Dc Dc Converters

Community

npuzsy

dc-dc-converters

Use when working on Simulink or Simscape Electrical DC-DC converter models, including buck, boost, buck-boost, flyback, forward, resonant, bidirectional converters, MPPT front ends, duty-cycle control, and regulation diagnostics.

Overview

Publisher	npuzsy
Repository	`simulink-power-electronics`
Skill name	`dc-dc-converters`
Stars	101
Forks	6
Bundled files	1
License	Apache-2.0
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by npuzsy on GitHub. Read the source before you install it.

Installation

Install the Dc Dc Converters AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/npuzsy/simulink-power-electronics/tree/master/subskills/dc-dc-converters
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/npuzsy/simulink-power-electronics/tree/master/subskills/dc-dc-converters

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/npuzsy/simulink-power-electronics.git /tmp/simulink-power-electronics
mkdir -p .claude/skills
cp -r /tmp/simulink-power-electronics/subskills/dc-dc-converters .claude/skills/dc-dc-converters

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dc Dc Converters in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Dc Dc Converters on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Dc Dc Converters is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

DC-DC Converters

Status

Developing subskill. Use this file to recognize DC-DC converter scope and choose evidence to collect. Apply the root workflow; do not reuse inverter waveform-balance rules for regulation or ripple problems.

Read references/inspection.md for corpus-derived inspection notes before diagnosing DC-DC examples. Treat those notes as developing guidance, not a complete methodology.

For generated or repaired Simscape Electrical schematics, also read ../../references/simscape-layout.md. DC-DC converters are sensitive to schematic readability because the return node, switch node, and output node are high-degree physical networks that generic automatic layout often routes poorly.

Scope

buck, boost, buck-boost, flyback, forward, and isolated DC-DC converters
resonant and soft-switching DC-DC converters
bidirectional converters for batteries, storage, and DC buses
duty-cycle, current-mode, voltage-mode, and MPPT-linked control paths

Evidence To Collect

topology, operating mode, switching frequency, input/output voltage, load, and duty range
inductor current, capacitor voltage, switch stress, and controller saturation signals
startup, load-step, line-step, or MPPT transient window used for validation
continuous/discontinuous conduction assumptions and sensor polarity
visual node map for generated component-level models: input positive, switching node, output positive, and return rail

Generated Layout Workflow

When asked to generate or clean up a DC-DC Simscape model:

Select the visual family:
- simple converter pipeline for buck/boost/buck-boost/SEPIC/Cuk
- bridge/symmetric layout for full-bridge or bidirectional converters
- resonant pipeline for LLC/series/parallel resonant converters
- subsystem-level converter block when the purpose is control/regulation
Name the electrical nodes before drawing:
- VIN_POS
- SW or commutation midpoint
- VOUT_POS
- RETURN
Place the physical power stage before control or scopes:
- source on the left
- switching device and freewheel path in the middle-left
- energy storage/output filter in the middle-right
- load on the right
- return rail as a bottom local rail
Place PWM/control below or above the switch, and place measurement/scopes at the measured node or at the right edge.
Reject layouts where the return/common node routes to a remote canvas edge or wraps around unrelated blocks.

Current Corpus-Derived Boundary

The current corpus contains many DC-DC library/helper candidates and fewer compiled runnable examples than motor drives. Use this subskill confidently for classification and evidence planning, but require a compiled, simulated, or measured state before promoting regulation/ripple rules.

For copied or downloaded DC-DC examples, prefer whole example folders or dependency closures. A single .slx often opens but does not provide enough initialization context for simulation-backed conclusions.

Promote When

Promote only after adding representative topologies, control-loop validation standards, transient/load-step checks, and scripts or model tests for regulation and device stress.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

references/inspection.md3 KB

Frequently asked questions

What does the Dc Dc Converters AI skill do?

Why use Dc Dc Converters on TypingMind?

Because you install it once and use it with any model. Dc Dc Converters is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Dc Dc Converters in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/npuzsy/simulink-power-electronics/tree/master/subskills/dc-dc-converters. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Dc Dc Converters?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Dc Dc Converters?

As many as you like. As long as a model supports skills, you can use Dc Dc Converters with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Dc Dc Converters AI skill free?

Yes. It is published on GitHub by npuzsy under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

DC-DC Converters

Status

Scope

Evidence To Collect

Generated Layout Workflow

Current Corpus-Derived Boundary

Promote When

Bundled files

Frequently asked questions

Related AI Skills

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