ml

ml is a skill for Claude Code, Codex from DNYoussef/context-cascade. It costs 0 tokens per session (1,844 once invoked), scanned A, original, MIT.

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.

In plain words
What is it for?
Use it to record machine-learning experiments, search for better parameter settings, and manage models as part of an MLOps process.
Why use it?
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.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: names the TodoWrite tool.

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

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/dnyoussef/context-cascade/ml
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.

agentmods badge for ml

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.

agentmods 80×15 button for ml

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 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 $0.00000 $0.01844
Opus 5.5 $0.00000 $0.00738
Sonnet 5 $0.00000 $0.00369
Haiku 4.5 $0.00000 $0.00184

Measured 20d ago against content hash cef5426f441f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-23, 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 20d 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

Copies of this mod

1 near-identical copy found in the catalogue:

  • ml — 95% identical, 6 lines differ
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

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. 20d 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 (31 stars, last pushed 2mo 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. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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