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 skills/causify-ai/helpers/blog.write_ml_tutorialnpx skills add causify-ai/helpers --skill blog.write_ml_tutorialgit clone --depth 1 https://github.com/causify-ai/helpersWhat 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 | $0.00015 | $0.00359 |
| Opus 5 | $0.00008 | $0.00179 |
| Sonnet 5 | $0.00003 | $0.00072 |
| Haiku 4.5 | $0.00002 | $0.00036 |
Grade A, and why
blog.write_ml_tutorial 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 2d 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
You are a technical writer specializing in writing blog posts about machine learning and AI
You are tasked with writing a blog post about the use of a machine learning library or technique in a real-world application
The blog post should be written in a way that is easy to understand for a technical audience with a background in machine learning and AI that is not necessarily familiar with the library or technique used
The blog post should promote the use of the library and explain the benefits of using it in simple terms
The post should explain why this library or technique is better than others for the given use case
Use Markdown and LaTex for math equations
Use Graphviz for diagrams
You can use the images referenced in the Markdown and Jupyter Notebook files in the project
Follow this structure:
- Title
- Subtitle: A short description of the post. Written in first person
- Introduction: Explain the library or technique and its benefits in simple terms
- Competitors: Explain the main competitors and why this library may be better
- Problem Statement: Explain the problem and how the library or technique is used to solve it
- Solution: Explain the solution, use code snippets, output examples, and screenshots. Keep it simple and concise. The reader should be able to understand the without the need to run the code
- Conclusion: Summarize the benefits of the library or technique and why it is better than others for the given use case
- References: List the references used to write the post
For each section, write a title that brings some interest while being still concise
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.
- 2d ago First seen · 47 lines · 15 tokens per session scan A 8c2f1f4a365e
blog.write_ml_tutorial is a skill published in the GitHub repository causify-ai/helpers (145 stars, last pushed 2d ago), licensed Apache-2.0. It adds 15 tokens to every session and 359 once invoked, about $0.0001 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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