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-stock-analysisgit 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-stock-analysis)<a href="https://agentmods.dev/skills/leecyno1/boutique-skills/alphagbm-stock-analysis"><img src="https://agentmods.dev/badge/skills/leecyno1/boutique-skills/alphagbm-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/leecyno1/boutique-skills/alphagbm-stock-analysis"><img src="https://agentmods.dev/badge/skills/leecyno1/boutique-skills/alphagbm-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 | $0.00120 | $0.01608 |
| Opus 5 | $0.00060 | $0.00804 |
| Sonnet 5 | $0.00024 | $0.00322 |
| Haiku 4.5 | $0.00012 | $0.00161 |
Grade A, and why
alphagbm-stock-analysis scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -H "Authorization: Bearer $ALPHAGBM_API_KEY" \ This is a copy
100% identical to alphagbm-stock-analysis — 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 — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AlphaGBM Stock Analysis
Analyze stocks via the AlphaGBM API — a G = B + M (Gain = Basics + Momentum) model combining fundamental analysis, market sentiment, EV expectation, ATR stop-loss, sector rotation, and AI reports.
When to use
- User asks to analyze a stock ticker (US / HK / A-share)
- User asks for a stock quote, target price, risk score, or EV recommendation
- User mentions AlphaGBM or wants a comprehensive stock analysis
Prerequisites
- API Key: stored in env
ALPHAGBM_API_KEY(formatagbm_xxxx…). - Base URL: default
https://alphagbm.zeabur.app. Override with envALPHAGBM_BASE_URL. - If the user has neither, tell them to register at https://alphagbm.com and create a key at
/api-keys.
API Endpoints
All endpoints require Authorization: Bearer $ALPHAGBM_API_KEY.
1. Quick Quote (instant, no quota cost)
GET /api/stock/quick-quote/<TICKER>
Returns: price, change%, PE, forward PE, 52-week range, sector, market cap.
Example:
curl -H "Authorization: Bearer $ALPHAGBM_API_KEY" \
https://alphagbm.zeabur.app/api/stock/quick-quote/AAPL
2. Full Stock Analysis — Synchronous (blocks 10-30s)
POST /api/stock/analyze-sync
Content-Type: application/json
{"ticker": "AAPL", "style": "balanced"}
| Parameter | Type | Required | Description |
|---|---|---|---|
ticker |
string | yes | Stock ticker (e.g. AAPL, 0700.HK, 600519.SS) |
style |
string | no | quality (default), value, growth, momentum, balanced |
Add ?compact=true for a condensed agent-friendly response (~500 tokens).
Response contains:
data— price, PE, PEG, growth, margin, target_price, stop_loss_price, market_sentiment (0-10), ev_model, sector_analysis, capital_analysisrisk— score (0-10), level, suggested_position%, risk flagsreport— AI-generated narrative report (markdown, ~2000 chars)
3. Full Stock Analysis — Async (for web frontend)
POST /api/stock/analyze-async
Content-Type: application/json
{"ticker": "TSLA", "style": "growth"}
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 453 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 · 190 lines · 120 tokens per session scan A a399a97880f0
alphagbm-stock-analysis is a skill published in the GitHub repository leecyno1/boutique-skills (5 stars, last pushed today), licensed MIT. It adds 120 tokens to every session and 1,608 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 100% identical to alphagbm-stock-analysis, 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.