A machine-learning development workflow covering experiment tracking, tuning model settings, and operating models after they are built. Machine learning means teaching software to make predictions or decisions from data.

Use it to record machine-learning experiments, search for better parameter settings, and manage models as part of an MLOps process.

It keeps experiments and model improvements organized and connects development work with running models in production. The input does not specify the exact tools used.

ml — Skill for Claude Code and Codex by DNYoussef/context-cascade

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 DNYoussef/context-cascade --skill ml

Clone the repo

git clone --depth 1 https://github.com/DNYoussef/context-cascade

Made for: Claude Code, Codex.

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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/dnyoussef/context-cascade/ml/github.svg)](https://agentmods.dev/skills/dnyoussef/context-cascade/ml)

Your own site

<a href="https://agentmods.dev/skills/dnyoussef/context-cascade/ml"><img src="https://agentmods.dev/badge/skills/dnyoussef/context-cascade/ml/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/dnyoussef/context-cascade/ml"><img src="https://agentmods.dev/badge/skills/dnyoussef/context-cascade/ml.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,844 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 95% copy Near-identical to another mod 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.

Model	Per session	Once invoked
Fable 5.1	$0.00000	$0.01844
Opus 5.5	$0.00000	$0.00738
Sonnet 5.5	$0.00000	$0.00369
Haiku 4.5	$0.00000	$0.00184

Measured 2mo ago against content hash cef5426f441f, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ml 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.

The scan reads SKILL.md. This mod also ships 10 executable files (examples/experiment-tracking.py, examples/hyperparameter-optimization.js, examples/mlops-pipeline.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Origin

This is a copy

95% identical to ml — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/platforms/ml/SKILL.md · 238 lines

How it starts

The opening of the file, as written. The whole thing — 238 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/============================================================================/ /* ML SKILL :: VERILINGUA x VERIX EDITION / /============================================================================*/

name: ml version: 2.0.0 description: | [assert|neutral] Machine Learning development workflow with experiment tracking, hyperparameter optimization, and MLOps integration [ground:given] [conf:0.95] [state:confirmed] category: specialized-development tags:

machine-learning
mlops
experiment-tracking
hyperparameter-tuning
model-registry author: ruv cognitive_frame: primary: aspectual goal_analysis: first_order: "Execute ml workflow" second_order: "Ensure quality and consistency" third_order: "Enable systematic specialized-development processes"

/----------------------------------------------------------------------------/ /* S0 META-IDENTITY / /----------------------------------------------------------------------------*/

[define|neutral] SKILL := { name: "ml", category: "specialized-development", version: "2.0.0", layer: L1 } [ground:given] [conf:1.0] [state:confirmed]

/----------------------------------------------------------------------------/ /* S1 COGNITIVE FRAME / /----------------------------------------------------------------------------*/

[define|neutral] COGNITIVE_FRAME := { frame: "Aspectual", source: "Russian", force: "Complete or ongoing?" } [ground:cognitive-science] [conf:0.92] [state:confirmed]

Kanitsal Cerceve (Evidential Frame Activation)

Kaynak dogrulama modu etkin.

/----------------------------------------------------------------------------/ /* S2 TRIGGER CONDITIONS / /----------------------------------------------------------------------------*/

[define|neutral] TRIGGER_POSITIVE := { keywords: ["ml", "specialized-development", "workflow"], context: "user needs ml capability" } [ground:given] [conf:1.0] [state:confirmed]

/----------------------------------------------------------------------------/ /* S3 CORE CONTENT / /----------------------------------------------------------------------------*/

Read the full file on GitHub · 238 lines

Files

What ships with it

16 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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.

2mo ago First seen · 238 lines · 0 tokens per session scan A cef5426f441f

Subscribe to this mod's changes

ml is a skill published in the GitHub repository DNYoussef/context-cascade (32 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,844 tokens. A static security scan graded it A with 0 findings. It is 95% identical to ml, differing in 6 lines, and is treated as a copy.

Data and AI

ml next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
mlDNYoussef/context-cascade	Skill	32	3mo ago	MIT	A	0	Claude Code, Codex
agent-platform-model-registrygoogle/skills	Skill	23k	yesterday	Apache-2.0	A	60	Claude Code, Codex
foundry-config-setupmicrosoft/agent-framework	Skill	15k	yesterday	MIT	A	65	Claude Code, Codex
google-cloud-solution-agentic-analytics-spark-knowledge-cataloggoogle/skills	Skill	23k	yesterday	Apache-2.0	A	132	Claude Code, Codex
training-checkwanshuiyin/Auto-claude-code-research-in-sleep	Skill	19k	yesterday	MIT	A	35	Claude Code
nemo-automodel-launcher-configNVIDIA/skills	Skill	3.9k	yesterday	Apache-2.0	A	30	Claude Code
finetuningmicrosoft/skills	Skill	3.2k	yesterday	MIT	A	132	Claude Code