Plugin Fleet Sweep logo

Plugin Fleet Sweep

Organization
oh-my-dsh
plugin-fleet-sweep

Use when the DSH host itself has been upgraded (or is about to be) and the whole installed fleet of Web/client plugins must be checked against the new host - one or more surfaces broke, vanished, or need their compatibility re-verified and re-released. Also use after a host upgrade to sweep for silent breaks before the user reports them, and to run the per-plugin fix/release loop (branch, bump, changelog, tag, mirrors).

Overview

Publisheroh-my-dsh
Repositorydsh-plugin-upgrade-skill
Skill nameplugin-fleet-sweep
Stars
300
Forks
36
Bundled files
1
LicenseMIT
Links
  • 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 oh-my-dsh on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/oh-my-dsh/dsh-plugin-upgrade-skill/tree/main/skills/plugin-fleet-sweep
  4. 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.
2

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/oh-my-dsh/dsh-plugin-upgrade-skill.git /tmp/dsh-plugin-upgrade-skill
mkdir -p .claude/skills
cp -r /tmp/dsh-plugin-upgrade-skill/skills/plugin-fleet-sweep .claude/skills/plugin-fleet-sweep
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Plugin Fleet Sweep 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 Plugin Fleet Sweep 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 Plugin Fleet Sweep 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.

Sweep a Plugin Fleet Across a DSH Host Upgrade

A host upgrade changes the contracts every plugin rides on at once. The unit of work is not one plugin: it is the fleet, swept in a fixed order, with one verdict per plugin and one release loop per broken plugin. The sweep runs against the REAL upgraded host - sources and Node-based tests passing prove nothing about browser-engine and runtime-surface changes.

Standing rules

  1. Verify on the target host, not in sources. A plugin "loads" when its client bundle is served, its CSS style[data-plugin] tag exists, and zero slot entry crashed / activation-failure records appear. A plugin "works" only when its surface marker is in the DOM and its expected requests fire. Record which of the two you have proven.
  2. One static sweep first, cheaply. Grep every plugin source for the APIs the new host renamed or removed (from the target version's corridor cards in plugin-upgrade/references/) before touching a browser. Static hits are already verdicts: broken-until-fixed.
  3. Absence of errors is weak evidence. A surface whose UI is interaction-gated (appears only after a paste, a file operation, a focus event) shows nothing in a idle sweep. For each plugin, know its trigger and either simulate it or mark the verdict "loaded, interaction path not exercised" instead of claiming success.
  4. Fix and release per plugin, never as a fleet commit. Each broken plugin gets its own branch-or-main commit, version bump, changelog row, tag, and mirror push (the repositories' own mirror flow; sync-mirrors.mjs is specific to the author's plugin repositories - use whatever the target repository documents, or skip mirrors if it has none). Mixed fleet commits make per-plugin rollbacks impossible.
  5. Compatibility builds over host-locked builds when the plugin must span host generations: resolve renamed host exports at runtime through a fallback chain (old name → new variants) instead of static named imports, and extend unit-test module mocks with every fallback name (strict mocks throw on undefined-export access and mask the real failure).

Workflow

  1. Read the target host version's corridor cards (plugin-upgrade/references/v<target>.md) and derive the static sweep patterns from them - the cards name the renamed/removed surfaces.
  2. Static sweep: grep every fleet repository for those patterns; record hits as broken-until-fixed with file:line.
  3. Live sweep: load the real GUI in a driven headless browser against the upgraded host and per plugin assert (a) the client CSS/style tag present, (b) zero slot entry crashed console records, (c) the surface's DOM marker present, (d) the expected requests fired. Method: references/fleet-sweep-checklist.md (includes the authenticated-GUI access and instrumentation discipline from plugin-runtime-debug/references/browser-forensics.md).
  4. Re-verify interaction-gated surfaces with their trigger simulated (paste, file write, keyboard chord) or downgrade the verdict explicitly.
  5. For each broken plugin: diagnose against the host source (plugin-runtime-debug standing rule), fix with a host-generation-compatible approach when the fleet spans host versions, run the plugin's typecheck/tests/build, then release: version bump, changelog/compatibility-table row naming the host version range, commit, tag, mirrors.
  6. Re-run the live sweep after releases and record the final per-plugin verdict table (plugin, host versions supported, evidence).

Report

End with a per-plugin table: verdict (working / fixed+released / interaction-path-unexercised / broken), the host versions covered, and the evidence (which assertion passed where). Note any host bug found (report upstream with the minimal repro) and any hot-fix living in the install tree that the next host upgrade will overwrite - list the reapplication material.

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 Plugin Fleet Sweep AI skill do?

Use when the DSH host itself has been upgraded (or is about to be) and the whole installed fleet of Web/client plugins must be checked against the new host - one or more surfaces broke, vanished, or need their compatibility re-verified and re-released. Also use after a host upgrade to sweep for silent breaks before the user reports them, and to run the per-plugin fix/release loop (branch, bump, changelog, tag, mirrors).

Why use Plugin Fleet Sweep on TypingMind?

Because you install it once and use it with any model. Plugin Fleet Sweep 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 Plugin Fleet Sweep in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/oh-my-dsh/dsh-plugin-upgrade-skill/tree/main/skills/plugin-fleet-sweep. 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 Plugin Fleet Sweep?

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 Plugin Fleet Sweep?

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

Is the Plugin Fleet Sweep AI skill free?

Yes. It is published on GitHub by oh-my-dsh 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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