alphaear-deepear-lite — Claude Code skill: how to install
Fetches high-frequency financial signals and transmission-chain analyses from DeepEar Lite. Useful for reviewing market sentiment and stock movement drivers in chat.
npx skills add RKiding/Awesome-finance-skills --skill alphaear-deepear-lite -a claude-codeWhat alphaear-deepear-lite does
The skill queries the DeepEar Lite real-time feed via scripts/deepear_lite.py. Using DeepEarLiteTools, the fetch_latest_signals() function pulls signal titles, summaries, confidence metrics, and source links.
It depends strictly on requests and loguru. No local database is needed, but the tool will fail if your environment cannot reach the remote feed.
You can verify the connection and data retrieval directly by running python scripts/deepear_lite.py.
What it helps with
- fetch real-time financial market signals with confidence scores
- track stock drivers and transmission-chain market analysis
- inspect market sentiment data without configuring a local database
Example prompts for the agent
- Fetch the latest financial signals from DeepEar Lite and summarize sentiment
- Show market trend factors and reasoning from the DeepEar Lite feed
How to install alphaear-deepear-lite
1Skills CLI (Vercel)
npx skills add RKiding/Awesome-finance-skills --skill alphaear-deepear-lite -a claude-code2Manually: put the files in place
~/.claude/skills/alphaear-deepear-lite/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/alphaear-deepear-lite/
1Skills CLI (Vercel)
npx skills add RKiding/Awesome-finance-skills --skill alphaear-deepear-lite -a codex2Manually: put the files in place
.agents/skills/alphaear-deepear-lite/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add RKiding/Awesome-finance-skills --skill alphaear-deepear-lite -a cursor2Manually: put the files in place
.cursor/skills/alphaear-deepear-lite/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install RKiding/Awesome-finance-skills alphaear-deepear-lite2Manually: put the files in place
.github/skills/alphaear-deepear-lite/SKILL.md1Skills CLI (Vercel)
npx skills add RKiding/Awesome-finance-skills --skill alphaear-deepear-lite -a gemini-cli2Platform CLI
gemini skills install https://github.com/RKiding/Awesome-finance-skills --path skills/alphaear-deepear-liteManually: put the files in place
.devin/skills/alphaear-deepear-lite/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add RKiding/Awesome-finance-skills --skill alphaear-deepear-lite -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about alphaear-deepear-lite
How to install alphaear-deepear-lite in Claude Code?
Run npx skills add RKiding/Awesome-finance-skills --skill alphaear-deepear-lite -a claude-code. This installs the skill files into your project.
What does alphaear-deepear-lite do?
It retrieves real-time financial signals, sentiment indicators, and market factor explanations directly from the DeepEar Lite service.
What dependencies are required?
It requires Python with the requests and loguru packages installed. A local database is not required.
Source text
SKILL.md · Apache-2.0
---
name: alphaear-deepear-lite
description: Fetch the latest financial signals and transmission-chain analyses from DeepEar Lite. Use when the user needs immediate insights into financial market trends, stock performance factors, and reasoning from the DeepEar Lite dashboard.
---
# DeepEar Lite Skill
## Overview
Fetch high-frequency financial signals, including titles, summaries, confidence scores, and reasoning directly from the DeepEar Lite platform's real-time data source.
## Capabilities
### 1. Fetch Latest Financial Signals
Use `scripts/deepear_lite.py` via `DeepEarLiteTools`.
- **Fetch Signals**: `fetch_latest_signals()`
- Retrieves all latest signals from `https://deepear.vercel.app/latest.json`.
- Returns a formatted report of signal titles, sentiment/confidence metrics, summaries, and source links.
## Dependencies
- `requests`, `loguru`
- No local database required for this skill.
## Testing
Run the test script to verify the connection and data fetching:
```bash
python scripts/deepear_lite.py
```
© RKiding · Apache-2.0 · RKiding/Awesome-finance-skills
