Write Java code using native dev.axllm:ax entrypoints for Ax packages.
npx skills add https://github.com/ax-llm/ax --skill ax-java-llm
Please help me install this Agent Skill. Skill: ax-java-llm Source: https://github.com/ax-llm/ax/tree/main/website/static/java/.well-known/agent-skills/ax-java-llm Command: npx skills add https://github.com/ax-llm/ax --skill ax-java-llm
This Skill helps you write Java code against the generated Ax package without accidentally using TypeScript-only APIs or mismatched call patterns.
dev.axllm:ax entrypoints for signatures, providers, agents, flows, and optimizers.Ask for a Java implementation that uses the generated Ax package and follows the package examples for the specific feature you want.
High-intent search queries and answers about installing and using this skill.
To write Java code for the Ax LLM framework natively, use the `dev.axllm:ax` package entrypoints for signatures, providers, agents, flows, and optimizers instead of TypeScript APIs. This ensures correct call patterns and deterministic code generation.
The correct Java package entrypoint for building Ax agents and flows is `dev.axllm:ax`. It provides the native Java syntax required for implementing signatures, providers, and optimizers without relying on TypeScript-only APIs.
Yes, you can use Ax optimizers and providers in a Java LLM application by leveraging the native `dev.axllm:ax` package. This allows you to translate Ax concepts into Java syntax and choose the right provider setup for network or no-key scenarios.
You translate Ax concepts into Java syntax by following the package API docs, capability manifest, and runnable examples as the source of truth. This approach guides the implementation of signatures, agents, and flows using the `dev.axllm:ax` entrypoints.
Your Ax Java implementation fails when it accidentally uses TypeScript-only APIs or mismatched call patterns. To fix this, align your code with the native package docs, AxIR manifests, and the correct Java entrypoints for deterministic provider mapping.
Yes, you need AxIR manifests and native package docs to generate deterministic Ax Java code. These resources act as the source of truth for mapping providers correctly and ensuring your Java implementation follows the expected API structure.
ax-llmGenerate Java provider clients and normalized model connection code for Ax AI integrations.
ax-llmWrite Go code for the generated Ax package using native entrypoints and runtime profiles.
ax-llmGenerate Python code for the axllm package using native signatures and entrypoints.
ax-llmBuild Go agents using the generated Ax package API.