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moltstreet

Daily AI signals for 52 ETFs — direction, confidence, target price, reasoning chain. Free, no API key.

fredxyt0 installations selon la source☆ 0 Étoiles du dépôt

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

skillhub install fredxyt/moltstreet

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

Instructions

MoltStreet — AI ETF Market Signals

Daily AI-generated market signals for 52 ETFs. Free, no API key needed.

When to use this skill

Activate when the user:

  • Asks about ETF market outlook, direction, or trading signals
  • Mentions any of the 52 covered ETFs by ticker (SPY, QQQ, XLK, GLD, etc.)
  • Asks "should I buy/sell [ETF]" or "what's the market doing today"
  • Wants sector comparison, portfolio analysis, or market sentiment
  • Asks about bullish/bearish signals or price targets

How to fetch signals

Single ETF signal:

curl -s https://moltstreet.com/api/v1/etf/SPY

List all available symbols (returns catalog, not signal data):

curl -s https://moltstreet.com/api/v1/etf/

This returns {"symbols": ["ASHR","DBA","DIA",...], "count": 52, ...}. To get actual signals, fetch each symbol individually.

Multiple ETFs — fetch each one:

for sym in SPY QQQ DIA IWM; do
  curl -s "https://moltstreet.com/api/v1/etf/$sym"
done

How to interpret and present

  1. Fetch the signal for the requested ETF(s)
  2. Interpret direction: 1 = bullish, -1 = bearish, 0 = neutral
  3. Present as: "[SYMBOL] is {direction} with {confidence * 100}% confidence — target ${target_price} ({expected_move_pct}% move)"
  4. Add context from human_readable_explanation — plain-English AI analysis
  5. Show conviction from committee.votes — 4 independent AI analysts voted
  6. Warn with risk_controls — what could invalidate the signal

Example agent interaction

User: "What's the outlook for tech stocks?" → Fetch XLK, QQQ, SOXX, SMH signals (4 calls) → Synthesize: "Tech sector is mixed — QQQ bearish (-1.2%, 85% conf) while SMH is bullish (+2.1%, 78% conf). The divergence is driven by..." → Add risk factors and committee consensus

User: "Any strong signals today?" → Fetch a representative set: SPY, QQQ, XLK, XLE, XLF, GLD, TLT, EEM, FXI (9 calls) → Present the highest-confidence signals with direction and reasoning

Response f...

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/fredxyt/moltstreet
Version
—
Commit
ca3c3bbdd1381e2f577ff13e3757b2a94d260f4a
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

Contenu extrait

SKILL.md
# MoltStreet — AI ETF Market Signals

Daily AI-generated market signals for 52 ETFs. Free, no API key needed.

## When to use this skill

Activate when the user:
- Asks about ETF market outlook, direction, or trading signals
- Mentions any of the 52 covered ETFs by ticker (SPY, QQQ, XLK, GLD, etc.)
- Asks "should I buy/sell [ETF]" or "what's the market doing today"
- Wants sector comparison, portfolio analysis, or market sentiment
- Asks about bullish/bearish signals or price targets

## How to fetch signals

Single ETF signal:
```bash
curl -s https://moltstreet.com/api/v1/etf/SPY
```

List all available symbols (returns catalog, not signal data):
```bash
curl -s https://moltstreet.com/api/v1/etf/
```
This returns `{"symbols": ["ASHR","DBA","DIA",...], "count": 52, ...}`. To get actual signals, fetch each symbol individually.

Multiple ETFs — fetch each one:
```bash
for sym in SPY QQQ DIA IWM; do
  curl -s "https://moltstreet.com/api/v1/etf/$sym"
done
```

## How to interpret and present

1. **Fetch** the signal for the requested ETF(s)
2. **Interpret** direction: `1` = bullish, `-1` = bearish, `0` = neutral
3. **Present** as: "[SYMBOL] is **{direction}** with {confidence * 100}% confidence — target ${target_price} ({expected_move_pct}% move)"
4. **Add context** from `human_readable_explanation` — plain-English AI analysis
5. **Show conviction** from `committee.votes` — 4 independent AI analysts voted
6. **Warn** with `risk_controls` — what could invalidate the signal

## Example agent interaction

User: "What's the outlook for tech stocks?"
→ Fetch XLK, QQQ, SOXX, SMH signals (4 calls)
→ Synthesize: "Tech sector is mixed — QQQ bearish (-1.2%, 85% conf) while SMH is bullish (+2.1%, 78% conf). The divergence is driven by..."
→ Add risk factors and committee consensus

User: "Any strong signals today?"
→ Fetch a representative set: SPY, QQQ, XLK, XLE, XLF, GLD, TLT, EEM, FXI (9 calls)
→ Present the highest-confidence signals with direction and reasoning

## Response f...

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