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 leecyno1/boutique-skills --skill alphagbm-unusual-activitygit clone --depth 1 https://github.com/leecyno1/boutique-skillsWrote 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/leecyno1/boutique-skills/alphagbm-unusual-activity)<a href="https://agentmods.dev/skills/leecyno1/boutique-skills/alphagbm-unusual-activity"><img src="https://agentmods.dev/badge/skills/leecyno1/boutique-skills/alphagbm-unusual-activity/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/leecyno1/boutique-skills/alphagbm-unusual-activity"><img src="https://agentmods.dev/badge/skills/leecyno1/boutique-skills/alphagbm-unusual-activity.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 | $0.00097 | $0.00790 |
| Opus 5 | $0.00048 | $0.00395 |
| Sonnet 5 | $0.00019 | $0.00158 |
| Haiku 4.5 | $0.00010 | $0.00079 |
Grade A, and why
alphagbm-unusual-activity 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.
This is a copy
100% identical to alphagbm-unusual-activity — 0 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AlphaGBM Unusual Options Activity
Detects unusual options activity and classifies smart money signals to help you follow institutional positioning.
What This Skill Does
| Concept | Description |
|---|---|
| Volume/OI Ratio | When today's volume far exceeds open interest, it signals new positioning |
| Block Trade | A single large transaction (typically 100+ contracts) executed at one price |
| Sweep Order | Aggressive order that sweeps across multiple exchanges to get filled fast — indicates urgency |
| Premium Flow | Net dollar amount of call vs put premium — shows directional conviction |
| Sentiment Classification | Categorizes activity as bullish sweep, bearish block, hedging, or earnings positioning |
| Historical Accuracy | How often past unusual activity correctly predicted direction |
How to Use
Input: A ticker symbol or market-wide scan request.
Output:
- Unusual activity list: timestamp, strike, expiry, type (call/put), volume, OI, premium, trade classification
- Sentiment classification per trade (bullish sweep, bearish block, hedging, earnings positioning)
- Net premium flow (calls vs puts in dollar terms)
- Historical accuracy: how often similar signals preceded the expected move
- Aggregated smart money score
Example Queries:
unusual options activity— Market-wide scan of today's most unusual tradessmart money AAPL— Institutional flow signals for Applelarge trades NVDA— Block and sweep orders for NVIDIAwho's buying TSLA puts— Bearish flow analysis for Teslaoptions flow SPY— Net premium flow for S&P 500 ETF
Mock Data
Mock data files are located in mock-data/unusual-activity/ and include:
aapl-unusual-trades.json— Recent unusual trades for AAPLmarket-wide-scan.json— Top 20 unusual activity signals across all tickersflow-summary.json— Aggregated premium flow by sector
API Endpoint
GET /api/options/unusual-activity/{symbol}
GET /api/options/unusual-activity/scan
What ships with it
17 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.
- LICENSE 1.0 KB
- mock-data/AAPL.json 6.7 KB
- mock-data/buffett-analysis/example-ko.json 1.9 KB
- mock-data/fear-score/example-calm.json 661 B
- mock-data/fear-score/example-signal-triggered.json 663 B
- mock-data/hedge-advisor/example-gain-protection.json 1.5 KB
- mock-data/marks-cycle/example-neutral.json 366 B
- mock-data/META.json 8.8 KB
- mock-data/NVDA.json 8.4 KB
- mock-data/SPY.json 7.5 KB
- mock-data/take-profit/example-leveraged-etf.json 1.1 KB
- mock-data/tepper-signal/example-armed.json 589 B
- mock-data/tepper-signal/example-cold.json 488 B
- mock-data/TSLA.json 9.4 KB
- mock-data/vix-status/example-extreme-fear.json 528 B
- mock-data/vix-status/example-sweet-spot.json 506 B
- SOURCE.txt 455 B
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 · 78 lines · 97 tokens per session scan A 60a4b39e5368
alphagbm-unusual-activity is a skill published in the GitHub repository leecyno1/boutique-skills (5 stars, last pushed today), licensed MIT. It adds 97 tokens to every session and 790 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to alphagbm-unusual-activity, differing in 0 lines, and is treated as a copy.
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.
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.
reading-receipt
An image-reading workflow for extracting structured information from receipts, invoices, and hometown-tax donation certificates. It can first extract text from PDFs and otherwise read their images.