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 MerkyorLynn/Lynn --skill stock-analysisgit clone --depth 1 https://github.com/MerkyorLynn/LynnWrote 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/merkyorlynn/lynn/stock-analysis)<a href="https://agentmods.dev/skills/merkyorlynn/lynn/stock-analysis"><img src="https://agentmods.dev/badge/skills/merkyorlynn/lynn/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/merkyorlynn/lynn/stock-analysis"><img src="https://agentmods.dev/badge/skills/merkyorlynn/lynn/stock-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00070 | $0.02272 |
| Opus 5 | $0.00035 | $0.01136 |
| Sonnet 5 | $0.00014 | $0.00454 |
| Haiku 4.5 | $0.00007 | $0.00227 |
Grade A, and why
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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 249 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Stock Analysis v6.1
Analyze US stocks and cryptocurrencies with 8-dimension analysis, portfolio management, watchlists, alerts, dividend analysis, and viral trend detection.
What's New in v6.2
- 🔮 Rumor Scanner — Early signals before mainstream news
- M&A rumors and takeover bids
- Insider buying/selling activity
- Analyst upgrades/downgrades
- Twitter/X "hearing that...", "sources say..." detection
- 🎯 Impact Scoring — Rumors ranked by potential market impact
What's in v6.1
- 🔥 Hot Scanner — Find viral stocks & crypto across multiple sources
- 🐦 Twitter/X Integration — Social sentiment via bird CLI
- 📰 Multi-Source Aggregation — CoinGecko, Google News, Yahoo Finance
- ⏰ Cron Support — Daily trend reports
What's in v6.0
- 🆕 Watchlist + Alerts — Price targets, stop losses, signal changes
- 🆕 Dividend Analysis — Yield, payout ratio, growth, safety score
- 🆕 Fast Mode —
--fastskips slow analyses (insider, news) - 🆕 Improved Performance —
--no-insiderfor faster runs
Quick Commands
Stock Analysis
# Basic analysis
uv run {baseDir}/scripts/analyze_stock.py AAPL
# Fast mode (skips insider trading & breaking news)
uv run {baseDir}/scripts/analyze_stock.py AAPL --fast
# Compare multiple
uv run {baseDir}/scripts/analyze_stock.py AAPL MSFT GOOGL
# Crypto
uv run {baseDir}/scripts/analyze_stock.py BTC-USD ETH-USD
Dividend Analysis (NEW v6.0)
# Analyze dividends
uv run {baseDir}/scripts/dividends.py JNJ
# Compare dividend stocks
uv run {baseDir}/scripts/dividends.py JNJ PG KO MCD --output json
Dividend Metrics:
- Dividend Yield & Annual Payout
- Payout Ratio (safe/moderate/high/unsustainable)
- 5-Year Dividend Growth (CAGR)
- Consecutive Years of Increases
- Safety Score (0-100)
- Income Rating (excellent/good/moderate/poor)
Watchlist + Alerts (NEW v6.0)
# Add to watchlist
uv run {baseDir}/scripts/watchlist.py add AAPL
# With price target alert
uv run {baseDir}/scripts/watchlist.py add AAPL --target 200
# With stop loss alert
uv run {baseDir}/scripts/watchlist.py add AAPL --stop 150
# Alert on signal change (BUY→SELL)
uv run {baseDir}/scripts/watchlist.py add AAPL --alert-on signal
# View watchlist
uv run {baseDir}/scripts/watchlist.py list
# Check for triggered alerts
uv run {baseDir}/scripts/watchlist.py check
uv run {baseDir}/scripts/watchlist.py check --notify # Telegram format
# Remove from watchlist
uv run {baseDir}/scripts/watchlist.py remove AAPL
What ships with it
16 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.
- _meta.json 133 B
- App-Plan.md 14 KB
- docs/ARCHITECTURE.md 16 KB
- docs/CONCEPT.md 8.9 KB
- docs/HOT_SCANNER.md 5.7 KB
- docs/README.md 2.3 KB
- docs/USAGE.md 8.7 KB
- README.md 6.2 KB
- scripts/analyze_stock.py 88 KB runs code
- scripts/dividends.py 13 KB runs code
- scripts/hot_scanner.py 24 KB runs code
- scripts/portfolio.py 18 KB runs code
- scripts/rumor_scanner.py 11 KB runs code
- scripts/test_stock_analysis.py 12 KB runs code
- scripts/watchlist.py 11 KB runs code
- TODO.md 13 KB
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.
- 10d ago First seen · 249 lines · 70 tokens per session scan A 6ae566bdf7f0
stock-analysis is a skill published in the GitHub repository MerkyorLynn/Lynn (43 stars, last pushed yesterday), licensed Apache-2.0. It adds 70 tokens to every session and 2,272 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.
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