swmm-experiment-audit

swmm-experiment-audit is a skill for Claude Code, Codex from Zhonghao1995/agentic-swmm-workflow. It costs 84 tokens per session (1,961 once invoked), scanned A, original, MIT.

An audit tool for Agentic SWMM runs. SWMM is software that models stormwater drainage; the tool gathers a run's files, commands, measurements, checks, and results into records for review.

In plain words
What is it for?
Use it after a successful or failed SWMM build, run, or quality check, when you need an Obsidian research note, machine-readable audit data, evidence for a paper, or a comparison between two runs.
Why use it?
Run information is often spread across manifests, logs, quality-check files, and output folders. This tool brings it together so another person can trace what happened and reproduce or compare the run.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Codex.

Good fit Use it after a successful or failed SWMM build, run, or quality check, when you need an Obsidian research note, machine-readable audit data, evidence for a paper, or a comparison between two runs.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/zhonghao1995/agentic-swmm-workflow/swmm-experiment-audit
Install

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.

Any agent
npx skills add Zhonghao1995/agentic-swmm-workflow --skill swmm-experiment-audit
Clone the repo
git clone --depth 1 https://github.com/Zhonghao1995/agentic-swmm-workflow

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for swmm-experiment-audit

README.md
[![agentmods](https://agentmods.dev/badge/skills/zhonghao1995/agentic-swmm-workflow/swmm-experiment-audit/github.svg)](https://agentmods.dev/skills/zhonghao1995/agentic-swmm-workflow/swmm-experiment-audit)
Your own site
<a href="https://agentmods.dev/skills/zhonghao1995/agentic-swmm-workflow/swmm-experiment-audit"><img src="https://agentmods.dev/badge/skills/zhonghao1995/agentic-swmm-workflow/swmm-experiment-audit/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.

agentmods 80×15 button for swmm-experiment-audit

Your own site · 80×15
<a href="https://agentmods.dev/skills/zhonghao1995/agentic-swmm-workflow/swmm-experiment-audit"><img src="https://agentmods.dev/badge/skills/zhonghao1995/agentic-swmm-workflow/swmm-experiment-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 84 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,961 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00084 $0.01961
Opus 5 $0.00042 $0.00981
Sonnet 5 $0.00017 $0.00392
Haiku 4.5 $0.00008 $0.00196

Measured 11d ago against content hash 18d77405977c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

swmm-experiment-audit 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.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/audit_run.py, scripts/init_obsidian_vault.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/swmm-experiment-audit/SKILL.md · 226 lines

How it starts

The opening of the file, as written. The whole thing — 226 lines — stays where its author put it; the contents beside it link to each section on GitHub.

SWMM Experiment Audit

Part of Agentic SWMM — install the project first for the executable toolchain (aiswmm CLI, SWMM solver, MCP servers).

What this skill provides

  • A standard audit layer for Agentic SWMM runs.
  • Consolidation of dispersed manifest.json, QA JSON, logs, metrics, and artifact paths.
  • Machine-readable outputs for reproducibility and review.
  • Obsidian-compatible Markdown notes for human research records.
  • Default local Obsidian export into a clean English audit vault.
  • Automatic update of the Obsidian Experiment Audit Index.
  • Optional run-to-run comparison for baseline/scenario or before/after parser validation.

This skill records what happened. It does not run SWMM, build models, invent missing artifacts, or replace module-level validation.

When to use this skill

Use this skill after any of these events:

  • swmm-end-to-end completes successfully.
  • swmm-end-to-end stops or fails after producing partial artifacts.
  • A user wants an Obsidian-ready experiment note for an existing run directory.
  • A user wants to compare two run directories.
  • A run needs evidence for reproducibility, metric provenance, QA status, or paper claims.

Do not use this skill as a substitute for swmm-runner, swmm-builder, or calibration tools. Run the model first, then audit the run directory.

Output contract

For every audited run, write these files into the run's 09_audit/ directory unless explicit output paths are provided:

  • experiment_provenance.json — machine-readable provenance (immutable).
  • experiment_note.md — human-readable Obsidian digest.
  • model_diagnostics.json — deterministic SWMM screening checks.
  • comparison.json — run-to-run comparison (only when --compare-to is given).

experiment_provenance.json is the machine-readable source for:

  • run identity
  • repo state
  • tool versions
  • command trace
  • input hash records
  • artifact index
  • metrics with source artifacts and source tables
  • QA checks
  • detected warnings and limitations

Read the full file on GitHub · 226 lines

Files

What ships with it

2 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.

Changes

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.

  1. 11d ago First seen · 226 lines · 84 tokens per session scan A 18d77405977c

Subscribe to this mod's changes

swmm-experiment-audit is a skill published in the GitHub repository Zhonghao1995/agentic-swmm-workflow (27 stars, last pushed 4d ago), licensed MIT. It adds 84 tokens to every session and 1,961 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.

Related

Other skills, from other repositories

arxiv-summarizer-orchestrator

End-to-end orchestration skill for periodic arXiv collection and reporting using three sub-skills: arxiv-search-collector, arxiv-paper-processor, and arxiv-batch-reporter. Supports manual language control across all markdown outputs and Stage-B processing strategy (subagentparallel default max 5, or serial).

InternLM/WildClawBench · 75 tokens

academic-literature-search

A multi-database search tool for academic papers and other scholarly publications. It searches sources such as Semantic Scholar, Crossref, arXiv, and PubMed, which cover research across fields including computing, physics, and medicine.

InternLM/WildClawBench · 0 tokens

cuopt-numerical-optimization-formulation

LP, MILP, QP — concepts, problem-text parsing, and formulation patterns (parameters, constraints, decisions, objective). Concepts only; no API.

NVIDIA/skills · 42 tokens

nemo-mbridge-perf-expert-parallel-overlap

Validate and use MoE expert-parallel communication overlap in Megatron-Bridge, including overlapmoeexpertparallelcomm, delaywgradcompute, and flex dispatcher backends such as DeepEP and HybridEP.

NVIDIA/skills · 56 tokens

earth2studio-create-datasource

Create and validate Earth2Studio data source wrappers (DataSource, ForecastSource, DataFrameSource, ForecastFrameSource) from remote stores. Do NOT use for fetching data with existing sources, model inference, or installation tasks.

NVIDIA/skills · 53 tokens

earth2studio-data-fetch

Fetch weather/climate data via Earth2Studio data sources for specific variables and times. Do NOT use for inference pipelines, model discovery, or installation.

NVIDIA/skills · 36 tokens