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DeepEar Analysis Skill — how to use DeepEar Analysis Skill how to use DeepEar Analysis Skill, DeepEar Analysis Skill API documentation, financial signal tracking with DeepEar, DeepEar Analysis Skill vs alternative frameworks, DeepEar Analysis Skill setup guide, installing DeepEar Analysis Skill for financial research

v1.0.0
GitHub

About this Skill

Perfect for Financial Analysis Agents needing comprehensive financial signal analysis via API triggers. DeepEar Analysis Skill is an open-source framework for deep research and financial signal tracking, providing an API endpoint for triggering analysis workflows

Features

Triggers financial signal analysis via POST /analyze API endpoint
Supports customizable analysis with optional query, sources, and concurrency parameters
Accepts JSON request bodies with specific parameters such as wide, depth, and update_from
Allows for concurrent analysis with adjustable concurrency levels
Provides a flexible framework for deep research and financial signal tracking

# Core Topics

HKUSTDial HKUSTDial
[0]
[0]
Updated: 3/6/2026

Quality Score

Top 5%
51
Excellent
Based on code quality & docs
Installation
SYS Universal Install (Auto-Detect)
Cursor IDE Windsurf IDE VS Code IDE
> npx killer-skills add HKUSTDial/DeepEar/DeepEar Analysis Skill

Agent Capability Analysis

The DeepEar Analysis Skill MCP Server by HKUSTDial is an open-source Categories.community integration for Claude and other AI agents, enabling seamless task automation and capability expansion. Optimized for how to use DeepEar Analysis Skill, DeepEar Analysis Skill API documentation, financial signal tracking with DeepEar.

Ideal Agent Persona

Perfect for Financial Analysis Agents needing comprehensive financial signal analysis via API triggers.

Core Value

Empowers agents to trigger customizable DeepEar analysis workflows via API endpoints, utilizing JSON request bodies to specify query parameters, news sources, and concurrency levels, thereby enhancing financial research and analysis capabilities.

Capabilities Granted for DeepEar Analysis Skill MCP Server

Triggering comprehensive financial signal analysis for specific market sectors
Customizing analysis workflows with adjustable parameters such as depth and concurrency
Integrating DeepEar analysis into existing financial research and analysis pipelines

! Prerequisites & Limits

  • Requires API access and proper JSON request body formatting
  • Dependent on the availability and quality of news sources and financial data
Project
SKILL.md
1.5 KB
.cursorrules
1.2 KB
package.json
240 B
Ready
UTF-8

# Tags

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SKILL.md
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DeepEar Analysis Skill

This skill wraps the DeepEar analysis workflow, allowing you to trigger comprehensive financial signal analysis via an API.

API Endpoints

POST /analyze

Triggers the DeepEar analysis workflow.

Request Body:

json
1{ 2 "query": "A-share tech sector", 3 "sources": "all", 4 "wide": 10, 5 "depth": "auto", 6 "concurrency": 5, 7 "update_from": "20240203_110000" 8}
  • query (optional): The user intent or topic to analyze.
  • sources (optional): News sources ('all', 'financial', 'social', 'tech', or comma-separated). Default: 'all'.
  • wide (optional): Number of items to fetch per source. Default: 10.
  • depth (optional): Analysis depth ('auto' or integer). Default: 'auto'.
  • concurrency (optional): Number of concurrent threads. Default: 5.
  • update_from (optional): Provide a run_id to update an existing analysis with new market data/logic.

Response:

json
1{ 2 "job_id": "550e8400-e29b-41d4-a716-446655440000", 3 "status": "pending", 4 "submitted_at": "2024-02-04T12:00:00.000000" 5}

GET /status/{job_id}

Check the progress and get the result of the analysis job.

Response (Completed):

json
1{ 2 "job_id": "550e8400-e29b-41d4-a716-446655440000", 3 "status": "completed", 4 "result": { 5 "report_path": "/path/to/DeepEar/reports/daily_report_20240204_1205.html", 6 "message": "Analysis completed successfully." 7 }, 8 "timestamp": "2024-02-04T12:05:00.000000" 9}

Usage

Run the server:

bash
1uv run skills/deepear/scripts/server.py

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