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/llm-rule-srp)<a href="https://agentmods.dev/rules/omril321/automated-notebooklm/llm-rule-srp"><img src="https://agentmods.dev/badge/rules/omril321/automated-notebooklm/llm-rule-srp/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/llm-rule-srp"><img src="https://agentmods.dev/badge/rules/omril321/automated-notebooklm/llm-rule-srp.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 | $0.00000 | $0.00153 |
| Opus 5 | $0.00000 | $0.00077 |
| Sonnet 5 | $0.00000 | $0.00031 |
| Haiku 4.5 | $0.00000 | $0.00015 |
Grade A, and why
llm-rule-srp 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 9d 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: LLM tool definitions must act as thin wrappers that delegate functionality to well-defined, single-responsibility services.
Guidelines:
- Keep tool definitions minimal — focus on input schema, metadata, and delegation.
- All core logic must live in a dedicated service class with clear inputs and outputs.
- Services should be testable, reusable, and adhere to Single Responsibility Principle.
- Tool execute functions should be short, readable, and primarily call a service.
Avoid:
- Embedding complex logic directly in the tool definition
- Mixing concerns (e.g., schema + business logic + side effects) in one layer
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.
- 9d ago First seen · 21 lines · 153 tokens per session scan A 6775beb6a09d
llm-rule-srp is a cursor rule published in the GitHub repository omril321/automated-notebooklm (15 stars, last pushed 7mo ago), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 153 tokens. 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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