Rstest Debugging

Organization

rstackjs

rstest-debugging

Diagnose Rstest startup, build, runtime, logging, memory, or performance problems using traces and comparable measurements.

Overview

Publisher	rstackjs
Repository	`agent-skills`
Skill name	`rstest-debugging`
Stars	93
Forks	4
Bundled files	4
License	MIT
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.
4 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by rstackjs on GitHub. Read the source before you install it.

Installation

Install the Rstest Debugging 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.
Enable the skill in any chat where you want it available.

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/rstackjs/agent-skills.git /tmp/agent-skills
mkdir -p .claude/skills
cp -r /tmp/agent-skills/skills/rstest-debugging .claude/skills/rstest-debugging

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

Use it in TypingMind

Enable Rstest Debugging 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 Rstest Debugging 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 Rstest Debugging 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.

Rstest debugging

Diagnose the measured lifecycle stage before changing configuration. Keep behavior and the test manifest fixed, change one variable at a time, and remove experiments that do not produce a repeatable benefit.

Workflow

Establish comparable single-file and full-scope baselines with references/performance-measurement.md.
Run rstest --trace when supported and classify the cost as host build/startup, runtime load/setup/collect, test bodies/hooks, or CLI/report/teardown overhead.
Use DEBUG=rstest for resolved config and build output. For Rstest 0.11.7+ experimental per-test bundle coverage, follow references/performance-measurement.md. Use Rsdoctor only after evidence points to the compiler. Use verbose reporting or a profiler only after narrowing to runtime files/cases.
If dependency loading or compilation is implicated, read references/dependency-bundling.md. Compare the environment default, bundleDependencies: false, and bundleDependencies: true; neither bundling nor externalization is universally faster.
If a fully mocked heavy module still reaches the build graph, read references/mocked-module-build-graph.md before testing an exact external.
If assets, console output, pools, isolation, or memory dominate, read references/runtime-output-memory.md.
Rerun the representative file and full scope. Keep a change only when behavior, discovery, snapshots, and coverage remain valid and the benefit survives repeated measurement. Remove traces, profiles, and .rstest debug artifacts created by the diagnosis before handing off.

Guardrails

Use the project's installed Rstest for final claims. Label local checkout or unreleased diagnostic results separately.
Keep Node version, test files, coverage, cache state, environment, workers, and command shape fixed while comparing.
Do not add worker durations that overlap or subtract runner/build/tests values without verifying their lifecycle boundaries.
Do not treat aggregate process-tree RSS as physical memory; it can double-count shared pages.
Do not disable isolation, reduce coverage, silence failures, or change production/test semantics for a benchmark win.
Do not stack speculative aliases, externals, compiler hooks, pool settings, or caches. Preserve only the measured minimum.

Handoff from migration

When invoked from migrate-to-rstest, first confirm that the Jest/Vitest and Rstest manifests match. If the migration intentionally adds tests, report same-scope performance separately from final expanded-scope performance.

Bundled files

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

Frequently asked questions

What does the Rstest Debugging AI skill do?

Diagnose Rstest startup, build, runtime, logging, memory, or performance problems using traces and comparable measurements.

Why use Rstest Debugging on TypingMind?

Because you install it once and use it with any model. Rstest Debugging 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 Rstest Debugging in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/rstackjs/agent-skills/tree/main/skills/rstest-debugging. 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 Rstest Debugging?

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 Rstest Debugging?

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

Is the Rstest Debugging AI skill free?

Yes. It is published on GitHub by rstackjs under the MIT 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

Rstest debugging

Workflow

Guardrails

Handoff from migration

Bundled files

Frequently asked questions

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