Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
Wrote 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/aisa-team/agent-skills/stock-dividend)<a href="https://agentmods.dev/skills/aisa-team/agent-skills/stock-dividend"><img src="https://agentmods.dev/badge/skills/aisa-team/agent-skills/stock-dividend/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/aisa-team/agent-skills/stock-dividend"><img src="https://agentmods.dev/badge/skills/aisa-team/agent-skills/stock-dividend.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 | $0.00072 | $0.00695 |
| Opus 5 | $0.00036 | $0.00347 |
| Sonnet 5 | $0.00014 | $0.00139 |
| Haiku 4.5 | $0.00007 | $0.00069 |
Grade A, and why
stock-dividend scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Dividend Analysis — AIsa Edition
Analyze dividend metrics for one or more tickers using the AIsa API. This is a read-only research helper: it does not connect to brokerage accounts, place orders, make purchases, or manage portfolios.
Usage
python3 "${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/v1by default. AISA_BASE_URLis 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.
What ships with it
1 file 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.
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.
- 11d ago First seen · 59 lines · 72 tokens per session scan A 9239b6cb554f
stock-dividend is a skill published in the GitHub repository AIsa-team/agent-skills (24 stars, last pushed today), licensed Apache-2.0. It adds 72 tokens to every session and 695 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
sector-rotation
An analysis framework for comparing industries in the Chinese A-share stock market, using business conditions, price momentum, valuation, and money flows. It produces rankings and higher- or lower-allocation suggestions.
strategy-pivot-designer
Detect backtest iteration stagnation and generate structurally different strategy pivot proposals when parameter tuning reaches a local optimum.
twitter-reader
Read Twitter/X for financial research using opencli (read-only). Use this skill whenever the user wants to read their Twitter feed, search for financial tweets, view bookmarks, look up user profiles, or gather market sentiment from Twitter/X. Triggers include: "check my feed", "search Twitter for", "show my…
chenhao-limit-up
A framework for judging Chinese A-share stocks that have reached the daily price-rise limit, using market mood, sector leadership, and trading momentum.
trading-risk-gate
Unified pre-trade safety gate: Ruin check (Law #1), ergodicity audit, and win-rate dominance validation. Absorbs: ergodicity-check, law-of-ruin, win-rate-dominance.
furusato
A Japanese hometown-tax donation manager for furusato nozei, a system where donations to municipalities can qualify for an income-tax or local-tax deduction. It reads donation receipts, stores donation records, and calculates deduction limits.