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Dart Package Maintenance

Community
kevmoo
dart-package-maintenance

Guidelines for maintaining external Dart packages, covering versioning, publishing workflows, and pull request management. Use when updating Dart packages, preparing for a release, or managing collaborative changes in a repository.

Overview

Publisherkevmoo
Repositorydash_skills
Skill namedart-package-maintenance
Stars
148
Forks
16
Bundled files
1
LicenseApache-2.0
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 kevmoo on GitHub. Read the source before you install it.

Installation

Install the Dart Package Maintenance 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/kevmoo/dash_skills/tree/main/skills/dart-package-maintenance
  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/kevmoo/dash_skills.git /tmp/dash_skills
mkdir -p .claude/skills
cp -r /tmp/dash_skills/skills/dart-package-maintenance .claude/skills/dart-package-maintenance
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dart Package Maintenance 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 Dart Package Maintenance 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 Dart Package Maintenance 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.

Dart Package Maintenance

Guidelines for maintaining Dart packages in alignment with the canonical Dart team External Package Maintenance specification.

When to use this skill

Use this skill when:

  • Updating Dart packages, preparing for a release, or managing collaborative changes in a repository.
  • Managing versioning, CHANGELOG.md synchronization, and publishing workflows.
  • Ensuring published packages comply with Dart team conventions.

When NOT to use (Abstention Guardrails)

Do NOT apply package maintenance version bumps or changelog updates when:

  • Internal / Private Packages: Packages marked publish_to: none in pubspec.yaml that are not published to pub.dev (e.g., application root packages or internal monorepo tooling).
  • Repository-Root Files or Historical CHANGELOG.md Typos: Pull requests that only modify repository-level files outside a published package (such as .github/workflows/, repo-root SKILL.md, or root docs in a monorepo) or that only fix typos/formatting in historical CHANGELOG.md sections.
  • In-Flight PR Commits: Intermediate commits on an active feature branch where the version already carries an appropriate -wip suffix.

Versioning

Semantic Versioning

Dart packages use semantic versioning with a pre-1.0.0 variation where the version numbers are shifted to the right before a 1.0.0 release; see also the package:pub_semver semantics:

  • Packages at 1.0.0 or later: major.minor.patch.
  • Packages not yet at 1.0.0: 0.major.minor, where the second number is bumped for breaking changes, such as 0.4.2 to 0.5.0-wip, and the third number is bumped for non-breaking features and bug fixes, such as 0.4.2 to 0.4.3-wip. Avoid +1 build suffixes (in package:pub_semver, 0.4.2+1-wip parses +1-wip as build metadata rather than a -wip pre-release).
  • Recommendation: Aim to publish 1.0.0 as soon as the package is stable.

Choose the version bump based on the impact of the change:

  • Major: Breaking changes, including removing or renaming a pubspec.yaml executables entry.
  • Minor: New features and non-breaking API changes, such as introducing a new class or adding a pubspec.yaml executables entry.
  • Patch: Bug fixes, minimum environment.sdk or runtime dependencies constraint updates, or any other change that does not impact calling code.

Updating the Version

Whenever the code in the repo differs from the latest version published on pub.dev, both pubspec.yaml and CHANGELOG.md must use a -wip version. We bump to -wip on the first change after a release, even if we don't plan on publishing the code in that state or if the change doesn't impact consumers.

When opening or merging a PR, check the current version in pubspec.yaml and CHANGELOG.md:

  • Currently at a published version, such as 1.2.3: Perform the appropriate version bump, append -wip in pubspec.yaml, and add a matching ## <version>-wip section at the top of CHANGELOG.md.
  • Already at a -wip version, such as 1.2.4-wip: Compare the existing -wip bump against the bump required for your change. If your change requires a larger bump, such as from a patch bump to a minor bump when adding a feature, update pubspec.yaml and rename the existing ## <version>-wip heading in CHANGELOG.md in place.
  • Not yet published to pub.dev, at 0.1.0-wip: Keep 0.1.0-wip and the - Initial release. entry without adding per-PR changelog entries until after the first release.

Updating CHANGELOG.md

  • User-visible changes: Add an entry under the top -wip section.
  • Internal or non-user-visible changes, such as safe refactorings, lint cleanups, test/, tool/, or README.md updates, or dev_dependencies and dependency_overrides changes:
    • If your PR creates the new -wip section, add the ## <version>-wip heading with no bullet items below it.
    • If the package is already at a -wip version, leave CHANGELOG.md untouched and apply the skip-changelog-check PR label.
  • Follow-up edits to unreleased work: If a subsequent PR modifies or reverts an unreleased change in the current -wip section, such as bumping an SDK or dependency constraint again before publishing, update or remove the existing -wip bullet in place instead of adding a duplicate entry.
  • Already-published sections: Never add new entries under an already-published version heading, especially after merging main when a release landed while your PR was open.

Breaking Changes

  • Evaluate the impact on dependent packages and internal projects.
  • Consider running changes through internal presubmits if possible.
  • Prefer incremental rollouts (e.g., new behavior as opt-in) to minimize downstream breakage.

Publishing Process

  1. Preparation: Remove the -wip suffix from pubspec.yaml and CHANGELOG.md in a dedicated pull request.
  2. Execution: Run dart pub publish (or flutter pub publish) and resolve all warnings and errors.
  3. Tagging: Create and push a git tag for the published version:
    • For single-package repos: v1.2.3
    • For monorepos: package_name-v1.2.3
    • Example: git tag v1.2.3 && git push --tags

Pull Request Management

  • Commits: Each PR should generally correspond to a single squashed commit upon merging.
  • Shared History: Once a PR is open, avoid force pushing to the branch.
  • Conflict Resolution: Prefer merging main into the PR branch rather than rebasing to resolve conflicts. This preserves the review history and comments.
  • Reviewing: Add comments from the "Files changed" view to batch them.
  • Local Inspection: Use gh pr checkout <number> to inspect changes locally in your IDE.

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 Dart Package Maintenance AI skill do?

Guidelines for maintaining external Dart packages, covering versioning, publishing workflows, and pull request management. Use when updating Dart packages, preparing for a release, or managing collaborative changes in a repository.

Why use Dart Package Maintenance on TypingMind?

Because you install it once and use it with any model. Dart Package Maintenance 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 Dart Package Maintenance in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/kevmoo/dash_skills/tree/main/skills/dart-package-maintenance. 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 Dart Package Maintenance?

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 Dart Package Maintenance?

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

Is the Dart Package Maintenance AI skill free?

Yes. It is published on GitHub by kevmoo 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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