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-tepper-signalgit 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-tepper-signal)<a href="https://agentmods.dev/skills/leecyno1/boutique-skills/alphagbm-tepper-signal"><img src="https://agentmods.dev/badge/skills/leecyno1/boutique-skills/alphagbm-tepper-signal/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-tepper-signal"><img src="https://agentmods.dev/badge/skills/leecyno1/boutique-skills/alphagbm-tepper-signal.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 | $0.00193 | $0.01412 |
| Opus 5 | $0.00097 | $0.00706 |
| Sonnet 5 | $0.00039 | $0.00282 |
| Haiku 4.5 | $0.00019 | $0.00141 |
Grade A, and why
alphagbm-tepper-signal 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-tepper-signal — 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 — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AlphaGBM Tepper Panic-Buy Signal
David Tepper made two historic panic-bottom calls: March 2009 ("I'm betting on the Fed") and March 2020 (COVID bottom). Both had identical fingerprints: VIX spiked > 40, multi-indicator fear was maxed, and Tepper loaded quality large-caps (banks 2009, SPY/QQQ 2020).
This skill mechanizes that fingerprint.
The Signal Logic
Three gates must all pass for the signal to arm:
- VIX ≥ 35 — extreme fear, not just elevated
- FearScore ≥ 80 — multi-indicator panic (reuses existing FearScore module: VIX + IV Rank + RSI + Volume + Put/Call + Consec-Down-Days)
- Quality filter — market cap > $50B AND profit margin > 0 (no memes, concept stocks, or pre-revenue small caps)
When all three pass → signal: true, level: armed.
Signal Levels
| Level | Condition | Prescription |
|---|---|---|
armed |
VIX ≥ 35 AND Fear ≥ 80 | 🔥 Historic-level buying moment — scale into SPY/QQQ/DIA |
watch |
VIX ≥ 30 OR Fear ≥ 70 | ⚡ Approaching — prepare capital, don't act yet |
near |
VIX ≥ 25 OR Fear ≥ 60 | Lukewarm — far from Tepper-level panic |
cold |
below | Calm — the patience state, which is most of the time |
Tepper's own framework includes "do nothing" as a first-class state. Most
calls to this endpoint will return cold — that's by design. The value isn't
in the signal firing often, it's in never missing a VIX > 40 event.
Why This Is a Separate Skill
alphagbm-fear-score gives the raw panic index. alphagbm-vix-status gives
the VIX tier. This skill combines them with Tepper's specific criteria
(quality filter + threshold rules) to produce a single yes/no decision.
How to Use
Input:
ticker(optional, defaultSPY) — the quality-filter applies to this ticker
Output:
vix,fear_score— the two input signalsvix_pass,fear_pass,quality_pass— per-gate booleanssignal— final booleanlevel—armed / watch / near / coldrecommended_etfs—["SPY", "QQQ", "DIA"](quality large-cap universe)advice_zh,advice_en— natural-language prescription
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 · 129 lines · 193 tokens per session scan A 6a3e33c3c994
alphagbm-tepper-signal is a skill published in the GitHub repository leecyno1/boutique-skills (5 stars, last pushed today), licensed MIT. It adds 193 tokens to every session and 1,412 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to alphagbm-tepper-signal, differing in 0 lines, and is treated as a copy.
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