Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Zhonghao1995/agentic-swmm-workflow --skill swmm-networkgit clone --depth 1 https://github.com/Zhonghao1995/agentic-swmm-workflowWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/zhonghao1995/agentic-swmm-workflow/swmm-network)<a href="https://agentmods.dev/skills/zhonghao1995/agentic-swmm-workflow/swmm-network"><img src="https://agentmods.dev/badge/skills/zhonghao1995/agentic-swmm-workflow/swmm-network/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/zhonghao1995/agentic-swmm-workflow/swmm-network"><img src="https://agentmods.dev/badge/skills/zhonghao1995/agentic-swmm-workflow/swmm-network.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00153 | $0.02516 |
| Opus 5 | $0.00077 | $0.01258 |
| Sonnet 5 | $0.00031 | $0.00503 |
| Haiku 4.5 | $0.00015 | $0.00252 |
Grade A, and why
swmm-network scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SWMM Network (pipe-system layer)
Part of Agentic SWMM — install the project first for the executable toolchain (aiswmm CLI, SWMM solver, MCP servers).
What this skill provides
- A stable JSON schema for SWMM drainage-network structure.
- Two complementary import paths:
- Raw municipal shapefile path (
prepare_storm_inputs→infer_outfall→reorient_pipes→import_city_network→qa) for typical city storm-pipe + manhole layers that arrive as bare LineString shapefiles. - Structured asset-DB path (
import_city_networkdirectly, orimport_networkfor a fully field-mapped GeoJSON/CSV) when the source already contains explicit from/to nodes, inverts, and diameters.
- Raw municipal shapefile path (
- A subcatchment-to-network wiring step (
assign_subcatchment_outlets) that ensures surface runoff actually enters the pipe network at a real upstream junction rather than dumping straight to the outfall. - Topology / hydraulic-attribute QA (
qa). - Lightweight introspection (
summary). - Export from network JSON to core SWMM INP sections (
export_inp).
When to use this skill
Use when a SWMM model needs a real pipe network. Specifically:
- You have municipal storm-pipe shapefile(s) and want them imported into a SWMM-ready network.json.
- You have a structured CAD/asset-DB export (CSV / GeoJSON with explicit topology) and want the same.
- You need to attach subcatchments to upstream junctions instead of letting them dump to the outfall.
- You need to QA an existing network.json before handing it to
swmm-builder.
Do not use this skill when the user only wants subcatchment delineation (use swmm-gis) or only wants to run a finished INP (use swmm-runner).
MCP tools
mcp/swmm-network/server.js exposes nine tools. Pick by what stage of the pipeline you're at.
Raw-shapefile preparation chain
prepare_storm_inputs— clip raw<municipal>StormGravityMain.shp(+ optional<municipal>StormManhole.shp) to a basin polygon and emit pipes.geojson, manholes.geojson, and a filled mapping.json from a template.- Args:
pipesShpPath,manholesShpPath(optional),basinClipGeojsonPath,mappingTemplatePath,outDir,caseName,sourceDescription,diameterPolicy(optional). - Use
templates/city_mapping_raw_shapefile.template.jsonas the mapping template. - Does not pick the outfall, fix flow direction, or snap drifting endpoints (those are separate tools).
- Args:
What ships with it
27 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- examples/basic-network.json 1.5 KB
- examples/city-dual-system/landuse.csv 69 B
- examples/city-dual-system/mapping.json 1.9 KB
- examples/city-dual-system/outfalls.csv 140 B
- examples/city-dual-system/pipes.csv 494 B
- examples/city-dual-system/README.md 685 B
- examples/city-dual-system/soil.csv 66 B
- examples/city-dual-system/subcatchments.csv 145 B
- examples/import-conduits.geojson 712 B
- examples/import-junctions.geojson 465 B
- examples/import-mapping.json 1.3 KB
- examples/import-outfalls.geojson 267 B
- scripts/_hash_util.py 826 B runs code
- scripts/assign_subcatchment_outlets.py 9.6 KB runs code
- scripts/city_network_adapter.py 18 KB runs code
- scripts/infer_outfall.py 6.5 KB runs code
- scripts/inp_to_network.py 3.8 KB runs code
- scripts/minimal_stub_network.py 4.3 KB runs code
- scripts/network_import.py 8.3 KB runs code
- scripts/network_qa.py 7.5 KB runs code
- scripts/network_to_inp.py 4.1 KB runs code
- scripts/prepare_storm_inputs.py 5.8 KB runs code
- scripts/reorient_pipes.py 8.1 KB runs code
- scripts/schema/network_model.schema.json 4.5 KB
- scripts/snap_pipe_endpoints.py 7.8 KB runs code
- templates/city_mapping_raw_shapefile.template.json 1.9 KB
- templates/README.md 3.9 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago Changed · +31 tokens per session c75b2759383b
- 9d ago First seen · 134 lines · 122 tokens per session scan A d3e9fbea037f
swmm-network is a skill published in the GitHub repository Zhonghao1995/agentic-swmm-workflow (27 stars, last pushed 3d ago), licensed MIT. It adds 153 tokens to every session and 2,516 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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