# Yahoo Finance

> Yahoo Finance provides stock information for a given ticker symbol, including stock price and trading information, company information, financial metrics, earnings and revenue, margins and returns, dividends, balance sheet data, ownership, analyst coverage, and risk metrics.

- Skill: `serejaris/yahoo-finance` (Agent Skill)
- Install (CLI): `npx skillmds@latest add serejaris/yahoo-finance`
- Raw SKILL.md: https://api.skillmd.com/api/skills/serejaris/yahoo-finance/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Finance & Business
- Author: serejaris (https://skillmd.com/u/serejaris)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/serejaris/yahoo-finance

---


# Yahoo Finance

Use this skill to answer questions that require Yahoo Finance data for a ticker
symbol.

## Setup

Check whether the agent-gw Python SDK is available in the current Python environment, and install it only if the check fails:

```bash
python3 -c "import agent_gw" || python3 -m pip install "$(curl -s https://cdn.kimi.com/agentgw/pysdk/manifest.json | python3 -c "import json,sys; print(json.load(sys.stdin)['latest']['url'])")"
```

The SDK needs an API key from `api_key=...`, `KIMI_API_KEY`, or
`~/.kimi/agent-gw.json`.

## Workflow

1. Run `python3 scripts/yahoo_finance_tool.py describe` from the plugin directory
   to call `get_data_source_desc({"name": "yahoo_finance"})`.
2. Read the returned Markdown carefully. It contains the overall data source
   rules, ticker formats, coverage, global constraints, and each API's
   description, required parameters, optional parameters, defaults, and allowed
   values.
3. Select the API that best matches the user's question.
4. Build `params` exactly from the Markdown requirements. Pay attention to ticker
   symbol, exchange suffix, date range, statement type, reporting period,
   currency, and metric definitions.
5. Use `python3 scripts/yahoo_finance_tool.py call` to call
   `call_data_source_tool`.
6. If the call fails, explain the failure reason from the response.
7. If the call succeeds, save any returned files first, then answer using
   `resp.result.assistant`; ignore `resp.result.user` unless display content is
   specifically needed.

## Common Use Cases

- Stock price and trading information for a ticker.
- Company information and profile data.
- Financial metrics, earnings, revenue, margins, returns, and risk metrics.
- Balance sheet data and other supported statement details.
- Dividends, ownership, holder information, and analyst coverage.

## Script

Use the bundled script from the plugin directory:

```bash
python3 scripts/yahoo_finance_tool.py describe
```

After reading the Markdown and selecting an API:

```bash
python3 scripts/yahoo_finance_tool.py call \
  --api-name "<api name from markdown>" \
  --params-json '{"required_param":"value"}'
```

For larger params, write a JSON object and pass
`--params-file path/to/params.json`.

The script:

- sends `{"name": "yahoo_finance"}` to `get_data_source_desc`
- sends `{"data_source_name": "yahoo_finance", "api_name": ..., "params": ...}` to
  `call_data_source_tool`
- prints failure messages from `error.user` or `error.assistant`
- saves returned files to each `files[].name` path returned by the data source
- prints the joined `result.assistant` texts on success

Expected `call_data_source_tool` response shape:

```python
{
    "is_success": bool,
    "result": {"user": list[str], "assistant": list[str]} | None,
    "error": {"user": list[str], "assistant": list[str]} | None,
    "files": [{"name": str, "content": str}],
}
```

When files are returned, `name` is the file path or name to write. The path is
usually dictated by the selected API's params in the Markdown docs. If an API
does not need files, the response normally has no files to save.