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Magnus HedemarkandGitHub
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* feat(skill): add spring ai diagnostics * fix(spring-ai): harden project compatibility diagnostics * Register Spring AI skill and normalize metadata * fix(spring-ai): scope Maven versions to dependency elements * fix(spring-ai): validate the shipped diagnostic fixture * docs(spring-ai): state the limits of static diagnostics * docs(spring-ai): clarify warning exit semantics * test(spring-ai): load the sibling diagnostic module explicitly * fix(spring-ai): ignore Java block comments in diagnostics * fix(spring-ai): preserve Java text block contents
spring-ai — Diagnose Spring AI projects before they surprise you
Why Install This Skill
Spring AI projects combine fast-moving framework APIs with model providers, retrieval stores, memory, tools, and streaming. A project can compile while leaking conversation context, logging prompts, executing an unauthorized tool, or treating partial output as complete.
This skill gives your agent a read-only diagnostic workflow for actual Maven and Gradle projects. It reports build versions, configuration hazards, source-level integration clues, and actionable findings as machine-readable JSON so you can retain evidence with a commit or incident record.
What You Get
| Path | Purpose |
|---|---|
SKILL.md |
Version posture, workflow, boundaries, and recovery expectations. |
scripts/spring_ai_check.py |
Stdlib-only Maven/Gradle/config/source diagnostic CLI. |
scripts/test_spring_ai_check.py |
Offline tests for parsing, findings, JSON, and error behavior. |
references/compatibility-and-setup.md |
Current setup checks and version-sensitive API notes. |
references/integration-boundaries.md |
ChatClient, memory, retrieval, tools/MCP, streaming, and observability checks. |
references/source-index.md |
Official Spring AI and Spring Boot URLs with verification date. |
examples/minimal-project/ |
Static diagnostic fixture used by the tests; not a runnable application. |
evals/evals.json |
Seven schema-v1 output-quality cases. |
Quick Start
No API key is required for diagnostics:
python3 spring-ai/scripts/spring_ai_check.py --root ./my-spring-app --json
Use --strict in CI when warnings should fail the check. The tool never contacts a model provider.
Triggers
- Diagnose Spring AI Maven or Gradle compatibility and configuration.
- Inspect ChatClient/advisor, retrieval, memory, tool/MCP, streaming, or observability integration.
- Prepare a local Spring AI smoke-test or troubleshoot a failed integration.
Requirements
- Python 3.8+ standard library.
- A Maven or Gradle project directory for useful results.
- Maven/Gradle and provider credentials only when running the project’s own tests; the diagnostic CLI does not need them.
- Re-check official documentation for upgrades; supported documentation posture is Spring AI 2.0.1 current stable and 1.0.9 maintenance reference as verified 2026-09-14.