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v1.0.0
GitHub

About this Skill

Perfect for Environmental Analysis Agents needing advanced erosion-gully-analysis capabilities with SiliconFlow and OpenAI interfaces. erosion-gully-analysis is a specialized AI skill for analyzing gully erosion, providing stable and reusable operational workflows for improved judgment and advice generation.

Features

Utilizes ai_analysis.py for AI module code
Leverages ai_prompts/screening_system.txt and ai_prompts/advice_system.txt for prompt files
Supports SiliconFlow (OpenAI-style) interface for compatibility
Allows for threshold adjustments in ai_analysis.py using _rule_screening and _rule_advice
Injects model and authorization information via environment variables (SILICONFLOW_BASE_URL, SILICONFLOW_API_KEY, SILICONFLOW_MODEL)

# Core Topics

1105564578 1105564578
[0]
[0]
Updated: 3/7/2026

Quality Score

Top 5%
26
Excellent
Based on code quality & docs
Installation
SYS Universal Install (Auto-Detect)
Cursor IDE Windsurf IDE VS Code IDE
> npx killer-skills add 1105564578/erosion-gully-system/erosion-gully-analysis

Agent Capability Analysis

The erosion-gully-analysis MCP Server by 1105564578 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 erosion-gully-analysis, what is erosion-gully-analysis, erosion-gully-analysis alternative.

Ideal Agent Persona

Perfect for Environmental Analysis Agents needing advanced erosion-gully-analysis capabilities with SiliconFlow and OpenAI interfaces.

Core Value

Empowers agents to generate high-quality judgments and advice for gully erosion using AI-driven analysis, supporting JSON output and compatible with SiliconFlow and OpenAI styles, leveraging environment variables for model and API key injection.

Capabilities Granted for erosion-gully-analysis MCP Server

Automating gully erosion judgment quality enhancements
Optimizing advice generation for developers and researchers
Integrating with SiliconFlow and OpenAI interfaces for seamless analysis

! Prerequisites & Limits

  • Requires SiliconFlow base URL, API key, and model environment variables
  • Limited to JSON output with fixed fields
  • Dependent on ai_analysis.py and ai_prompts files for functionality
Project
SKILL.md
992 B
.cursorrules
1.2 KB
package.json
240 B
Ready
UTF-8

# Tags

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SKILL.md
Readonly

侵蚀沟 AI 分析 Skill

目标

为本项目的 AI 分析模块提供稳定可复用的操作流程,支持:

  • 提升“是否治理”的判断质量
  • 优化治理建议的专业性与可执行性
  • 兼容 SiliconFlow(OpenAI 风格)接口

关键入口

  • AI 模块代码:ai_analysis.py
  • 提示词文件:
    • ai_prompts/screening_system.txt
    • ai_prompts/advice_system.txt

使用流程

  1. 需要提升判断质量时,优先修改 ai_prompts/*.txt,避免直接改逻辑。
  2. 如需调整规则兜底阈值,修改 ai_analysis.py_rule_screening_rule_advice
  3. 模型/鉴权信息通过环境变量注入:
    • SILICONFLOW_BASE_URL
    • SILICONFLOW_API_KEY
    • SILICONFLOW_MODEL

输出约束

  • 必须输出 JSON,字段固定:
    • 初筛:decision / reason / risk_level
    • 建议:risk_level / summary / actions

注意事项

  • 优先保证 JSON 可解析
  • 若 LLM 失败,系统会自动回退到规则结果

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