feat(skills): expose additional tools after skill activation

[wangjl1993]

Aligns Kotlin SkillToolset with adk-python's "load_skill activates additional tools" behavior.

Skills can declare additional tool names in frontmatter via metadata.adk_additional_tools. These tools remain hidden from the LLM until the model calls load_skill for that skill.
Activation state is recorded per-agent under _adk_activated_skill_{agent} and re-read on each LLM step, so subsequent requests expose the expanded toolset.

This also:

• Preserves metadata.adk_additional_tools in loaded/listed frontmatter responses.
• Validates metadata.adk_additional_tools as a list of non-blank strings.
• Supports resolving activated tools from both provided tools and provided toolsets.
• Adds parser and toolset tests for the activation flow.

Validation:

• ./gradlew -Pkotlin.daemon.jvmargs="-Xmx4g" --no-daemon --stacktrace build

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[damianmomotgoogle]

Thx for contribution! We need a bit of time to verify how it will co-work with just introduced context compaction.

In the mean time can you sync it to HEAD revision? Thx!

[wangjl1993]

Thx for contribution! We need a bit of time to verify how it will co-work with just introduced context compaction.

In the mean time can you sync it to HEAD revision? Thx!

Synced the PR to latest main HEAD and verified with full build:

GRADLE_OPTS="-Xmx4g -XX:MaxMetaspaceSize=1g -Dorg.gradle.daemon=false" JAVA_HOME=/usr/lib/jvm/java-21-openjdk-amd64 ./gradlew -Pkotlin.daemon.jvmargs="-Xmx4g"
--no-daemon --stacktrace build

BUILD SUCCESSFUL in 2m 18s

The skill activation state is stored in session state and re-read when toolsets build tools for each LLM step, so it should survive context compaction.