← Voltar para o catálogo
Read historical Agentic SWMM experiment audit artifacts and summarize repeated assumptions, QA issues, failures, missing evidence, run-to-run differences, lessons learned, and controlled skill update proposals. Use downstream of swmm-experiment-audit when multiple audited runs exist or when a user asks for modeling memory, failure-pattern extraction, lessons learned, or human-reviewed skill refine
Ver no GitHub ↗
Copiar URL do repo
Copiar link do SKILL.md Licença: MIT
Como adicionar
Copiar comando
/plugin marketplace add Zhonghao1995/agentic-swmm-workflow
O comando exato pode variar conforme o repositório. Confira o README no GitHub.
Para o autor da skill
Cole no README do seu repo
Mostra que sua skill está catalogada na Skillteca, gera backlink e tráfego rastreável.
[](https://www.skillteca.com.br/skills/swmm-modeling-memory)
Copiar snippet
Alerta por categoria
1 email curto, só com as skills novas de DevOps e Infra. 4 minutos de leitura, sem spam, cancela com 1 clique.
Você confirma o email no primeiro envio. Sem spam. Cancela com 1 clique.
Ler descrição completa Recolher descrição
SWMM Modeling Memory
What this skill provides
A downstream memory layer for audited Agentic SWMM runs. Deterministic summaries of repeated assumptions, QA issues, failures, missing evidence, and run-to-run differences. Run-level memory_summary.json cards that compress audit artifacts into reusable next-run context. Project/case-level memory groups that keep Tod Creek, Tecnopolo, TUFLOW, Generate_SWMM_inp, acceptance, and other cases separate. Summaries of deterministic SWMM-sp
[Description truncada. Veja o README completo no GitHub.]
Compartilhar
X
LinkedIn
Copiar link