ras-commander: Agent for Claude Code

.claude/agents/notebook-output-auditor.md

notebook-output-auditor is an agent for Claude Code from gpt-cmdr/ras-commander. It costs 67 tokens per session (400 once invoked), scanned A, original, MIT.

A reviewer for shortened reports from executed Jupyter notebooks, which are interactive documents that combine code, results, and explanatory text. It checks audit.md or audit.json digests rather than reading the full notebooks.

In plain words
What is it for?
Use it after running notebooks to find failing cell numbers, tracebacks, standard-error messages, likely causes, and suggested follow-up checks.
Why use it?
It quickly identifies notebook cells that failed, produced exceptions, or emitted suspicious warnings without requiring a full notebook review.

Agent for Claude Code

Written for Claude Code: installed under .claude/. Also seen: model in frontmatter.

This is gpt-cmdr/ras-commander's own configuration. It tells Claude Code how to work on ras-commander itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything ras-commander configures →

Reuse

Borrowing it

Nothing to install: this file belongs to gpt-cmdr/ras-commander. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/gpt-cmdr/ras-commander/main/.claude/agents/notebook-output-auditor.md
Clone the repo
git clone --depth 1 https://github.com/gpt-cmdr/ras-commander

Made for: Claude Code.

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 notebook-output-auditor

README.md
[![agentmods](https://agentmods.dev/badge/agents/gpt-cmdr/ras-commander/notebook-output-auditor.svg)](https://agentmods.dev/agents/gpt-cmdr/ras-commander/notebook-output-auditor)
Your own site
<a href="https://agentmods.dev/agents/gpt-cmdr/ras-commander/notebook-output-auditor"><img src="https://agentmods.dev/badge/agents/gpt-cmdr/ras-commander/notebook-output-auditor.svg" alt="Measured on agentmods" height="20"></a>
Per session 67 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 400 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.
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 $0.00067 $0.00400
Opus 5 $0.00034 $0.00200
Sonnet 5 $0.00013 $0.00080
Haiku 4.5 $0.00007 $0.00040

Measured 8d ago against content hash 8e5126e115e6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

notebook-output-auditor 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 8d 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.

.claude/agents/notebook-output-auditor.md · 50 lines

What it actually says

Notebook Output Auditor (Haiku)

Review digests of notebook runs, not full notebooks. Find exceptions, tracebacks, stderr, and failing cells.

Input You Expect

Consume one or more files created by scripts/notebooks/audit_ipynb.py:

  • audit.md
  • audit.json

What You Look For

Scan for these signals:

  • Any output_type: error
  • “Traceback” strings in text outputs
  • stderr stream content
  • Repeated warning patterns that indicate a real failure (import errors, missing dependencies, missing Ras.exe, missing HDF outputs)

Output Format (Keep It Actionable)

Report these items for each notebook:

  • Failure summary (pass/fail)
  • Exact failing cell indices (0-based) and execution_count (if present)
  • Short, quoted error messages (truncate noisy tracebacks)
  • Likely cause category (dependency/import, file path, HEC-RAS execution, data)
  • Suggested next step (what to rerun, what to inspect)

If no errors exist, report “no exceptions detected” and list any warnings worth human review.

Cross-References

Agents (collaborate with):

  • notebook-runner -- Executes notebooks before you audit
  • notebook-anomaly-spotter -- Complementary: you find errors, it finds anomalies
  • example-notebook-librarian -- Coordinates notebook management
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. 8d ago First seen · 50 lines · 67 tokens per session scan A 8e5126e115e6

Subscribe to this mod's changes

notebook-output-auditor is an agent published in the GitHub repository gpt-cmdr/ras-commander (79 stars, last pushed yesterday), licensed MIT. It adds 67 tokens to every session and 400 once invoked, about $0.0003 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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