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 skills add causify-ai/helpers --skill notebook.implement_outlinegit clone --depth 1 https://github.com/causify-ai/helpersWrote 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/skills/causify-ai/helpers/notebook.implement_outline)<a href="https://agentmods.dev/skills/causify-ai/helpers/notebook.implement_outline"><img src="https://agentmods.dev/badge/skills/causify-ai/helpers/notebook.implement_outline/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/skills/causify-ai/helpers/notebook.implement_outline"><img src="https://agentmods.dev/badge/skills/causify-ai/helpers/notebook.implement_outline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 3 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
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 | $0.00011 | $0.01022 |
| Opus 5.5 | $0.00004 | $0.00409 |
| Sonnet 5.5 | $0.00002 | $0.00204 |
| Haiku 4.5 | $0.00001 | $0.00102 |
Grade A, and why
notebook.implement_outline 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 15d 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Goal
- Input: A
notebook_outline.<TAG>.mdoutline file describing each notebook cell (created via.claude/skills/notebook.create_outline/SKILL.md) - Outputs:
.ipynbfile: Fully functional Jupyter notebook with working code, visualizations, and interactive widgets.pyfile: A Python file paired usingjupytextto the.ipynbusing py:percent*_utils.pyfile: Reusable helper functions for the notebook code
- Purpose: Implement the pedagogical design as a fully executable, interactive notebook
- Each visualization follows the triplet structure:
- Pre-visualization markdown (goal, then the input/panel description)
- Code cell (visualization / interactive widget)
- Post-visualization markdown (guided usage: actions plus observations, then
the implementation followed by the
print_obj_info()code cell)
Core Workflow
- Understand the outline: Review each cell's Purpose, Display, and (if present) Widgets and Guided Usage
- Implement utility functions: Write reusable widget and visualization code in
*_utils.py - Create notebook cells: Add markdown cells (context) and code cells (widget calls) to the notebook
- Follow the separation principle: Utilities contain implementation; notebook contains only function calls
Key Conventions
- Follow
.claude/skills/notebook.rules.md: General notebook conventions and structure, especially:## Visualization Cell Triplet Details: Pre-viz and post-viz markdown cells# Visualization and Interactivity: Widget patterns and comments panel conventions
- Follow outline cell format from
.claude/skills/notebook.create_outline/SKILL.md - Follow
.claude/skills/coding.rules.mdfor Python code in*_utils.pyand in the Python cells in.ipynbfile - Follow
.claude/skills/notebook.rules.md# Code Architecture and Responsibility->## Utilities vs. Notebook Responsibilitiesfor organizing utility files and notebooks
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.
- 15d ago Changed · +1 lines fc9b743c1b5a
- 1mo ago Changed · +2 lines 9a44e8894b5d
- 1mo ago Changed · +10 lines · -5 tokens per session b567355eb35b
- 1mo ago First seen · 93 lines · 16 tokens per session scan A bb7c0246d29c
notebook.implement_outline is a skill published in the GitHub repository causify-ai/helpers (150 stars, last pushed yesterday), licensed Apache-2.0. It adds 11 tokens to every session and 1,022 once invoked, about $0.0000 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 2026-09-03.
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