nemo-relay-instrument-calls

por nvidia

Wrap application tool calls and LLM/provider calls with NeMo Relay scopes and managed execution APIs

npx skills add https://github.com/nvidia/nemo-relay --skill nemo-relay-instrument-calls

Instrument Tool And LLM Calls

Use this skill when an app already has tool functions or model/provider calls and needs to run them through NeMo Relay correctly.

Default Guidance

  • Put a scope around the natural agent, request, workflow, or graph boundary.
  • Use managed execution APIs first:
    • Rust: tool_call_execute(ToolCallExecuteParams::builder()...), llm_call_execute(LlmCallExecuteParams::builder()...)
    • Python: tools.execute(...), llm.execute(...)
    • Node.js: toolCallExecute(...), llmCallExecute(...)
    • Go: tools.Execute(...), llm.Execute(...) or the top-level wrappers
  • Use manual lifecycle APIs only when the host framework cannot be wrapped by the managed execute helpers.

Embedded Runtime Semantics

  • Managed tool and LLM execution runs conditional-execution guardrails first on the raw input. If rejected, the runtime emits a standalone mark event and does not run request intercepts or the callable.
  • Request intercepts run after conditional guardrails and rewrite the real input that reaches execution intercepts and the callback.
  • Sanitize-request guardrails affect emitted start-event payloads only. They do not rewrite the caller-visible request or arguments.
  • Execution intercepts wrap the callback with the middleware next pattern and may short-circuit by returning their own result.
  • Sanitize-response guardrails affect emitted end-event payloads only. The value returned to application code remains the raw callback or execution-intercept result.
  • If execution fails after the start event has been emitted, the runtime still emits an end event without a semantic output payload.
  • Tool calls are named operations with JSON-compatible arguments and results. Keep the original tool callable responsible for business logic; let NeMo Relay own lifecycle events, middleware, and metadata.
  • LLM calls use an LLMRequest made of metadata plus content. Pass model names and stable call identifiers when they matter for trace export or diagnostics.
  • Manual lifecycle APIs are for framework adapters that already own execution. If you use them, every start call needs a matching end or error path with the relevant semantic payloads supplied explicitly.
  • Partial middleware APIs such as request_intercepts(...) and conditional_execution(...) are for advanced adapters that need one middleware family before calling a provider manually.
  • Streaming LLM wrappers collect chunks and finalize a response at stream end; dropping the stream early can prevent finalizers and subscribers from seeing a complete output.

Checklist

  • Scope boundary chosen before the first tool or LLM call
  • Existing tool function wrapped without losing its original arguments/result
  • Existing LLM/provider call wrapped at the right abstraction layer
  • Optional metadata, attributes, or model name attached where useful
  • Context propagation handled if the call hops threads or async tasks

Use Another Skill When

  • You need traces, ATIF, or export setup -> nemo-relay-setup-observability
  • You are debugging missing events or load failures -> nemo-relay-debug-runtime-integration
  • You need per-request isolation or worker-pool advice -> nemo-relay-use-context-isolation
  • You need reusable config-activated runtime behavior -> nemo-relay-build-plugin

Related Skills

  • nemo-relay-start
  • nemo-relay-typed-wrappers-codecs
  • nemo-relay-setup-observability
  • nemo-relay-build-plugin

Más skills de nvidia

compileiq-debug
nvidia
Úsalo cuando algo esté mal: Search() se cuelga, todas las evaluaciones devuelven INVALID_SCORE, las puntuaciones no mejoran, cada configuración devuelve el mismo número, errores de ptxas…
official
create-github-pr
nvidia
Crear solicitudes de extracción de GitHub usando la CLI gh. Usar cuando el usuario quiera crear un nuevo PR, enviar código para revisión o abrir una solicitud de extracción. Palabras clave de activación -…
official
diagnose-perf
nvidia
Triaje de rendimiento para respondedores iniciales en Isaac Sim e Isaac Lab. Identifica la categoría del cuello de botella (limitado por GPU, limitado por CPU, VRAM, carga) usando nvidia-smi y…
official
eagle3-review-logs
nvidia
Revisa los registros de experimentos del pipeline EAGLE3 desde el directorio experiments/ del lanzador. Resume el estado de aprobación/fallo para las 4 tareas, diagnostica fallos con la causa raíz…
official
nemoclaw-maintainer-cross-issue-sweep
nvidia
Scans other open issues to find ones a given PR may also fix or accidentally break. Outputs adjacent-fix opportunities and contradiction risks with file:line…
official
karpathy-guidelines
nvidia
Pautas de comportamiento para reducir errores comunes de codificación en LLM. Úselas al escribir, revisar o refactorizar código para evitar la sobrecomplicación, realizar cambios quirúrgicos,…
official
fhir-basics
nvidia
Enseña a los agentes cómo funcionan las APIs de FHIR R4, qué recursos están disponibles, cómo consultarlos con parámetros de búsqueda y cómo analizar correctamente todos los formatos de respuesta…
official
underdeclared-agent
nvidia
A helpful assistant agent
official