Creating Financial Models
Chen-zexi/open-ptc-agent
This skill provides an advanced financial modeling suite with DCF analysis, sensitivity testing, Monte Carlo simulations, and scenario planning for investment decisions
Retrieve market capitalization data for multiple companies at once using Octagon MCP.
Install Batch Market Cap
$ npx skills add OctagonAI/skills --skill batch-market-cap -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install OctagonAI/skills batch-market-cap --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/OctagonAI/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/batch-market-cap .claude/skills/batch-market-cap && 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 "batch-market-cap" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/batch-market-cap into .claude/skills/batch-market-cap/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "batch-market-cap", 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/OctagonAI/skills/tree/main/skills/batch-market-capType 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 OctagonAI/skills --skill batch-market-cap -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install OctagonAI/skills batch-market-cap --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/batch-market-cap .agents/skills/batch-market-cap && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "batch-market-cap" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/batch-market-cap into .agents/skills/batch-market-cap/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "batch-market-cap", 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 OctagonAI/skills --skill batch-market-cap -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install OctagonAI/skills batch-market-cap --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/batch-market-cap .cursor/skills/batch-market-cap && 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 "batch-market-cap" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/batch-market-cap into .cursor/skills/batch-market-cap/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "batch-market-cap", 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/OctagonAI/skills.git --path skills/batch-market-cap--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 OctagonAI/skills --skill batch-market-cap -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install OctagonAI/skills batch-market-cap --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/batch-market-cap .gemini/skills/batch-market-cap && 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 "batch-market-cap" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/batch-market-cap into .gemini/skills/batch-market-cap/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "batch-market-cap", 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 OctagonAI/skills batch-market-capInstalls 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 OctagonAI/skills --skill batch-market-cap -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/batch-market-cap .github/skills/batch-market-cap && 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 "batch-market-cap" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/batch-market-cap into .github/skills/batch-market-cap/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "batch-market-cap", 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 OctagonAI/skills --skill batch-market-cap -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install OctagonAI/skills batch-market-cap --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/OctagonAI/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/batch-market-cap .opencode/skills/batch-market-cap && 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 "batch-market-cap" agent skill from https://github.com/OctagonAI/skills/tree/main/skills/batch-market-cap into .opencode/skills/batch-market-cap/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "batch-market-cap", 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.
Facts
- Skill name
batch-market-cap- GitHub stars
- 127
- Token cost
- ~1.6k tokens
- SKILL.md length
- 530 words
- Files
- 5 (incl. references)
- Skills in repo
- 53
- Repo updated
- First seen
- Licence
- MIT
At a glance
Retrieve market capitalization data for multiple companies at once using Octagon MCP.
- Works in 4 steps: Prepare Company List → Execute Query via Octagon MCP → Expected Output → …
- Comparing valuations across peers
- SKILL.md covers Prerequisites, Workflow, Example Queries and Market Cap Categories, plus 6 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Batch Market Cap is an agent skill from OctagonAI/skills. Retrieve market capitalization data for multiple companies at once using Octagon MCP. Use when comparing valuations across peers, screening by market cap, or analyzing a portfolio's composition by company size.
Its SKILL.md is about 1.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `README.md`, `marketplace.json` and `references/interpreting-results.md`).
It sits in Business, Finance & HR. It works with Model Context Protocol. The repository describes itself as: A collection of Claude skills for agentic financial research by Octagon. The licence is MIT.
When your agent uses it
- Comparing valuations across peers
- Screening by market cap
- Analyzing a portfolios composition by company size
Example prompts
- “/batch-market-cap”
Workflow steps
4 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 51e938c. It shows what the files ask for, not the result of running them.
Tool permissions
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.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are json).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Batch Market Cap loads about 1.6k tokens when it runs, and up to ~3.8k if it reads all its reference files. Until then it costs about 57 tokens; SKILL.md has 530 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.
Safety
Auto-check passed
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.
SKILL.md
The full file from OctagonAI/skills at commit 51e938c, republished under its MIT licence (© OctagonAI). 530 words, ~1,566 tokens.
Download SKILL.mdSave it as
.claude/skills/batch-market-cap/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- batch-market-cap
- description
- Retrieve market capitalization data for multiple companies at once using Octagon MCP. Use when comparing valuations across peers, screening by market cap, or analyzing a portfolio's composition by company size.
Batch Market Cap
Retrieve market capitalization data for multiple companies in a single query using the Octagon MCP server.
Prerequisites
Ensure Octagon MCP is configured in your AI agent (Cursor, Claude Desktop, Windsurf, etc.). See references/mcp-setup.md for installation instructions.
Workflow
1. Prepare Company List
Compile the list of ticker symbols you want to analyze (e.g., AAPL, MSFT, GOOGL).
2. Execute Query via Octagon MCP
Use the octagon-agent tool with a natural language prompt:
Retrieve market capitalization data for the following companies: <TICKER1>, <TICKER2>, <TICKER3>.MCP Call Format:
{
"server": "octagon-mcp",
"toolName": "octagon-agent",
"arguments": {
"prompt": "Retrieve market capitalization data for the following companies: AAPL, MSFT, GOOG."
}
}3. Expected Output
The agent returns a structured table with market cap data:
| Company | Ticker | Market Cap (USD) | Source |
|---|---|---|---|
| Apple | AAPL | $2.99986 trillion | Octagon Companies Agent |
| Microsoft | MSFT | $3.143 trillion | Companies Market Cap |
| Alphabet | GOOGL | $2.00018 trillion | Octagon Companies Agent |
Data Sources: octagon-companies-agent, octagon-financials-agent, octagon-web-search-agent
4. Interpret Results
See references/interpreting-results.md for guidance on:
- Comparing market caps across companies
- Understanding size categories
- Analyzing relative valuations
- Tracking market cap changes
Example Queries
Basic Batch Query:
Retrieve market capitalization data for the following companies: AAPL, MSFT, GOOG.Sector Comparison:
Get market caps for tech giants: AAPL, MSFT, GOOGL, AMZN, META, NVDA.Portfolio Analysis:
What are the market capitalizations of TSLA, F, GM, and RIVN?Industry Comparison:
Compare market caps of major banks: JPM, BAC, WFC, C, GS.Index Components:
Get market caps for the top 10 S&P 500 companies by weight.International Comparison:
Compare market caps of AAPL, SMSN.IL (Samsung), TSM, and ASML.Market Cap Categories
Size Classifications
| Category | Market Cap Range |
|---|---|
| Mega-cap | >$200 billion |
| Large-cap | $10B - $200B |
| Mid-cap | $2B - $10B |
| Small-cap | $300M - $2B |
| Micro-cap | $50M - $300M |
| Nano-cap | <$50M |
Category Characteristics
| Category | Typical Traits |
|---|---|
| Mega-cap | Market leaders, global reach, stable |
| Large-cap | Established, diversified, moderate growth |
| Mid-cap | Growth potential, less coverage |
| Small-cap | Higher growth, higher volatility |
| Micro-cap | Speculative, limited liquidity |
Comparative Analysis Framework
Peer Comparison
| Analysis | Purpose |
|---|---|
| Absolute Size | Rank by market cap |
| Relative Size | Ratio to peers |
| Size Distribution | Concentration analysis |
| Historical Rank | Position changes |
Industry Context
| Comparison | What It Shows |
|---|---|
| vs. Industry Leader | Distance from top |
| vs. Industry Median | Above/below average |
| vs. Sector Total | Market share proxy |
Valuation Implications
| Scenario | Interpretation |
|---|---|
| Higher market cap, lower revenue | Premium valuation |
| Lower market cap, higher revenue | Discount valuation |
| Similar market cap, different earnings | P/E differential |
Use Cases
Portfolio Allocation
| Use | Description |
|---|---|
| Concentration Analysis | Largest holdings by cap |
| Diversification Check | Size mix across holdings |
| Rebalancing | Adjust for cap changes |
Show full SKILL.md (218 more words)Show less
Competitive Analysis
| Use | Description |
|---|---|
| Market Leadership | Largest in industry |
| Relative Positioning | Size vs. competitors |
| Growth Comparison | Cap changes over time |
Screening
| Use | Description |
|---|---|
| Size Filter | Include/exclude by cap |
| Category Selection | Target specific sizes |
| Index Eligibility | Meets cap requirements |
Market Cap Calculations
Basic Formula
Market Cap = Share Price × Shares OutstandingFactors Affecting Market Cap
| Factor | Impact |
|---|---|
| Price Change | Direct proportional effect |
| Share Buybacks | Reduces shares, concentrates value |
| New Issuance | Dilutes if price doesn't rise |
| Stock Splits | No effect (price adjusts) |
Fully Diluted Market Cap
| Component | Description |
|---|---|
| Basic Shares | Currently outstanding |
| Options | Employee stock options |
| Warrants | Convertible instruments |
| Convertibles | Convertible debt/preferred |
Data Considerations
Source Variations
| Factor | Consideration |
|---|---|
| Timing | Real-time vs. delayed data |
| Currency | USD conversion rates |
| Share Count | Basic vs. diluted |
| Updates | Frequency of refresh |
Handling Discrepancies
| Issue | Approach |
|---|---|
| Different sources | Note the variance |
| Different dates | Use consistent timing |
| Currency mix | Convert to single currency |
| Missing data | Flag unavailable items |
Analysis Tips
Use consistent data: Same source/date for fair comparison.
Consider context: Industry norms for market cap.
Track changes: Market cap shifts over time.
Combine with fundamentals: P/E, P/S for valuation context.
Watch for outliers: Investigate unusual sizes.
Global perspective: Different markets, different scales.
Integration with Other Skills
| Skill | Combined Use |
|---|---|
| stock-quote | Market cap + current price |
| income-statement | Market cap vs. revenue/earnings |
| financial-metrics-analysis | Valuation multiples |
| analyst-estimates | Market cap vs. price targets |
© OctagonAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 4 other files (references) in skills/batch-market-cap of OctagonAI/skills.
- SKILL.md
- README.md
- marketplace.json
- references/interpreting-results.md
- references/mcp-setup.md
Open the folder on GitHubat commit 51e938c
Compare with similar skills
Batch Market Cap 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 |
|---|---|---|---|---|---|---|
| Batch Market Cap this skillOctagonAI/skills | 127 | — | ~1.6k | Automated safety check: Pass | MIT | |
| Creating Financial ModelsChen-zexi/open-ptc-agent | 729 | 3 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Stock APIzhangxiangliang/stock-api | 2k | — | ~507 | Automated safety check: Pass | MIT | |
| Tradingview MCPatilaahmettaner/tradingview-mcp | 5k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Dr Manhattanguzus/dr-manhattan | 204 | — | ~2k | Automated safety check: Pass | Apache-2.0 | |
| Agentic Trading DeskOft3r/agentic-trading-desk | 306 | — | ~5.1k | Automated safety check: Pass | MIT |
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Questions about Batch Market Cap
What does Batch Market Cap do?
Retrieve market capitalization data for multiple companies at once using Octagon MCP. Batch Market Cap is an agent skill from OctagonAI/skills. Retrieve market capitalization data for multiple companies at once using Octagon MCP.
When should I use Batch Market Cap?
Batch Market Cap fits situations like: comparing valuations across peers; screening by market cap; analyzing a portfolios composition by company size.
How do I install Batch Market Cap in Claude Code?
Run `npx skills add OctagonAI/skills --skill batch-market-cap -a claude-code`. Or copy the skill folder (skills/batch-market-cap in OctagonAI/skills) into .claude/skills/batch-market-cap in your project. Claude Code loads it when a task matches its description.
How do I install Batch Market Cap in Codex?
Run `npx skills add OctagonAI/skills --skill batch-market-cap -a codex`. Or copy the skill folder (skills/batch-market-cap in OctagonAI/skills) into .agents/skills/batch-market-cap in your project. Codex loads it when a task matches its description.
Can I use Batch Market Cap in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add OctagonAI/skills --skill batch-market-cap -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/batch-market-cap, .gemini/skills/batch-market-cap, .github/skills/batch-market-cap and .opencode/skills/batch-market-cap in your project.
What does Batch Market Cap need to run?
SKILL.md names no scripts, command-line tools or credentials: Batch Market Cap is instructions for the agent only.
Does Batch Market Cap access the network?
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.
Is Batch Market Cap safe to install?
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.
What licence does Batch Market Cap use?
Batch Market Cap is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Batch Market Cap use?
About 1.6k tokens (SKILL.md is roughly 6.3k 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 2.2k tokens, read only when the agent opens those files.
What are the alternatives to Batch Market Cap?
Skills that share tags, products or a category with Batch Market Cap: Creating Financial Models (Chen-zexi/open-ptc-agent, 729 stars), Stock API (zhangxiangliang/stock-api, 2k stars), Tradingview MCP (atilaahmettaner/tradingview-mcp, 5k stars) and Dr Manhattan (guzus/dr-manhattan, 204 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Batch Market Cap?
OctagonAI (a GitHub organization) maintains it in OctagonAI/skills, which has 127 GitHub stars. The repository holds 53 skills in this directory. The repository was last updated on June 5, 2026.
Source: OctagonAI/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.