Inject In Sling Model

Organization

adobe

inject-in-sling-model

AEM Cloud Service expert skill — migrate javax.inject.@Inject fields in Sling Model (@Model) classes to injector-specific annotations (@ValueMapValue / @OSGiService / @SlingObject). Self-discoverable (scan for @Model classes with field-level @Inject); the replacement is chosen deterministically from each field's declared type. Use for "fix @Inject in HeroModel.java", "modernize my Sling Models", or when scanning an AEM project for @Inject misuse. Detailed decision table, companion-annotation handling, import management, and file-level skip policy are in recipe.md.

Overview

Publisher	adobe
Repository	`skills`
Skill name	`inject-in-sling-model`
Stars	298
Forks	92
Bundled files	1
License	Apache-2.0
Links	Skill source Repository Homepage

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 adobe on GitHub. Read the source before you install it.

Installation

Install the Inject In Sling Model 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/adobe/skills/tree/main/plugins/aem/cloud-service/skills/code-assessment/inject-in-sling-model
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/adobe/skills/tree/main/plugins/aem/cloud-service/skills/code-assessment/inject-in-sling-model

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/adobe/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/plugins/aem/cloud-service/skills/code-assessment/inject-in-sling-model .claude/skills/inject-in-sling-model

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

Use it in TypingMind

Enable Inject In Sling Model 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 Inject In Sling Model 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 Inject In Sling Model 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.

@Inject in Sling Models — AEM as a Cloud Service

This pattern is executed by the code-assessment runbook — follow ../references/runbook.md for the full flow (preflight → plan → apply → verify, run log). This skill supplies the detection + recipe the runbook applies.

Overview

javax.inject.@Inject on fields of @Model classes is discouraged by the Apache Sling Models documentation. Removing @Inject without a replacement breaks injection, so each field is migrated to an injector-specific annotation chosen from its declared type.

Classification — confirm this pattern applies

A *.java file whose class is annotated @Model, with at least one field annotated @Inject.
Constructor-parameter and setter-method @Inject are out of scope (trigger the file-level skip).

Discovery

Detection is performed by the analyzer (../scripts/analyze.sh), run by the runbook:

bash
bash ../scripts/analyze.sh <workspace-root> --pattern inject-in-sling-model

Match criteria (what the detector flags): a class annotated @Model (org.apache.sling.models.annotations.Model, confirmed import-aware) with at least one field annotated @Inject (javax.inject.Inject or jakarta.inject.Inject). One finding per matching field. Constructor/setter @Inject and non-@Model classes are not flagged. The replacement annotation is chosen from the field's declared type by the decision table in recipe.md.

Resolution contract

self-evident — the replacement annotation is fully determined by the field's declared Java type via the decision table in recipe.md. No external input is required.

Review checklist

Each migrated field maps to exactly one injector-specific annotation per the decision table
Sling objects (Resource / ResourceResolver / request / response) → @SlingObject, not @Self
@Named merged into the new annotation's name; @Default / @Via preserved
@Optional → per-field injectionStrategy = InjectionStrategy.OPTIONAL (never a class-level defaultInjectionStrategy change)
Unused imports removed; new imports added and ordered per the file's convention
File-level skip respected — no partial migration of a file with any ambiguous field

Recipe

Read recipe.md in full before editing: input contract, decision table, companion annotations, import management, unlocatable / skip-file policy, per-file procedure, before/after example, editing strategy.

Handoff

The skill never commits. See ../references/git-workflow.md for git vs in-place handoff and the suggested commit message.

Bundled files

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

recipe.md12 KB

Frequently asked questions

What does the Inject In Sling Model AI skill do?

Why use Inject In Sling Model on TypingMind?

Because you install it once and use it with any model. Inject In Sling Model 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 Inject In Sling Model in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/adobe/skills/tree/main/plugins/aem/cloud-service/skills/code-assessment/inject-in-sling-model. 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 Inject In Sling Model?

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 Inject In Sling Model?

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

Is the Inject In Sling Model AI skill free?

Yes. It is published on GitHub by adobe 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

@Inject in Sling Models — AEM as a Cloud Service

Overview

Classification — confirm this pattern applies

Discovery

Resolution contract

Review checklist

Recipe

Handoff

Bundled files

Frequently asked questions

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