docs(agents): capture vllm backend lessons + runtime lib packaging

[mudler]

New .agents/vllm-backend.md with everything that's easy to get wrong on the vllm/vllm-omni backends:

• Use vLLM's native ToolParserManager / ReasoningParserManager — do not write regex-based parsers. Selection is explicit via Options[], defaults live in core/config/parser_defaults.json.
• Concrete parsers don't always accept the tools= kwarg the abstract base declares; try/except TypeError is mandatory.
• ChatDelta.tool_calls is the contract — Reply.message text alone won't surface tool calls in /v1/chat/completions.
• vllm version pin trap: 0.14.1+cpu pairs with torch 2.9.1+cpu. Newer wheels declare torch==2.10.0+cpu which only exists on the PyTorch test channel and pulls an incompatible torchvision.
• SIMD baseline: prebuilt wheel needs AVX-512 VNNI/BF16. SIGILL symptom + FROM_SOURCE=true escape hatch are documented.
• libnuma.so.1 + libgomp.so.1 must be bundled because vllm._C silently fails to register torch ops if they're missing.
• backend_hooks system: hooks_llamacpp / hooks_vllm split + the '*' / '' / named-backend keys.
• ToProto() must serialize ToolCallID and Reasoning — easy to miss when adding fields to schema.Message.

Also extended .agents/adding-backends.md with a generic 'Bundling runtime shared libraries' section: Dockerfile.python is FROM scratch, package.sh is the mechanism, libbackend.sh adds ${EDIR}/lib to LD_LIBRARY_PATH, and how to verify packaging without trusting the host (extract image, boot in fresh ubuntu container).

Index in AGENTS.md updated.

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