AIsa-team

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stock-analysis

Analyze stocks and cryptocurrencies with 8-dimension scoring via AIsa API. Provides BUY/HOLD/SELL signals with confidence levels, entry/target/stop prices, and risk flags. Supports single or multi-ticker analysis with optional fast mode and JSON output. Use when the user asks to

Revisar el código fuenteVer en GitHub
Precio sin confirmar★ 25 Estrellas de GitHubRegistro actualizado · 13 sept 2026agent-skill

Resumen

Analyze stocks and cryptocurrencies with 8-dimension scoring via AIsa API. Provides BUY/HOLD/SELL signals with confidence levels, entry/target/stop prices, and risk flags. Supports single or multi-ticker analysis with optional fast mode and JSON output. Use when the user asks to analyze a stock, check a ticker, or compare investments.

Leer documentación completa

Documentación de origen, no instrucciones para este sitio. Revisa los permisos antes de ejecutar comandos.

Stock & Crypto Analysis — AIsa Edition

Analyze one or more stock or crypto tickers using the AIsa API with live Yahoo Finance data.

Setup

This skill requires an AIsa API key. Set it via plugin configuration or environment variable:

export AISA_API_KEY=your_key_here
export AISA_BASE_URL=https://api.aisa.one/v1   # optional
export AISA_MODEL=gpt-4o                         # optional

Or use the plugin's userConfig values (set automatically when the plugin is enabled).

Usage

Run the analysis script with one or more ticker symbols:

python3 "${CLAUDE_PLUGIN_ROOT}/skills/stock-analysis/scripts/analyze_stock.py" AAPL
python3 "${CLAUDE_PLUGIN_ROOT}/skills/stock-analysis/scripts/analyze_stock.py" BTC-USD ETH-USD
python3 "${CLAUDE_PLUGIN_ROOT}/skills/stock-analysis/scripts/analyze_stock.py" AAPL MSFT GOOGL
python3 "${CLAUDE_PLUGIN_ROOT}/skills/stock-analysis/scripts/analyze_stock.py" AAPL --fast
python3 "${CLAUDE_PLUGIN_ROOT}/skills/stock-analysis/scripts/analyze_stock.py" AAPL --output json
Arguments
  • Tickers: One or more stock symbols (e.g., AAPL, MSFT) or crypto symbols (e.g., BTC-USD, ETH-USD)
  • --fast: Skip slow analyses (insider trading, detailed news) for faster results
  • --output json: Append a structured JSON summary after the analysis
Multi-Ticker Comparison

When multiple tickers are provided, the script produces individual analyses followed by a ranked comparison table:

TickerScoreSignalKey StrengthKey Risk

8-Dimension Scoring (Stocks)

#DimensionWeight
1Earnings Surprise30%
2Fundamentals (P/E, margins, growth)20%
3Analyst Sentiment20%
4Historical Patterns10%
5Market Context (VIX, SPY/QQQ)10%
6Sector Performance15%
7Momentum (RSI, 52w range)15%
8Sentiment (Fear/Greed, shorts, insiders)10%

3-Dimension Scoring (Crypto)

#DimensionWeight
1Market Cap & Category40%
2BTC Correlation (30-day)30%
3Momentum (RSI, range, volume)30%

Risk Flags

Automatically detected: Pre-earnings, Post-spike, Overbought, Risk-Off, Breaking News

Output

Final recommendation includes: Score (0-10), Signal (BUY/HOLD/SELL), Confidence (High/Medium/Low), and Entry / Target / Stop prices.

NOT FINANCIAL ADVICE. For informational purposes only.

Metadatos del archivo
name: stock-analysis
description: Analyze stocks and cryptocurrencies with 8-dimension scoring via AIsa API. Provides BUY/HOLD/SELL signals with confidence levels, entry/target/stop prices, and risk flags. Supports single or multi-ticker analysis with optional fast mode and JSON output. Use when the user asks to analyze a stock, check a ticker, or compare investments.
compatibility: Designed for Agent Skills compatible clients such as OpenClaw, Claude Code, Hermes, and GitHub-backed skill catalogs. Requires system binaries python3, environment variables AISA_API_KEY and internet access to api.aisa.one.
metadata:
  aisa:
    emoji: 📊
    requires:
      bins:
      - python3
      env:
      - AISA_API_KEY
    primaryEnv: AISA_API_KEY
    compatibility: Designed for Agent Skills compatible clients such as OpenClaw, Claude Code, Hermes, and GitHub-backed skill catalogs. Requires system binaries python3, environment variables AISA_API_KEY and internet access to api.aisa.one.
Ver texto original
---
name: stock-analysis
description: Analyze stocks and cryptocurrencies with 8-dimension scoring via AIsa API. Provides BUY/HOLD/SELL signals with confidence levels, entry/target/stop prices, and risk flags. Supports single or multi-ticker analysis with optional fast mode and JSON output. Use when the user asks to analyze a stock, check a ticker, or compare investments.
compatibility: Designed for Agent Skills compatible clients such as OpenClaw, Claude Code, Hermes, and GitHub-backed skill catalogs. Requires system binaries python3, environment variables AISA_API_KEY and internet access to api.aisa.one.
metadata:
  aisa:
    emoji: 📊
    requires:
      bins:
      - python3
      env:
      - AISA_API_KEY
    primaryEnv: AISA_API_KEY
    compatibility: Designed for Agent Skills compatible clients such as OpenClaw, Claude Code, Hermes, and GitHub-backed skill catalogs. Requires system binaries python3, environment variables AISA_API_KEY and internet access to api.aisa.one.
---

# Stock & Crypto Analysis — AIsa Edition

Analyze one or more stock or crypto tickers using the AIsa API with live Yahoo Finance data.

## Setup

This skill requires an AIsa API key. Set it via plugin configuration or environment variable:

```bash
export AISA_API_KEY=your_key_here
export AISA_BASE_URL=https://api.aisa.one/v1   # optional
export AISA_MODEL=gpt-4o                         # optional
```

Or use the plugin's `userConfig` values (set automatically when the plugin is enabled).

## Usage

Run the analysis script with one or more ticker symbols:

```bash
python3 "${CLAUDE_PLUGIN_ROOT}/skills/stock-analysis/scripts/analyze_stock.py" AAPL
python3 "${CLAUDE_PLUGIN_ROOT}/skills/stock-analysis/scripts/analyze_stock.py" BTC-USD ETH-USD
python3 "${CLAUDE_PLUGIN_ROOT}/skills/stock-analysis/scripts/analyze_stock.py" AAPL MSFT GOOGL
python3 "${CLAUDE_PLUGIN_ROOT}/skills/stock-analysis/scripts/analyze_stock.py" AAPL --fast
python3 "${CLAUDE_PLUGIN_ROOT}/skills/stock-analysis/scripts/analyze_stock.py" AAPL --output json
```

### Arguments

- **Tickers**: One or more stock symbols (e.g., `AAPL`, `MSFT`) or crypto symbols (e.g., `BTC-USD`, `ETH-USD`)
- `--fast`: Skip slow analyses (insider trading, detailed news) for faster results
- `--output json`: Append a structured JSON summary after the analysis

### Multi-Ticker Comparison

When multiple tickers are provided, the script produces individual analyses followed by a ranked comparison table:

| Ticker | Score | Signal | Key Strength | Key Risk |
|--------|-------|--------|-------------|----------|

## 8-Dimension Scoring (Stocks)

| # | Dimension | Weight |
|---|-----------|--------|
| 1 | Earnings Surprise | 30% |
| 2 | Fundamentals (P/E, margins, growth) | 20% |
| 3 | Analyst Sentiment | 20% |
| 4 | Historical Patterns | 10% |
| 5 | Market Context (VIX, SPY/QQQ) | 10% |
| 6 | Sector Performance | 15% |
| 7 | Momentum (RSI, 52w range) | 15% |
| 8 | Sentiment (Fear/Greed, shorts, insiders) | 10% |

## 3-Dimension Scoring (Crypto)

| # | Dimension | Weight |
|---|-----------|--------|
| 1 | Market Cap & Category | 40% |
| 2 | BTC Correlation (30-day) | 30% |
| 3 | Momentum (RSI, range, volume) | 30% |

## Risk Flags

Automatically detected: Pre-earnings, Post-spike, Overbought, Risk-Off, Breaking News

## Output

Final recommendation includes: **Score (0-10)**, **Signal (BUY/HOLD/SELL)**, **Confidence (High/Medium/Low)**, and **Entry / Target / Stop prices**.

**NOT FINANCIAL ADVICE.** For informational purposes only.

Revisar el código fuente

Precio y costes de ejecución

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Licencia
Apache-2.0
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Fuente del skill registrada

La ruta de instrucciones está registrada. No implica pruebas de ejecución, seguridad ni compatibilidad.

Revisar antes de instalar: Evitar instalación automática

Licencia: Apache-2.0

  • Dependency or permission surface needs review
  • Permission surface may require sandboxing
  • Financial research output is not financial advice; require human review before any live investment decision
  • The SKILL.md instructs to run with `python3` but the script's docstring uses `uv run` and declares dependencies via PEP 723. This inconsistency may confuse users about how to install required packages (e.g., `openai`).
  • The script uses `response_format` for JSON output, which may not be supported by all models or API endpoints, potentially causing errors in some environments.
  • Low GitHub adoption signal
  • Financial research output is not financial advice; require human review before any live investment decision.
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • GitHub adoption: 25 GitHub stars
  • Stars/forks activity: 25 stars, 6 forks; issue activity unavailable in current metadata
  • Dependency/runtime risk: command execution surface, credential or environment access
Abrir auditoría completa

Las herramientas son indicios de metadatos, no compatibilidad probada. Los prompts son sugerencias.

Empieza con una tarea pequeña

  1. 1Lee la fuente y confirma entradas, resultados, dependencias y permisos.
  2. 2Pide un plan al agente. Aprueba la configuración y los costes antes de probar en un entorno aislado.
  3. 3Comprueba resultados y archivos modificados. Informa solo de lo ejecutado y conserva la revisión de la fuente.

Consulta dependencias, claves API y costes externos en la fuente. Un repositorio público no implica servicios gratuitos.

Fuente y notas de uso

IndexadoRevisado por IA

Los metadatos y revisiones son orientativos. Popularidad, descubrimiento y ejecución correcta son hechos distintos.

Repositorio fuente
AIsa-team/agent-skills
Licencia
Apache-2.0
Versión
Unknown
Último push de GitHub
10 sept 2026
Registro actualizado
13 sept 2026

Versión declarada en el registro; consulta las versiones de la fuente.

Calidad

57/100

Prometedor

Confianza

55/100

Do not auto-install

Auditoría

69/100

Requiere revisión

  • Dependency or permission surface needs review
  • Permission surface may require sandboxing
  • Financial research output is not financial advice; require human review before any live investment decision
  • The SKILL.md instructs to run with `python3` but the script's docstring uses `uv run` and declares dependencies via PEP 723. This inconsistency may confuse users about how to install required packages (e.g., `openai`).
  • The script uses `response_format` for JSON output, which may not be supported by all models or API endpoints, potentially causing errors in some environments.
  • Low GitHub adoption signal
  • Financial research output is not financial advice; require human review before any live investment decision.
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • GitHub adoption: 25 GitHub stars
  • Stars/forks activity: 25 stars, 6 forks; issue activity unavailable in current metadata
  • Dependency/runtime risk: command execution surface, credential or environment access
Verified installs
—
Resultados
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Copiar no es instalar. Los recuentos requieren un informe de instalación correcta, no garantizan calidad general.

Acceso para agentes

La API Registry expone señales de decisión, confianza, auditoría, casos de uso e instalación sin raspar la interfaz.

Más detalles
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      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/aisa-team-stock-analysis",
    "api": "https://www.openagentskill.com/api/agent/skills/aisa-team-stock-analysis",
    "audit": "https://www.openagentskill.com/skills/aisa-team-stock-analysis/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=aisa-team-stock-analysis&task=Use%20stock-analysis%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20stock-analysis%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20stock-analysis%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/aisa-team-stock-analysis/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/aisa-team-stock-analysis"
  }
}

Para el creador

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Creador
AIsa-team
Indexado por
Índice comunitario de OpenAgentSkill

La atribución enlaza al repositorio público o al perfil del creador. Los creadores pueden reclamar la ficha para actualizar las señales de propiedad.

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[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/aisa-team-stock-analysis?metric=listed&label=Listed)](https://www.openagentskill.com/skills/aisa-team-stock-analysis?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/aisa-team-stock-analysis?metric=trust&label=Trust)](https://www.openagentskill.com/skills/aisa-team-stock-analysis?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/aisa-team-stock-analysis?metric=audit&label=Audit)](https://www.openagentskill.com/skills/aisa-team-stock-analysis/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/aisa-team-stock-analysis?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/aisa-team-stock-analysis?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)

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