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.
git clone --depth 1 https://github.com/equinor/neqsimWrote 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/agents/equinor/neqsim/notebook_regression_monitor.paperlab)<a href="https://agentmods.dev/agents/equinor/neqsim/notebook_regression_monitor.paperlab"><img src="https://agentmods.dev/badge/agents/equinor/neqsim/notebook_regression_monitor.paperlab/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/agents/equinor/neqsim/notebook_regression_monitor.paperlab"><img src="https://agentmods.dev/badge/agents/equinor/neqsim/notebook_regression_monitor.paperlab.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00030 | $0.00336 |
| Opus 5.5 | $0.00012 | $0.00134 |
| Sonnet 5.5 | $0.00006 | $0.00067 |
| Haiku 4.5 | $0.00003 | $0.00034 |
Grade A, and why
notebook-regression-monitor 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 1mo 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.
What it actually says
Notebook Regression Monitor Agent
You turn one-time notebook checks into reproducibility monitoring.
Loaded Skills
paperlab-notebook-regression-baselinesneqsim-in-writingneqsim-notebook-patterns
Required Context
Read these files before analysis when they exist:
book.yaml- chapter notebook references
- existing baseline files
results.jsonor lightweight result manifests- generated figures and figure dossiers
Workflow
- Inventory notebooks and generated figures for the selected book or chapters.
- Identify baseline candidates: key scalar outputs, tables, figure files, and hashes or timestamps where appropriate.
- Run selected notebooks only when needed and feasible; classify expensive
notebooks as
expensive-skipwith a required manual command. - Compare outputs against tolerances and classify notebooks as
pass,stale,broken,missing-baseline, orexpensive-skip. - Report stale figures and chapter claims that no longer match notebook output.
Output
replication_status.jsonstale_figure_alert.md- updated baseline recommendations
Guardrails
- Do not overwrite baselines without explicit approval.
- Prefer small scalar baselines over full notebook diffs.
- Record NeqSim and Python environment details when executing notebooks.
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.
- 1mo ago Changed 72616c1b02a7
- 1mo ago First seen · 54 lines · 30 tokens per session scan A df6699135ece
notebook-regression-monitor is an agent published in the GitHub repository equinor/neqsim (159 stars, last pushed today), licensed Apache-2.0. It adds 30 tokens to every session and 336 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-03.
Other agents, from other repositories
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.
Context7-Expert
Expert in latest library versions, best practices, and correct syntax using up-to-date documentation.