Skip to content

搜索技能.../

Agent Skill Search Engine

搜索

搜索
分类
职业

关于

关于
隐私政策
服务条款

© 2026 Skills Pool. 保留所有权利。

Swmm Network | Skills Pool

技能档案

Swmm Network

Build and validate SWMM pipe-network models for urban drainage systems. Use when defining or checking junctions, conduits, outfalls, xsections, coordinates, or exporting network JSON into SWMM INP sections.

Zhonghao19951 星标2026年4月12日

职业
分类: 机器学习

技能内容

SWMM Network (pipe-system layer)

What this skill provides

A stable JSON schema for SWMM drainage-network structure
MVP import from GeoJSON/CSV into the network schema via field-mapping config
Basic QA for topology and required hydraulic attributes
Export from network JSON to core SWMM INP sections
MCP skeleton for qa, export_inp, and summary

MVP scope

This skill currently focuses on the pipe-system/network layer only:

junctions
outfalls
conduits
xsections
coordinates
optional vertices

It does not yet generate networks from GIS/DEM automatically. It expects a network JSON that follows the schema.

Scripts

相关技能

快速安装

Swmm Network

npx skillvault add Zhonghao1995/zhonghao1995-agentic-swmm-workflow-skills-swmm-network-skill-md

下载 Skill 打开源码仓库

作者: Zhonghao1995
星标: 1
更新时间: 2026年4月12日
职业

本页内容

01SWMM Network (pipe-system layer)

scripts/network_import.py
- imports GeoJSON/CSV network data into the stable network JSON schema using a field-mapping config
scripts/network_qa.py
- validates network JSON and writes a machine-readable QA report
scripts/network_to_inp.py
- exports network JSON to SWMM INP sections
scripts/schema/network_model.schema.json
- stable schema target for future GIS import/synthesis tools

Conventions

Prefer explicit, machine-readable JSON in/out.
Keep node/link IDs unique and stable.
MVP assumes gravity network basics first, not pumps/weirs/orifices.
Future skills/tools can target this schema and then hand off to swmm-runner and swmm-calibration.

02

What this skill provides

Civil Engineers

Continuous Learning V2

Instinct-based learning system that observes sessions via hooks, creates atomic instincts with confidence scoring, and evolves them into skills/commands/agents. v2.1 adds project-scoped instincts to prevent cross-project contamination.

Continuous Learning V2

Hook'lar aracılığıyla oturumları gözlemleyen, güven skorlaması ile atomik instinct'ler oluşturan ve bunları skill/command/agent'lara evriltiren instinct tabanlı öğrenme sistemi. v2.1 çapraz proje kontaminasyonunu önlemek için proje kapsamlı instinct'ler ekler.

Continuous Learning V2

훅을 통해 세션을 관찰하고, 신뢰도 점수가 있는 원자적 본능을 생성하며, 이를 스킬/명령어/에이전트로 진화시키는 본능 기반 학습 시스템. v2.1에서는 프로젝트 간 오염을 방지하기 위한 프로젝트 범위 본능이 추가되었습니다.

Continuous Learning

Claude Codeセッションから再利用可能なパターンを自動的に抽出し、将来の使用のために学習済みスキルとして保存します。

Continuous Learning

Automatically extract reusable patterns from Claude Code sessions and save them as learned skills for future use.

Pytorch Patterns

PyTorch deep learning patterns and best practices for building robust, efficient, and reproducible training pipelines, model architectures, and data loading.

Civil Engineers