blog.write_ml_tutorial

blog.write_ml_tutorial is a skill for Claude Code from gpsaggese/helpers. It costs 14 tokens per session (355 once invoked), scanned A, original, Apache-2.0.

A blog-writing routine for explaining a machine-learning library or technique in a practical application. Machine learning is software that learns patterns from data to make predictions or decisions.

In plain words
What is it for?
Use it to produce a structured tutorial with an introduction, alternatives, problem, solution, code, examples, and references.
Why use it?
It helps technical readers understand an unfamiliar tool through a real use case, examples, comparisons, and code.

Skill for Claude Code

Written for Claude Code: installed under .claude/. Also seen: model in frontmatter.

Good fit Use it to produce a structured tutorial with an introduction, alternatives, problem, solution, code, examples, and references.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/gpsaggese/helpers/blog.write_ml_tutorial
Install

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.

Any agent
npx skills add gpsaggese/helpers --skill blog.write_ml_tutorial
Clone the repo
git clone --depth 1 https://github.com/gpsaggese/helpers

Made for: Claude Code.

Wrote 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.

agentmods badge for blog.write_ml_tutorial

README.md
[![agentmods](https://agentmods.dev/badge/skills/gpsaggese/helpers/blog.write_ml_tutorial/github.svg)](https://agentmods.dev/skills/gpsaggese/helpers/blog.write_ml_tutorial)
Your own site
<a href="https://agentmods.dev/skills/gpsaggese/helpers/blog.write_ml_tutorial"><img src="https://agentmods.dev/badge/skills/gpsaggese/helpers/blog.write_ml_tutorial/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.

agentmods 80×15 button for blog.write_ml_tutorial

Your own site · 80×15
<a href="https://agentmods.dev/skills/gpsaggese/helpers/blog.write_ml_tutorial"><img src="https://agentmods.dev/badge/skills/gpsaggese/helpers/blog.write_ml_tutorial.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 14 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 355 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00014 $0.00355
Opus 5.5 $0.00006 $0.00142
Sonnet 5.5 $0.00003 $0.00071
Haiku 4.5 $0.00001 $0.00036

Measured yesterday against content hash 0faa8b5fc4ba, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 yesterday.

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.

.claude/skills/blog.write_ml_tutorial/SKILL.md · 43 lines

What it actually says

Goal

  • Write a blog post about using an ML library or technique in a real-world application
  • Target a technical audience with an ML and AI background that may not know the library or technique
  • Promote the library and explain its benefits in simple terms
  • Explain why it is better than alternatives for the use case

Workflow

Write the Post

  • Follow this structure:
    • Title
    • Subtitle: short description of the post, 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 solves it
    • Solution: explain the solution with code snippets, output examples, and screenshots, simple enough to follow without running the code
    • Conclusion: summarize the benefits and why it is better for the use case
    • References: list the references used to write the post
  • Give each section a concise, interesting title

Conventions

  • Use Markdown and LaTeX for math equations
  • Use Graphviz for diagrams
  • Use the images referenced in the Markdown and Jupyter Notebook files in the project

Verification

  • Confirm the post follows the required structure (Title, Subtitle, Introduction, Competitors, Problem Statement, Solution, Conclusion, References)
  • Confirm code snippets and screenshots let the reader follow along without running the code
Changes

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.

  1. yesterday First seen · 43 lines · 14 tokens per session scan A 0faa8b5fc4ba

Subscribe to this mod's changes

blog.write_ml_tutorial is a skill published in the GitHub repository gpsaggese/helpers (158 stars, last pushed today), licensed Apache-2.0. It adds 14 tokens to every session and 355 once invoked, about $0.0001 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 2026-11-06.

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