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Agent skill

Optimizing Deep Learning Models

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Optimize deep learning models using Adam, SGD, and learning rate scheduling to improve accuracy and reduce training time.

MITAuto-check passedAI & LLM Engineering

Install Optimizing Deep Learning Models

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill optimizing-deep-learning-models -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace optimizing-deep-learning-models --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/optimizing-deep-learning-models .claude/skills/optimizing-deep-learning-models && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
optimizing-deep-learning-models
GitHub stars
2.8k
Token cost
~989 tokens
SKILL.md length
450 words
Files
6 (incl. scripts, references, assets)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Optimize deep learning models using Adam, SGD, and learning rate scheduling to improve accuracy and reduce training time.

  • Works in 4 steps: Analyze Model: Examines the deep… → Identify Optimizations: Determines the… → Apply Optimizations: Generates optimized… → …
  • Asked to optimize deep learning model
  • SKILL.md covers Overview, How It Works, When to Use This Skill and Examples, plus 7 more sections
  • Runs Python scripts from its folder

What it does

Optimizing Deep Learning Models is an agent skill from jeremylongshore/tons-of-skills-marketplace. Optimize deep learning models using Adam, SGD, and learning rate scheduling to improve accuracy and reduce training time. Use when asked to "optimize deep learning model" or "improve model performance". Trigger with phrases like 'optimize', 'performance', or 'speed up'.

Its SKILL.md is about 990 tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including scripts, reference files and assets (for example `assets/README.md`, `assets/optimization_config.json` and `references/README.md`). Compatibility notes: Designed for Claude Code

It sits in AI & LLM Engineering, covering Deep learning. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • Asked to optimize deep learning model
  • Improve model performance
  • With phrases like optimize

Example prompts

  • “optimize deep learning model”
  • “improve model performance”
  • “optimize”
  • “/optimizing-deep-learning-models”

Requirements

  • Python 3
  • Compatibility (from SKILL.md): Designed for Claude Code
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Grep, Glob, Bash(cmd:*)

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Analyze Model: Examines the deep learning model's architecture, training data, and performance metrics.
  2. Identify Optimizations: Determines the most effective optimization strategies based on the analysis, such as adjusting the learning rate…
  3. Apply Optimizations: Generates optimized code that implements the chosen strategies.
  4. Evaluate Performance: Assesses the impact of the optimizations on model performance, providing metrics like accuracy, training time, and…

What it can do on your machine

Read from SKILL.md and the folder at commit 80f86df. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Grep
    • Glob
    • Bash(cmd:*)

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Claude Code

    From compatibility in the SKILL.md frontmatter.

Context cost

Optimizing Deep Learning Models loads about 989 tokens when it runs, and up to ~1k if it reads all its reference files. Until then it costs about 76 tokens; SKILL.md has 450 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~76
When it runs · the whole SKILL.md, loaded when a task matches
~989
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit 80f86df, republished under its MIT licence (© jeremylongshore). 450 words, ~989 tokens.

Download SKILL.mdSave it as .claude/skills/optimizing-deep-learning-models/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
optimizing-deep-learning-models
description
Optimize deep learning models using Adam, SGD, and learning rate scheduling to improve accuracy and reduce training time. Use when asked to "optimize deep learning model" or "improve model performance". Trigger with phrases like 'optimize', 'performance', or 'speed up'.
allowed-tools
Read, Write, Edit, Grep, Glob, Bash(cmd:*)
compatibility
Designed for Claude Code
version
1.23.0
author
Jeremy Longshore <jeremy@intentsolutions.io>
license
MIT
tags
ai, performance, optimizing-deep

Deep Learning Optimizer

Optimize deep learning models by tuning optimizers (Adam, SGD), learning rate schedules, and regularization strategies to improve accuracy and reduce training time.

Overview

This skill empowers Claude to automatically optimize deep learning models, enhancing their performance and efficiency. It intelligently applies various optimization techniques based on the model's characteristics and the user's objectives.

How It Works

  1. Analyze Model: Examines the deep learning model's architecture, training data, and performance metrics.
  2. Identify Optimizations: Determines the most effective optimization strategies based on the analysis, such as adjusting the learning rate, applying regularization techniques, or modifying the optimizer.
  3. Apply Optimizations: Generates optimized code that implements the chosen strategies.
  4. Evaluate Performance: Assesses the impact of the optimizations on model performance, providing metrics like accuracy, training time, and resource consumption.

When to Use This Skill

This skill activates when you need to:

  • Optimize the performance of a deep learning model.
  • Reduce the training time of a deep learning model.
  • Improve the accuracy of a deep learning model.
  • Optimize the learning rate for a deep learning model.
  • Reduce resource consumption during deep learning model training.

Examples

Example 1: Improving Model Accuracy

User request: "Optimize this deep learning model for improved image classification accuracy."

The skill will:

  1. Analyze the model and identify potential areas for improvement, such as adjusting the learning rate or adding regularization.
  2. Apply the selected optimization techniques and generate optimized code.
  3. Evaluate the model's performance and report the improved accuracy.
Show full SKILL.md (205 more words)Show less
Example 2: Reducing Training Time

User request: "Reduce the training time of this deep learning model."

The skill will:

  1. Analyze the model and identify bottlenecks in the training process.
  2. Apply techniques like batch size adjustment or optimizer selection to reduce training time.
  3. Evaluate the model's performance and report the reduced training time.

Best Practices

  • Optimizer Selection: Experiment with different optimizers (e.g., Adam, SGD) to find the best fit for the model and dataset.
  • Learning Rate Scheduling: Implement learning rate scheduling to dynamically adjust the learning rate during training.
  • Regularization: Apply regularization techniques (e.g., L1, L2 regularization) to prevent overfitting.

Integration

This skill can be integrated with other plugins that provide model building and data preprocessing capabilities. It can also be used in conjunction with monitoring tools to track the performance of optimized models.

Prerequisites

  • Appropriate file access permissions
  • Required dependencies installed

Instructions

  1. Invoke this skill when the trigger conditions are met
  2. Provide necessary context and parameters
  3. Review the generated output
  4. Apply modifications as needed

Output

The skill produces structured output relevant to the task.

Error Handling

  • Invalid input: Prompts for correction
  • Missing dependencies: Lists required components
  • Permission errors: Suggests remediation steps

Resources

  • Project documentation
  • Related skills and commands

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (scripts, references, assets) in skills/.curated/optimizing-deep-learning-models of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • assets/README.md
  • assets/optimization_config.json
  • references/README.md
  • scripts/README.md
  • scripts/analyze_model.py

Open the folder on GitHubat commit 80f86df

Compare with similar skills

Optimizing Deep Learning Models next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Optimizing Deep Learning Models compared with similar skills
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Optimizing Deep Learning Models this skilljeremylongshore/tons-of-skills-marketplace2.8k—~989Automated safety check: PassMIT
Add Uint Supportpytorch/pytorch104k2 repos~2.3kAutomated safety check: PassCustom licence
Segment Anything Model GuideOrchestra-Research/AI-Research-SKILLs13k8 repos~3.3kAutomated safety check: PassMIT
Add Oponnx/onnx22k—~1.2kAutomated safety check: PassApache-2.0
CLIP Image-Text MatchingOrchestra-Research/AI-Research-SKILLs13k7 repos~1.7kAutomated safety check: PassMIT
Add Function Bodyonnx/onnx22k—~1.1kAutomated safety check: PassApache-2.0

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Categories

Questions about Optimizing Deep Learning Models

What does Optimizing Deep Learning Models do?

Optimize deep learning models using Adam, SGD, and learning rate scheduling to improve accuracy and reduce training time. Optimizing Deep Learning Models is an agent skill from jeremylongshore/tons-of-skills-marketplace. Optimize deep learning models using Adam, SGD, and learning rate scheduling to improve accuracy and reduce training time.

When should I use Optimizing Deep Learning Models?

Optimizing Deep Learning Models fits situations like: asked to optimize deep learning model; improve model performance; with phrases like optimize.

How do I install Optimizing Deep Learning Models in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill optimizing-deep-learning-models -a claude-code`. Or copy the skill folder (skills/.curated/optimizing-deep-learning-models in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/optimizing-deep-learning-models in your project. Claude Code loads it when a task matches its description.

How do I install Optimizing Deep Learning Models in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill optimizing-deep-learning-models -a codex`. Or copy the skill folder (skills/.curated/optimizing-deep-learning-models in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/optimizing-deep-learning-models in your project. Codex loads it when a task matches its description.

Can I use Optimizing Deep Learning Models in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill optimizing-deep-learning-models -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/optimizing-deep-learning-models, .gemini/skills/optimizing-deep-learning-models, .github/skills/optimizing-deep-learning-models and .opencode/skills/optimizing-deep-learning-models in your project.

What does Optimizing Deep Learning Models need to run?

Going by SKILL.md and its folder, Optimizing Deep Learning Models needs Python for the scripts in its folder. Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Write, Edit, Grep, Glob, Bash(cmd:*). Compatibility (from SKILL.md): Designed for Claude Code.

Does Optimizing Deep Learning Models access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Optimizing Deep Learning Models safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Optimizing Deep Learning Models use?

Optimizing Deep Learning Models is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Optimizing Deep Learning Models use?

About 989 tokens (SKILL.md is roughly 4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 17 tokens, read only when the agent opens those files.

What are the alternatives to Optimizing Deep Learning Models?

Skills that share tags, products or a category with Optimizing Deep Learning Models: Add Uint Support (pytorch/pytorch, 104k stars), Segment Anything Model Guide (Orchestra-Research/AI-Research-SKILLs, 13k stars), Add Op (onnx/onnx, 22k stars) and CLIP Image-Text Matching (Orchestra-Research/AI-Research-SKILLs, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Optimizing Deep Learning Models?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,825 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 9, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.