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.
npx agentmods add instructions/claude-world/notebooklm-skill/copilot-instructionsgit clone --depth 1 https://github.com/claude-world/notebooklm-skillWrote 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/instructions/claude-world/notebooklm-skill/copilot-instructions)<a href="https://agentmods.dev/instructions/claude-world/notebooklm-skill/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/claude-world/notebooklm-skill/copilot-instructions.svg" alt="Measured on agentmods" 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 | $0.00089 | $0.00089 |
| Opus 5 | $0.00044 | $0.00044 |
| Sonnet 5 | $0.00018 | $0.00018 |
| Haiku 4.5 | $0.00009 | $0.00009 |
Grade A, and why
notebooklm-skill copilot-instructions.md 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 5d 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
This Python project provides a JSON-first CLI, five async pipelines, and 13 MCP tools
for NotebookLM. Keep all notebooklm-py API adaptation in scripts/common.py so the
three public surfaces stay consistent. Follow the Ruff and mypy configuration, use
typed async code, and add behavior-focused pytest tests. Never log browser-state
cookies, overwrite output silently, or report partial upstream work as success.
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.
- 5d ago First seen · 6 lines · 89 tokens per session scan A 94bf2201d286
notebooklm-skill copilot-instructions.md is an instructions file published in the GitHub repository claude-world/notebooklm-skill (451 stars, last pushed 1mo ago), licensed MIT. It adds 89 tokens to every session, about $0.0004 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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