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.
npx skills add nicepkg/ai-workflow --skill us-stock-analysisgit clone --depth 1 https://github.com/nicepkg/ai-workflowWrote 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/skills/nicepkg/ai-workflow/us-stock-analysis)<a href="https://agentmods.dev/skills/nicepkg/ai-workflow/us-stock-analysis"><img src="https://agentmods.dev/badge/skills/nicepkg/ai-workflow/us-stock-analysis/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/skills/nicepkg/ai-workflow/us-stock-analysis"><img src="https://agentmods.dev/badge/skills/nicepkg/ai-workflow/us-stock-analysis.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 | $0.00094 | $0.02168 |
| Opus 5.5 | $0.00038 | $0.00867 |
| Sonnet 5.5 | $0.00019 | $0.00434 |
| Haiku 4.5 | $0.00009 | $0.00217 |
Grade A, and why
us-stock-analysis 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 1mo 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.
This is a copy
100% identical to us-stock-analysis — 28 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 295 lines — stays where its author put it; the contents beside it link to each section on GitHub.
US Stock Analysis
Overview
Perform comprehensive analysis of US stocks covering fundamental analysis (financials, business quality, valuation), technical analysis (indicators, trends, patterns), peer comparisons, and generate detailed investment reports. Fetch real-time market data via web search tools and apply structured analytical frameworks.
Data Sources
Always use web search tools to gather current market data:
Primary Data to Fetch:
- Current stock price and trading data (price, volume, 52-week range)
- Financial statements (income statement, balance sheet, cash flow)
- Key metrics (P/E, EPS, revenue, margins, debt ratios)
- Analyst ratings and price targets
- Recent news and developments
- Peer/competitor data (for comparisons)
- Technical data (moving averages, RSI, MACD when available)
Search Strategy:
- Use ticker symbol + specific data needed (e.g., "AAPL financial metrics 2024")
- For comprehensive data: Search for earnings reports, investor presentations, or SEC filings
- For technical data: Search for "AAPL technical analysis" or use financial data sites
- Always verify data recency (prefer data from last quarter)
Quality Sources:
- Yahoo Finance, Google Finance, MarketWatch, Seeking Alpha, Bloomberg, CNBC
- Company investor relations pages
- SEC filings (10-K, 10-Q) for detailed financials
- TradingView, StockCharts for technical data
Analysis Types
This skill supports four types of analysis. Determine which type(s) the user needs:
- Basic Stock Info - Quick overview with key metrics
- Fundamental Analysis - Deep dive into business, financials, valuation
- Technical Analysis - Chart patterns, indicators, trend analysis
- Comprehensive Report - Complete analysis combining all approaches
Analysis Workflows
1. Basic Stock Information
When to Use: User asks for quick overview or basic info
Steps:
- Search for current stock data (price, volume, market cap)
- Gather key metrics (P/E, EPS, revenue growth, margins)
- Get 52-week range and year-to-date performance
- Find recent news or major developments
- Present in concise summary format
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 295 lines · 94 tokens per session scan A 4de04c619b18
us-stock-analysis is a skill published in the GitHub repository nicepkg/ai-workflow (288 stars, last pushed 9mo ago), licensed MIT. It adds 94 tokens to every session and 2,168 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to us-stock-analysis, differing in 28 lines, and is treated as a copy.
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