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-design-reviewgit 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-design-review)<a href="https://agentmods.dev/skills/zhonghao1995/agentic-swmm-workflow/swmm-design-review"><img src="https://agentmods.dev/badge/skills/zhonghao1995/agentic-swmm-workflow/swmm-design-review/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-design-review"><img src="https://agentmods.dev/badge/skills/zhonghao1995/agentic-swmm-workflow/swmm-design-review.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 | $0.00086 | $0.01661 |
| Opus 5 | $0.00043 | $0.00830 |
| Sonnet 5 | $0.00017 | $0.00332 |
| Haiku 4.5 | $0.00009 | $0.00166 |
Grade A, and why
swmm-design-review 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 11d 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 — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.
swmm-design-review — Design Review / Code-Compliance Checker
What this skill does
Evaluates a completed SWMM run against a configurable rulebook of design checks.
Reads the run's existing artifacts (manifest.json + model.rpt + model.inp) — SWMM
is never re-run. Classifies each rule as pass, fail, warn, or needs-data
and writes 11_review/design_review.json + 11_review/design_review.md into the
run directory (canonical per ADR-0004; the underlying script's own bare default
is the legacy 09_review/ — see CLI usage below).
This skill is decision-support only. It never certifies regulatory compliance.
CLI usage
# Standalone script
python3 skills/swmm-design-review/scripts/design_review.py \
--run-dir <path> # required: directory with model.rpt, manifest.json, model.inp
[--rpt <path>] # override: explicit model.rpt path
[--inp <path>] # override: explicit model.inp path
[--manifest <path>] # override: explicit manifest.json path
[--rules <rulebook>] # override rulebook YAML/JSON (repeatable for multiple books)
[--out-dir <dir>] # bare-script default: <run-dir>/09_review/ (legacy)
[--no-inp] # skip INP-derived metrics (slope, diameter)
# CLI verb (registered in aiswmm CLI) — always passes --out-dir explicitly,
# defaulting to the canonical <run-dir>/11_review/ (ADR-0004)
aiswmm review --run-dir <path> [--rules <rulebook.yaml>] [--out-dir <dir>]
Exit codes: 0 = pass/warn/needs-data only; 1 = any FAIL; 2 = script/input error.
Agent tool: review_run
Registered in AgentToolRegistry. Direct handler (not MCP-routed) — writes
11_review/design_review.json + 11_review/design_review.md into the run dir
(canonical per ADR-0004).
review_run(run_dir="runs/my_run/")
review_run(run_dir="runs/my_run/", rules="skills/swmm-design-review/rulebooks/gb50014_template.yaml")
is_read_only=False — QUICK profile prompts the user (tool writes files).
What ships with it
3 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.
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.
- 11d ago First seen · 166 lines · 86 tokens per session scan A f001158c1e6b
swmm-design-review is a skill published in the GitHub repository Zhonghao1995/agentic-swmm-workflow (27 stars, last pushed 4d ago), licensed MIT. It adds 86 tokens to every session and 1,661 once invoked, about $0.0004 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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