Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/SKYLENAGE-AI/QwenClawBenchnpx agentmods add skills/skylenage-ai/qwenclawbench/stock-alertsWrote 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/skylenage-ai/qwenclawbench/stock-alerts)<a href="https://agentmods.dev/skills/skylenage-ai/qwenclawbench/stock-alerts"><img src="https://agentmods.dev/badge/skills/skylenage-ai/qwenclawbench/stock-alerts/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/skylenage-ai/qwenclawbench/stock-alerts"><img src="https://agentmods.dev/badge/skills/skylenage-ai/qwenclawbench/stock-alerts.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 | $0.00045 | $0.00272 |
| Opus 5 | $0.00023 | $0.00136 |
| Sonnet 5 | $0.00009 | $0.00054 |
| Haiku 4.5 | $0.00005 | $0.00027 |
Grade A, and why
stock-alerts 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 12d 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.
What it actually says
Stock Alerts Skill
Monitor stock prices and send alerts when thresholds are crossed.
When to Use
✅ USE this skill when:
- "Alert me when AAPL drops below $150"
- "Notify me if 000001.SZ goes above 15 CNY"
- "Set a price alert for Tesla"
Commands
Set Alert
python3 skills/stock-alerts/scripts/alert.py set --symbol AAPL --condition below --price 150.00
List Alerts
python3 skills/stock-alerts/scripts/alert.py list
Remove Alert
python3 skills/stock-alerts/scripts/alert.py remove --id 3
Notes
- Checks run on heartbeat intervals (not real-time)
- Stores alerts in
data/stock-alerts.json - Works with any market data skill (tushare, yahoo, etc.)
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.
- 12d ago First seen · 48 lines · 45 tokens per session scan A afe3e6526102
stock-alerts is a skill published in the GitHub repository SKYLENAGE-AI/QwenClawBench (60 stars, last pushed 3mo ago), licensed MIT. It adds 45 tokens to every session and 272 once invoked, about $0.0002 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
sector-rotation
An analysis framework for comparing industries in the Chinese A-share stock market, using business conditions, price momentum, valuation, and money flows. It produces rankings and higher- or lower-allocation suggestions.
strategy-pivot-designer
Detect backtest iteration stagnation and generate structurally different strategy pivot proposals when parameter tuning reaches a local optimum.
twitter-reader
Read Twitter/X for financial research using opencli (read-only). Use this skill whenever the user wants to read their Twitter feed, search for financial tweets, view bookmarks, look up user profiles, or gather market sentiment from Twitter/X. Triggers include: "check my feed", "search Twitter for", "show my…
chenhao-limit-up
A framework for judging Chinese A-share stocks that have reached the daily price-rise limit, using market mood, sector leadership, and trading momentum.
trading-risk-gate
Unified pre-trade safety gate: Ruin check (Law #1), ergodicity audit, and win-rate dominance validation. Absorbs: ergodicity-check, law-of-ruin, win-rate-dominance.
furusato
A Japanese hometown-tax donation manager for furusato nozei, a system where donations to municipalities can qualify for an income-tax or local-tax deduction. It reads donation receipts, stores donation records, and calculates deduction limits.