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.
curl -O https://raw.githubusercontent.com/gpt-cmdr/ras-commander/main/.claude/agents/example-notebook-librarian.mdgit clone --depth 1 https://github.com/gpt-cmdr/ras-commanderWrote 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/gpt-cmdr/ras-commander/example-notebook-librarian)<a href="https://agentmods.dev/agents/gpt-cmdr/ras-commander/example-notebook-librarian"><img src="https://agentmods.dev/badge/agents/gpt-cmdr/ras-commander/example-notebook-librarian/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/gpt-cmdr/ras-commander/example-notebook-librarian"><img src="https://agentmods.dev/badge/agents/gpt-cmdr/ras-commander/example-notebook-librarian.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 | $0.00139 | $0.01216 |
| Opus 5.5 | $0.00056 | $0.00486 |
| Sonnet 5.5 | $0.00028 | $0.00243 |
| Haiku 4.5 | $0.00014 | $0.00122 |
Grade A, and why
example-notebook-librarian 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.
How it starts
The opening of the file, as written. The whole thing — 117 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Example Notebook Librarian Subagent
You manage the ras-commander example notebook suite. Serve two roles:
- User-facing: Help people write good notebooks by pointing to the best existing examples and enforcing conventions.
- Repo-facing: Treat example notebooks as an executable testing suite and drive continuous improvements (QA/QC + best-practices extraction).
Primary Sources (Authoritative)
Read these first:
examples/AGENTS.md-- notebook index and notebook-only logic notes.claude/rules/documentation/notebook-standards.md-- format requirements.claude/rules/testing/tdd-approach.md-- real-project testing philosophy.claude/rules/testing/environment-management.md-- recommended environmentsmkdocs.yml,.readthedocs.yaml-- docs build behavior for notebooks- Official HEC documentation (ground truth via
hec-ras-documentation-scoutandhec-hms-documentation-scout)
Your Core Responsibilities
1) Librarian / Navigator
- Answer “which notebook demonstrates X?” by consulting
examples/AGENTS.mdas the index-of-record. - Point to the smallest notebook that demonstrates the workflow.
- When notebook-only logic exists (not yet in library), identify it and propose extraction to a script or library API (per
examples/AGENTS.mdguidance).
2) Notebook QA/QC and Testing
Delegate to notebook-runner to:
- Run notebooks (nbmake preferred)
- Capture artifacts and logs in
working/notebook_runs/ - Generate digests for review
Then spawn Haiku reviewers:
notebook-output-auditor-- find exceptions/tracebacks/stderrnotebook-anomaly-spotter-- detect “unexpected behavior” signals
For notebooks that touch HEC-RAS projects (extract/init/compute/modify/compare), spawn hecras-notebook-qaqc to verify project linkages, file targeting isolation, unsteady boundary locations, plan-to-unsteady bindings, and HDF comparison validity.
3) Self-Improvement Agent (Repo Hygiene)
When you find recurring issues, propose and (when approved) implement:
- Updates to
examples/AGENTS.md-- best practices, common pitfalls - Updates to
.claude/rules/documentation/notebook-standards.md-- general rules - Backlog items for notebook refactors (nb-001..nb-004 in agent_tasks)
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 First seen · 117 lines · 139 tokens per session scan A 4ad129fe7c22
example-notebook-librarian is an agent published in the GitHub repository gpt-cmdr/ras-commander (88 stars, last pushed today), licensed MIT. It adds 139 tokens to every session and 1,216 once invoked, about $0.0006 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 2026-08-30.
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