Registry indexed

stock-dividend

Analyze read-only dividend metrics for stocks via AIsa API. Provides yield, payout ratio, growth CAGR, safety score, income rating, and Dividend Aristocrat/King status without placing trades, making purchases, or managing brokerage accounts. Use when: the user needs market data,

Review the source View on GitHub

Overview

Read full documentation

Source documentation, not instructions for this website. Review permissions before running any commands.

Dividend Analysis — AIsa Edition

Analyze dividend metrics for one or more tickers using the AIsa API. This is a read-only research helper: it does not connect to brokerage accounts, place orders, make purchases, or manage portfolios.

Usage

python3 "${CLAUDE_PLUGIN_ROOT}/skills/stock-dividend/scripts/dividends.py" JNJ
python3 "${CLAUDE_PLUGIN_ROOT}/skills/stock-dividend/scripts/dividends.py" JNJ PG KO
python3 "${CLAUDE_PLUGIN_ROOT}/skills/stock-dividend/scripts/dividends.py" JNJ PG KO --output json

Arguments

Tickers: One or more dividend-paying stock symbols. Inputs are validated before they are sent to the model.
--output json: Append structured JSON summary

Permission Boundary

The only required secret is AISA_API_KEY.
Requests go to https://api.aisa.one/v1 by default.
AISA_BASE_URL is optional and should only point to a trusted AIsa-compatible HTTPS endpoint.
Do not provide brokerage credentials, trading passwords, cookies, or payment details. This skill has no purchase or order-placement workflow.

Analysis Output

For each ticker, the analysis includes:

Core Metrics: Yield, ex-date, frequency, last payment amount
Payout Analysis: Payout ratio, FCF payout, coverage ratio
Growth: 1Y, 3Y CAGR, 5Y CAGR, consecutive years of increases
Last 5 Annual Dividends table
Safety Score (0-100): Based on payout ratio (25pts), FCF coverage (20pts), growth consistency (20pts), balance sheet (15pts), earnings stability (10pts), consecutive years (10pts)
Income Rating: Excellent (80+), Good (60-79), Moderate (40-59), Poor (<40)
Dividend Aristocrat/King status check

When multiple tickers are provided, a ranked comparison table is included.

NOT FINANCIAL ADVICE. For informational purposes only.

View source ↗

File metadata

name: stock-dividend
description: 'Analyze read-only dividend metrics for stocks via AIsa API. Provides yield, payout ratio, growth CAGR, safety score, income rating, and Dividend Aristocrat/King status without placing trades, making purchases, or managing brokerage accounts. Use when: the user needs market data, stock analysis, dividend research, or read-only financial data workflows.'
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.
    version: 1.0.2
  openclaw:
    clawhub-slug: stock-dividend-aisa

View original text

---
name: stock-dividend
description: 'Analyze read-only dividend metrics for stocks via AIsa API. Provides yield, payout ratio, growth CAGR, safety score, income rating, and Dividend Aristocrat/King status without placing trades, making purchases, or managing brokerage accounts. Use when: the user needs market data, stock analysis, dividend research, or read-only financial data workflows.'
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.
    version: 1.0.2
  openclaw:
    clawhub-slug: stock-dividend-aisa
---

# Dividend Analysis — AIsa Edition

Analyze dividend metrics for one or more tickers using the AIsa API. This is a read-only research helper: it does not connect to brokerage accounts, place orders, make purchases, or manage portfolios.

## Usage

```bash
python3 "${CLAUDE_PLUGIN_ROOT}/skills/stock-dividend/scripts/dividends.py" JNJ
python3 "${CLAUDE_PLUGIN_ROOT}/skills/stock-dividend/scripts/dividends.py" JNJ PG KO
python3 "${CLAUDE_PLUGIN_ROOT}/skills/stock-dividend/scripts/dividends.py" JNJ PG KO --output json
```

### Arguments

- **Tickers**: One or more dividend-paying stock symbols. Inputs are validated before they are sent to the model.
- `--output json`: Append structured JSON summary

## Permission Boundary

- The only required secret is `AISA_API_KEY`.
- Requests go to `https://api.aisa.one/v1` by default.
- `AISA_BASE_URL` is optional and should only point to a trusted AIsa-compatible HTTPS endpoint.
- Do not provide brokerage credentials, trading passwords, cookies, or payment details. This skill has no purchase or order-placement workflow.

## Analysis Output

For each ticker, the analysis includes:

- **Core Metrics**: Yield, ex-date, frequency, last payment amount
- **Payout Analysis**: Payout ratio, FCF payout, coverage ratio
- **Growth**: 1Y, 3Y CAGR, 5Y CAGR, consecutive years of increases
- **Last 5 Annual Dividends** table
- **Safety Score (0-100)**: Based on payout ratio (25pts), FCF coverage (20pts), growth consistency (20pts), balance sheet (15pts), earnings stability (10pts), consecutive years (10pts)
- **Income Rating**: Excellent (80+), Good (60-79), Moderate (40-59), Poor (<40)
- **Dividend Aristocrat/King** status check

When multiple tickers are provided, a ranked comparison table is included.

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

Review the source

Skill source recorded

Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.

Review before install: Avoid automatic install

License: 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
Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required
SKILL.md usage examples use `python3` directly, but the script requires the `openai` package which is not mentioned in the requirements. This could cause runtime errors if the dependency is not installed.
The script supports an `AISA_MODEL` environment variable that is not documented in SKILL.md.
Low GitHub adoption signal
Financial research output is not financial advice; require human review before any live investment decision.
This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
GitHub adoption: 25 GitHub stars

Agent access

This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.

More details

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Creator: AIsa-team
Source: AIsa-team/agent-skills
Indexed by: OpenAgentSkill community index

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stock-dividend

Overview

Dividend Analysis — AIsa Edition

Usage

Arguments

Permission Boundary

Analysis Output

Review the source

Source & usage notes

Agent access

For the creator

Registry indexed

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Community signal

Start with one small task

Overview

Dividend Analysis — AIsa Edition

Usage

Arguments

Permission Boundary

Analysis Output

Review the source

Source & usage notes

Agent access

Related skills

For the creator

Registry indexed

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Add the evidence badges to your README

Community signal

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