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 quant-scannergit 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/quant-scanner)<a href="https://agentmods.dev/skills/merkyorlynn/lynn/quant-scanner"><img src="https://agentmods.dev/badge/skills/merkyorlynn/lynn/quant-scanner.svg" alt="Measured on agentmods" 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 | $0.00090 | $0.01790 |
| Opus 5 | $0.00045 | $0.00895 |
| Sonnet 5 | $0.00018 | $0.00358 |
| Haiku 4.5 | $0.00009 | $0.00179 |
Grade A, and why
quant-scanner 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 7d 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 — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Quant Scanner v1.0
Model-driven quantitative stock scanner for US equities. Scans ~100 large/mid-cap stocks, detects the current market regime, adaptively adjusts 5-factor scoring weights, and outputs ranked picks with an HTML report.
Setup
Required: A free Finnhub API key.
- Go to https://finnhub.io and sign up (free)
- Copy your API key from the dashboard
- Set it as an environment variable:
export FINNHUB_API_KEY="your_key_here"
Or pass it directly via --api-key:
python3 {baseDir}/scripts/quant_scan.py --api-key YOUR_KEY
Quick Commands
Full Scan (HTML + JSON report)
python3 {baseDir}/scripts/quant_scan.py
This will:
- Fetch quote, metrics, profile, and analyst recommendations for ~100 stocks
- Detect market regime (volatility, momentum, breadth)
- Score each stock on 5 adaptive factors
- Output a ranked list + HTML report
Quick Top 10
python3 {baseDir}/scripts/quant_scan.py --top 10
Specific Tickers Only
python3 {baseDir}/scripts/quant_scan.py --tickers AAPL,NVDA,TSLA,GOOGL,META
Custom Universe File
python3 {baseDir}/scripts/quant_scan.py --universe my_watchlist.txt
Where my_watchlist.txt has one ticker per line.
JSON Output Only (for piping)
python3 {baseDir}/scripts/quant_scan.py --format json
How It Works
5-Factor Adaptive Scoring
Each stock is scored on 5 factors. The weights adapt to the detected market regime:
| Factor | Base Weight | Bullish Adj | Bearish Adj | High-Vol Adj |
|---|---|---|---|---|
| Momentum (5D/13W/MTD return + relative strength vs S&P 500) | 30% | x1.3 boost | x0.7 dampen | — |
| Value (P/E, forward P/E, PEG, dividend yield) | 20% | x0.8 reduce | x1.3 boost | — |
| Quality (ROE, net margin, revenue growth, EPS growth) | 25% | — | — | x1.2 boost |
| Analyst Sentiment (buy/hold/sell consensus ratio) | 10% | — | — | — |
| Risk-Adjusted (beta, volatility, leverage, liquidity) | 15% | — | — | x1.4 penalty |
What ships with it
2 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.
- 7d ago First seen · 182 lines · 90 tokens per session scan A 887cdc5222d3
quant-scanner is a skill published in the GitHub repository MerkyorLynn/Lynn (42 stars, last pushed yesterday), licensed Apache-2.0. It adds 90 tokens to every session and 1,790 once invoked, about $0.0005 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 skills, from other repositories
cua-driver
Drive a native GUI app (macOS, Windows, Linux) via the Qwen Cua Driver CLI (default) or MCP server; snapshot its accessibility tree, act through snapshot-bound element tokens, native menu paths, exact window geometry, or pixel coordinates, and verify from fresh state. Use when the user asks you to operate, drive…
codegraph
Analyze indexed codebases via graph database (neug) and vector index (zvec). Covers call graphs, dependencies, dead code, hotspots, module coupling, architecture reports, semantic search, impact analysis, bug root cause from GitHub issues, class diagrams (UML), and PR review (risk scoring, conflict detection…
stuck
Diagnose frozen, stuck, or slow Qwen Code sessions on this machine. Scans for problematic processes, high CPU/memory usage, hung subprocesses, and debug logs. Use /stuck or /stuck to focus on a specific process.
tmux-real-user-testing
A real-user test workflow for Qwen Code's terminal interface, using tmux to drive the program and capture readable screen snapshots. tmux is a tool for running and observing terminal sessions.
batch
Execute batch operations on multiple files in parallel. Automatically discovers files, splits into chunks, and processes with parallel worker agents. Use /batch followed by operation and file pattern.
goal-draft
Turn a fuzzy intention into a /goal objective the Goal verifier can actually judge - one outcome, numbered binary "Done when" checks that leave evidence in the transcript, guardrails, a budget, and a block protocol. Use when the user wants to set or define a goal, asks whether a goal is good enough, or says "keep…