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/omril321/automated-notebooklmWrote 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/rules/omril321/automated-notebooklm/clean-code)<a href="https://agentmods.dev/rules/omril321/automated-notebooklm/clean-code"><img src="https://agentmods.dev/badge/rules/omril321/automated-notebooklm/clean-code/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/rules/omril321/automated-notebooklm/clean-code"><img src="https://agentmods.dev/badge/rules/omril321/automated-notebooklm/clean-code.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 | $0.00191 | $0.00191 |
| Opus 5.5 | $0.00076 | $0.00076 |
| Sonnet 5.5 | $0.00038 | $0.00038 |
| Haiku 4.5 | $0.00019 | $0.00019 |
Grade A, and why
clean-code 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
Summary: Encourage clean, modular code through small, single-purpose functions with clear inputs and outputs.
Guidelines:
- Functions must follow the Single Responsibility Principle.
- Keep functions short — ideally under one screen of code.
- Use descriptive names for clarity (e.g., fetchUserData, not getData).
- Prefer pure functions; make side effects explicit when necessary.
- Avoid deep nesting — use guard clauses and helper functions.
- Follow consistent formatting and avoid code duplication.
Avoid:
- Monolithic functions doing multiple things
- Vague or generic naming
- Repeated logic
- Over-commenting obvious code
- Unclear control flow due to nesting
- Best Practices Enforcement:
- Prioritize in code reviews
- Use linters/static analysis for complexity and style issues
- Encourage refactoring and pairing to share clean code habits
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 · 30 lines · 191 tokens per session scan A aed42b3ea5cd
clean-code is a cursor rule published in the GitHub repository omril321/automated-notebooklm (14 stars, last pushed 8mo ago), licensed Apache-2.0. It adds 191 tokens to every session, about $0.0008 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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