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-hedge-advisorgit 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-hedge-advisor)<a href="https://agentmods.dev/skills/leecyno1/boutique-skills/alphagbm-hedge-advisor"><img src="https://agentmods.dev/badge/skills/leecyno1/boutique-skills/alphagbm-hedge-advisor/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-hedge-advisor"><img src="https://agentmods.dev/badge/skills/leecyno1/boutique-skills/alphagbm-hedge-advisor.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 | $0.00140 | $0.01479 |
| Opus 5 | $0.00070 | $0.00740 |
| Sonnet 5 | $0.00028 | $0.00296 |
| Haiku 4.5 | $0.00014 | $0.00148 |
Grade A, and why
alphagbm-hedge-advisor 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-hedge-advisor — 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 — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AlphaGBM Hedge Advisor
"I own AAPL at $140 and it's now $180 — how do I protect the gains?"
Takes that question literally. Given a ticker + cost basis + position purpose, the skill classifies the holding into one of four scenarios and returns ready-to-trade hedge specs with strikes and costs already resolved from the live option chain.
Scenarios
| Scenario | Trigger | Recommended Hedge |
|---|---|---|
| Falling Knife | Recent drawdown ≥ 15% from 30-day high AND PnL ≤ +5% | Long Put 5% OTM, 75 DTE, 100% cover, budget ~5% |
| Bottom Fishing | PnL within ±8% of cost AND purpose = just_bought or long_term | Long Put 5% OTM, 90 DTE, 50-75% cover, budget ~3% |
| Gain Protection | PnL ≥ 15% | Collar 95/110 (zero-cost or net-credit) + Tier-down as alternative |
| Normal Hold | Fallback when no scenario fires | Position rules only, no urgent hedge |
What's Returned
For each recommendation spec, the skill resolves actual strikes and prices from the live option chain:
- Long Put: strike, DTE,
cost_per_share,cost_per_contract,cost_pct_of_spot, delta, IV - Collar:
long_put_strike,short_call_strike,put_cost,call_credit,net_cost_per_share(negative = you receive a credit), breakeven analysis - Tier-down / Position rules: static rules copy only
Also returns a position_rules[] array (single-name ≤20%, sector ≤30-35%, cash
reserve 10-15%, etc.) for the normal-hold case.
How to Use
Input:
ticker(required)cost_basis(required, float — your average entry price)purpose(optional, defaultlong_term) — one oflong_term / short_term / pre_earnings / just_bought
Output:
- Scenario label + reason (zh/en)
- Current price, cost basis, unrealized P&L %, recent drawdown %
recommendations[]— each with type, priority, title, rationale, andresolvedblock containing the actual priced hedgeposition_rules[]— always-applicable sizing rules
Example Queries:
hedge my AAPL at $140, now it's $180→ Gain Protection → Collar 95/110 quoteI just bought NVDA at $110 on the dip, should I hedge?→ Falling Knife or Bottom Fishing → Long Put 5% OTM 60-90 DTEhow to protect my TSLA position→ Gain Protection or Bottom Fishing based on PnLcollar MSFT at cost 340 current 410→ Full collar pricing
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 452 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 · 143 lines · 140 tokens per session scan A 4287a30377f1
alphagbm-hedge-advisor is a skill published in the GitHub repository leecyno1/boutique-skills (5 stars, last pushed today), licensed MIT. It adds 140 tokens to every session and 1,479 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to alphagbm-hedge-advisor, differing in 0 lines, and is treated as a copy.
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