwq/AGI-Super-Team/tree/main/skills/company-investment-research into .gemini/skills/company-investment-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "company-investment-research", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install aAAaqwq/AGI-Super-Team company-investment-researchInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add aAAaqwq/AGI-Super-Team --skill company-investment-research -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/company-investment-research .github/skills/company-investment-research && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "company-investment-research" agent skill from https://github.com/aAAaqwq/AGI-Super-Team/tree/main/skills/company-investment-research into .github/skills/company-investment-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "company-investment-research", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aAAaqwq/AGI-Super-Team --skill company-investment-research -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install aAAaqwq/AGI-Super-Team company-investment-research --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aAAaqwq/AGI-Super-Team.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/company-investment-research .opencode/skills/company-investment-research && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "company-investment-research" agent skill from https://github.com/aAAaqwq/AGI-Super-Team/tree/main/skills/company-investment-research into .opencode/skills/company-investment-research/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "company-investment-research", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
company-investment-researchStructured, multi-dimensional company investment research framework for AI agents and human analysts.
Company Investment Research is an agent skill from aAAaqwq/AGI-Super-Team. Structured, multi-dimensional company investment research framework for AI agents and human analysts. Provides a 10-part checklist (moat, tech, market, customers, growth, financials, geography, governance, valuation, recommendation) to turn scattered info into a consistent, high-quality investment memo. | 面向 AI Agent 与人工分析师的公司投研框架,用 10 大维度系统梳理商业模式、护城河、成长与估值,快速产出结构化投研报告。
Its SKILL.md is about 4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files (for example `.clawhub/origin.json`, `_meta.json` and `references/analysis-framework.md`).
It sits in Business, Finance & HR. It works with NVIDIA AI Platform. The repository describes itself as: An installable, cross-framework AI organization: C-suite agents, expert subagents, curated skills, independent review, and one-command setup across 18 AI client/runtime adapters. The licence is MIT.
12 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 7cefd81. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
pythonFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Company Investment Research loads about 4k tokens when it runs, and up to ~8.1k if it reads all its reference files. Until then it costs about 100 tokens; SKILL.md has 1,631 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from aAAaqwq/AGI-Super-Team at commit 7cefd81, republished under its MIT licence (© aAAaqwq). 1,631 words, ~3,958 tokens.
.claude/skills/company-investment-research/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.This skill provides a systematic framework for conducting comprehensive investment research and due diligence on companies. It structures analysis across 10 critical dimensions to support informed investment decisions.
本技能为公司基本面研究提供一套结构化投研框架,覆盖 10 个关键维度,帮助你从零开始梳理一家公司的商业模式、竞争力、增长与估值,并最终形成一份有逻辑的投资结论。
Use this skill when you need to:
适合在以下场景使用:
"Analyze NVIDIA (NVDA) as an investment using the company-investment-research framework. Follow all 10 dimensions and end with a clear BUY/HOLD/SELL view, including key risks."
「请基于
company-investment-research投研框架,系统分析英伟达(NVIDIA, NVDA)的投资价值,按 10 个维度展开,最后给出 BUY/HOLD/SELL 判断,并列出关键风险。」
"Using the company-investment-research skill, compare NVIDIA vs AMD as AI infrastructure investments. Highlight differences in moat, growth drivers, and valuation, then state which one looks more attractive on a 3–5 year horizon and why."
「使用该投研框架对比分析 NVIDIA 与 AMD 作为 AI 基础设施投资标的的优劣,从护城河、成长驱动、估值三方面重点展开,并给出未来 3–5 年哪个更具吸引力及原因。」
"Run a lightweight version of the company-investment-research framework on Snowflake. Focus on competitive positioning, growth drivers, and valuation to decide whether it deserves full deep-dive research."
「对 Snowflake 做一版简化版投研:重点看竞争地位、成长驱动和估值,判断是否值得投入时间做完整深度研究。」
"Create a 2–3 page investment memo for Tesla using the company-investment-research structure. The target audience is an investment committee; keep language concise but include key numbers and scenarios (base/bull/bear)."
「按照本框架,为特斯拉生成一份 2–3 页的投资备忘录,供投委会讨论使用:语言简洁,但需包含核心数据与基础/乐观/悲观三种情景。」
Below are add-on checklists for specific industries. Use them on top of the 10 core dimensions.
下面是针对特定行业的额外检查项,在 10 大通用维度基础上叠加使用即可。
Typical businesses / 典型业务: 内容平台、电商、社交、短视频、本地生活等。
Extra focus areas / 额外关注点:
User metrics / 用户指标
Engagement & retention / 使用粘性与留存
Monetization model / 变现模式
Unit economics / 单位经济模型
Additional questions / 可直接提问的附加问题:
Prompt 示例: 「针对某互联网平台公司,在 10 大维度基础上,额外重点分析用户增长 & 留存、变现模式与单位经济模型,并结合监管风险给出中长期盈利能力判断。」
Typical businesses / 典型业务: GPU/CPU/ASIC 设计、晶圆制造(Foundry)、封装测试、设备与材料等。
Extra focus areas / 额外关注点:
Position in the value chain / 产业链位置
Technology node & roadmap / 工艺节点与技术路线
End markets & demand drivers / 下游应用与需求驱动
Capacity & supply constraints / 产能与供给约束
Additional questions / 可直接提问的附加问题:
Prompt 示例: 「针对某半导体公司,在 10 大维度基础上,重点补充其在产业链中的位置、主要下游应用结构、工艺/产品路线图以及 AI/汽车电子等结构性需求的暴露度,并评估地缘政治对其业务的潜在影响。」
Typical businesses / 典型业务: 连锁咖啡品牌、连锁茶饮、快餐/休闲餐厅品牌等。
Extra focus areas / 额外关注点:
Store economics / 单店模型
Same-store sales & expansion / 同店增长与扩店节奏
Brand & customer perception / 品牌力与消费者心智
Supply chain & cost structure / 供应链与成本结构
Additional questions / 可直接提问的附加问题:
Prompt 示例: 「针对某连锁咖啡品牌,在 10 大通用维度基础上,重点拆解单店经济模型(投资额、回本周期、毛利结构)、同店增长与扩店策略、品牌定位与复购率,并评估在不同经济周期下的抗压能力。」
When analyzing a company for investment, follow this structured approach to ensure comprehensive coverage:
在分析一家公司时,建议按以下 10 个维度逐一梳理,避免遗漏关键点:
Core Questions:
Search Strategy:
Analysis Approach:
Core Questions:
Search Strategy:
Key Metrics:
Core Questions:
Search Strategy:
Analysis Framework:
Core Questions:
Search Strategy:
Risk Assessment:
Core Questions:
Search Strategy:
Evaluation Criteria:
Core Questions:
Search Strategy:
Analysis Components:
Core Questions:
Search Strategy:
Key Considerations:
Core Questions:
Search Strategy:
Governance Assessment:
Core Questions:
Search Strategy:
Valuation Framework:
Synthesize all analysis into clear recommendation:
If Investment is Recommended:
If Investment is NOT Recommended:
Present findings in a clear, structured format:
# Investment Analysis: [Company Name]
**Date:** [Current Date]
**Analyst:** [Your Name or Agent]
## Executive Summary
[2-3 paragraph overview with key takeaway and recommendation]
## 1. Competitive Positioning
[Findings]
## 2. Technology & Innovation
[Findings]
## 3. Market Position
[Findings]
## 4. Customer Base
[Findings]
## 5. Growth Analysis
[Findings]
## 6. Financial Performance
[Findings]
## 7. International Exposure
[Findings]
## 8. Ownership & Governance
[Findings]
## 9. Valuation
[Findings]
## 10. Investment Recommendation
**Recommendation:** BUY / HOLD / SELL
**Target Price:** [If applicable]
**Investment Thesis:** [Key reasons]
**Key Risks:** [Main concerns]建议在实际使用中,将上述结构作为 Markdown 模板,一边研究一边填空,最终沉淀为可复用的投研文档库。
Use Multiple Sources / 多源交叉验证
Cross-reference information from company filings, analyst reports, news, and financial databases.
Verify Timeliness / 确保数据新鲜度
Always check dates on data – use the most recent available information.
Quantify When Possible / 尽量量化
Provide specific numbers, percentages, and metrics rather than only qualitative descriptions.
Acknowledge Limitations / 明确假设与局限
Note when information is unavailable or when making assumptions.
Maintain Objectivity / 保持客观
Present both bullish and bearish perspectives; avoid confirmation bias.
Source Attribution / 标注关键来源
Cite sources for key data points, especially financial figures.
This skill focuses on how to think and structure research. For data and filings, pair it with external tools/APIs.
本技能侧重于思考框架与结构化输出,财报与数据建议通过其他工具或脚本获取,然后作为本框架的输入。
示例以美股为主(可按同样思路换成 A 股/港股对应数据源):
Download latest 10-K / 10-Q filings
Use any SEC helper tool or script, for example:
# Example: download the latest 10-K for NVIDIA (NVDA) into ./filings
sec-edgar-downloader company "NVIDIA" \
--form-type 10-K --num 1 --download-folder ./filingsFetch key financials via an API or Python script
For example, a simple Python entry point:
python scripts/fetch_financials.py --ticker NVDA --out data/nvda.jsonThe script can query any financial data provider (Yahoo Finance, financial APIs, etc.) and standardize outputs (revenue, margins, key ratios) for later use in this framework.
Use web_fetch for qualitative sections
For business descriptions, risk factors, and management discussion, you can:
1. Download the filing (PDF/HTML)
2. Use web_fetch to extract key sections into markdown
3. Feed those into the 10-dimension analysis推荐实践:将「数据抓取脚本 + 本投研框架」放在同一项目中,通过 Makefile 或 shell 脚本串联,形成一键跑通的投研流水线(先拉数据,再生成报告草稿)。
© aAAaqwq, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 4 other files (references) in skills/company-investment-research of aAAaqwq/AGI-Super-Team.
Open the folder on GitHubat commit 7cefd81
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in aAAaqwq/AGI-Super-Team, which our catalogue first saw on October 7, 2026.
Company Investment Research next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Company Investment Research this skillaAAaqwq/AGI-Super-Team | 105 | 1 repos | ~4k | Automated safety check: Pass | MIT | |
| Portfolio OptimizationNVIDIA/skills | 3.6k | — | ~4.9k | Automated safety check: Pass | Apache-2.0 | |
| Kernel ProfilingZJLi2013/awesome-kernel-skills | 102 | — | ~696 | Automated safety check: Pass | None | |
| Tao Run Deft PasNVIDIA/skills | 3.6k | — | ~4.2k | Automated safety check: Notes | Apache-2.0 | |
| Deepstream SopNVIDIA/skills | 3.6k | — | ~4.7k | Automated safety check: Notes | Apache-2.0 | |
| Amc Setup Calibration StackNVIDIA/skills | 3.6k | — | ~3.9k | Automated safety check: Notes | Apache-2.0 |
NVIDIA/skills
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Works with
Categories
Structured, multi-dimensional company investment research framework for AI agents and human analysts. Company Investment Research is an agent skill from aAAaqwq/AGI-Super-Team. Structured, multi-dimensional company investment research framework for AI agents and human analysts.
Company Investment Research fits situations like: business, Finance & HR work in your project.
Run `npx skills add aAAaqwq/AGI-Super-Team --skill company-investment-research -a claude-code`. Or copy the skill folder (skills/company-investment-research in aAAaqwq/AGI-Super-Team) into .claude/skills/company-investment-research in your project. Claude Code loads it when a task matches its description.
Run `npx skills add aAAaqwq/AGI-Super-Team --skill company-investment-research -a codex`. Or copy the skill folder (skills/company-investment-research in aAAaqwq/AGI-Super-Team) into .agents/skills/company-investment-research in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aAAaqwq/AGI-Super-Team --skill company-investment-research -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/company-investment-research, .gemini/skills/company-investment-research, .github/skills/company-investment-research and .opencode/skills/company-investment-research in your project.
Going by SKILL.md and its folder, Company Investment Research needs the command-line tools its instructions call (python).
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Company Investment Research is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 4k tokens (SKILL.md is roughly 16k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 4.2k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Company Investment Research: Portfolio Optimization (NVIDIA/skills, 3.6k stars), Kernel Profiling (ZJLi2013/awesome-kernel-skills, 102 stars), Tao Run Deft Pas (NVIDIA/skills, 3.6k stars) and Deepstream Sop (NVIDIA/skills, 3.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
aAAaqwq (a GitHub user) maintains it in aAAaqwq/AGI-Super-Team, which has 105 GitHub stars. The repository holds 167 skills in this directory. The repository was last updated on October 8, 2026.
Source: aAAaqwq/AGI-Super-Team on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.