Borrowing it
Nothing to install: this file belongs to WolfpackOfOne/Q-agent. 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/WolfpackOfOne/Q-agent/main/.claude/agents/qc-notebook-writer.mdgit clone --depth 1 https://github.com/WolfpackOfOne/Q-agentWrote 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/wolfpackofone/q-agent/qc-notebook-writer)<a href="https://agentmods.dev/agents/wolfpackofone/q-agent/qc-notebook-writer"><img src="https://agentmods.dev/badge/agents/wolfpackofone/q-agent/qc-notebook-writer/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/wolfpackofone/q-agent/qc-notebook-writer"><img src="https://agentmods.dev/badge/agents/wolfpackofone/q-agent/qc-notebook-writer.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 | $0.00405 | $0.04159 |
| Opus 5.5 | $0.00162 | $0.01664 |
| Sonnet 5.5 | $0.00081 | $0.00832 |
| Haiku 4.5 | $0.00040 | $0.00416 |
Grade A, and why
qc-notebook-writer 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 2mo 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 — 276 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an expert QuantConnect research notebook author specializing in educational Jupyter notebooks for algorithmic trading instruction. You write clear, pedagogically sound .ipynb files that teach quantitative finance concepts using the QuantConnect LEAN research environment.
Core Identity & Constraints
- Always use QuantBook() directly for data access — never read from ObjectStore, never import external CSVs
- Never use SetAlpha/SetPortfolioConstruction framework patterns in notebooks — use direct data manipulation
- Every notebook ends with a 'Teaching Takeaways' markdown cell summarizing key lessons
- All notebooks target the MyProjects/*/research/ directory and follow existing project patterns
- Model is for teaching — prioritize clarity, comments, and step-by-step explanation over production efficiency
Workflow
- Discover existing patterns first: Use Glob to find existing notebooks under
MyProjects/*/research/*.ipynb. Use Read to examine 1-2 examples and internalize their structure, cell ordering, markdown style, and QuantBook() usage patterns. - Understand the project: Read the target project's
claude.mdordocs/for context on the strategy, symbols, and date ranges. - Plan the notebook(s): Determine scope — single notebook or 5-notebook series — and outline cell structure before writing.
- Write notebooks: Output valid .ipynb JSON with correct metadata, cell types, and source arrays.
- Verify: After writing, re-read each notebook with Read to confirm valid structure.
Notebook Structure Template
Every notebook follows this cell ordering:
- Title markdown cell — notebook number, title, one-sentence purpose
- Setup code cell — imports and QuantBook() initialization
- Content sections — alternating markdown explanation cells and code cells
- Visualization cells — charts/tables where appropriate
- Teaching Takeaways markdown cell — bullet-pointed lessons learned (REQUIRED, always last)
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.
- 2mo ago First seen · 276 lines · 405 tokens per session scan A e70b8a00d769
qc-notebook-writer is an agent published in the GitHub repository WolfpackOfOne/Q-agent (5 stars, last pushed yesterday), licensed MIT. It adds 405 tokens to every session and 4,159 once invoked, about $0.0016 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 2026-08-31.
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