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Release Kotlin Library

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chrisbanes
release-kotlin-library

Use when preparing, publishing, or checking readiness for a Kotlin library release, including verifying its gradle-maven-publish-plugin prerequisite, reconciling changelogs and API snapshots, and checking publication.

Overview

Publisherchrisbanes
Repositoryskills
Skill namerelease-kotlin-library
Stars
1.1K
Forks
53
Bundled files
6
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.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by chrisbanes on GitHub. Read the source before you install it.

Installation

Install the Release Kotlin Library 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/chrisbanes/skills/tree/main/skills/release-kotlin-library
  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/chrisbanes/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/release-kotlin-library .claude/skills/release-kotlin-library
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Release Kotlin Library 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 Release Kotlin Library 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 Release Kotlin Library 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.

Release Kotlin library

Core principle

Publish the prepared, validated, user-approved release commit and call the release complete only after verifying its artifacts and Git state.

Prerequisite

This skill relies on gradle-maven-publish-plugin (com.vanniktech.maven.publish) for library publication, whether run locally or through tag-triggered CI. API snapshot support assumes Metalava-generated api/api.txt files; disable snapshots when the repository does not maintain them.

Procedure

  1. Establish scope and inspect repository instructions, Git state, release history, version properties, publishing configuration and required checks. Confirm published modules apply com.vanniktech.maven.publish directly or via a convention plugin; declaration alone is insufficient. If absent or unverified, report it and stop before release mutations; do not install or migrate publishing plugins. Distinguish readiness review, preparation and explicit release authorization; select the matching finish path before proceeding. For recovery or recovery review, select and read the recovery answer form before analysis. For changelog-related review, also read the changelog procedure. For preparation or changelog-only work, read the preparation answer form alone in a standalone command before analysis. Check that the returned output contains the complete form, from its heading through its final sentence; if not, stop and recover that read before proceeding. Keep reviews read-only, including credentials. Follow the existing local or CI publishing mechanism; do not migrate it. Read the helper contract before configuring the bundled script. Stop before mutation on unsupported layouts or ambiguous destinations.
  2. Before preparation, read the changelog procedure completely; resolve baseline, version and coverage ambiguity. Do not guess or create a changelog.
  3. Identify repository release checks, including tests and Metalava API generation and compatibility checks where configured. Confirm that API files are current before snapshotting; the helper copies them without running Metalava. Do not treat other API dump formats as Metalava snapshots. Require passing evidence for the release code; a green parent commit is insufficient after relevant changes. For Gradle execution, use gradle-run, with --no-scan unless a scan is explicitly authorized. Fix failed checks within authorized scope; otherwise stop with the failing gate and next action.
  4. Configure and preflight the helper with explicit versions, paths, heading style, API snapshot applicability, branch, remote, tag and command arguments. Keep configuration and evidence outside tracked release files. Check the index, snapshot collisions and local/remote destinations before writes. Load ~/.env for local publication as data, never by shell sourcing or printing it. Preserve explicit process environment values. Missing required credentials block local publication; do not request or log their values. For tag-triggered CI, use existing Git authentication and CI-managed publishing secrets without loading or requiring local dotenv values.
  5. Prepare the release: update the version, finalize the changelog heading and applicable published-module API snapshots, run configured checks, and commit only release files. When finalizing a stable release entry, draft the stable summary from every surviving coverage-ledger row in final-behavior wording before grouping that cycle's original prerelease entries beneath it in a <details> block with <summary>Prerelease history</summary>. Move the original prerelease entries as one block without reordering them. Preserve their headings, anchors, dates and text, with blank lines around the enclosed Markdown. Leave older stable releases outside the block. If the renderer lacks collapsible HTML, retain expanded entries. Before handing off, compare the actual stable summary against every surviving row in the coverage ledger; confirm each appears outside prerelease history and add any missing surviving change to the stable summary. Compare the grouped history against the source to verify its original entry order. Inspect the resulting commit. Bind validation to this state and invalidate it if relevant code changes. The helper must not publish during preparation.
  6. Present the prepared release for explicit user approval before publication: release version and tag, finalized changelog (or its absence), next development version, release commit, artifact coordinates and destination, publishing mechanism, and validation results. Provide the actual notes or a directly reviewable diff, not just a claim that they are ready. Explain that this approval gate is required by this skill and wait for the user's decision; a general request to release does not approve unseen release details. Reuse approval already given for this exact prepared release. If the code, versions, notes or publishing scope change, prepare and validate the revised release and obtain approval again. Preparation-only and readiness requests stop at their requested scope without soliciting publication approval.
  7. Once the prepared release is approved and all gates pass, publish from that commit via the repository's selected mechanism. Local publication and tag-triggered CI are alternatives; do not run both. Do not publish artifacts, push a release tag or trigger publishing CI before approval.
  8. Verify all expected artifact coordinates and versions at the configured destination, along with CI completion when applicable. Verify the remote tag resolves to the prepared commit. A successful command or tag alone is not artifact evidence. Only then advance, commit, push and verify the agreed next development version. Create and read back a GitHub Release only when repository conventions call for it, using the finalized release notes.
  9. On partial or uncertain success, stop dependent mutations and report verified, failed and unknown stages without secrets. Inspect live artifact, workflow, tag and branch state before recovery; never blindly repeat publication, overwrite remote tags, delete published artifacts or claim rollback. Resume only a proven remaining action within existing authorization.

Finish paths

  • Preparation, including changelog-only: Fill the selected preparation answer form. Show actual reviewable notes or diff, remaining checks, and the explicit later publication-approval gate; do not request approval now.
  • Recovery/recovery review: Fill the selected recovery answer form; check every applicable disposition before replying.
  • Completed release: Report release version, commit/tag, validation, artifact readback, next development commit, and conditional GitHub Release URL. Claim completion only when every applicable check passes.

For a readiness review or blocker, state that narrower outcome and remaining gate. Do not expose credential contents or raw sensitive command output.

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 Release Kotlin Library AI skill do?

Use when preparing, publishing, or checking readiness for a Kotlin library release, including verifying its gradle-maven-publish-plugin prerequisite, reconciling changelogs and API snapshots, and checking publication.

Why use Release Kotlin Library on TypingMind?

Because you install it once and use it with any model. Release Kotlin Library 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 Release Kotlin Library in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/chrisbanes/skills/tree/main/skills/release-kotlin-library. 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 Release Kotlin Library?

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 Release Kotlin Library?

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

Is the Release Kotlin Library AI skill free?

Yes. It is published on GitHub by chrisbanes 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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