add-binding-feature

par nvidia

Ajouter ou modifier une surface d'API publique NeMo Relay à travers le runtime central et chaque binding affecté

npx skills add https://github.com/nvidia/nemo-relay --skill add-binding-feature

Add a Binding Feature

Use this skill when a change affects the public runtime surface and must stay in parity across the Rust core, FFI, and one or more bindings.

Do not use this skill for:

  • Internal-only core refactors with no public API change
  • New middleware contracts, which use the middleware-specific workflow
  • Binding-local bug fixes that do not change shared behavior
  • Docs-only or example-only updates

Implementation Order

  1. Core Rust Implement the behavior first in crates/core/src/api/ and related core modules such as crates/core/src/api/runtime/, crates/core/src/codec/, or crates/core/src/json.rs.
  2. FFI / shared C surface, when affected Update crates/ffi and its generated header only when the capability is exposed through the C ABI or Go binding.
  3. Language-native bindings Update each binding that exposes the capability; leave unrelated bindings unchanged.
  4. Language wrapper helpers Update Python wrapper modules, Go shorthand packages, typed helpers, or adaptive/plugin helpers if the new behavior belongs there.
  5. Docs and examples Update reference docs, language-binding docs, and examples when the public surface or expected usage changed.
  6. Validation Follow the repository validation policy for the surfaces whose public or observable behavior changed.

Naming Conventions

LayerConventionExample
Rustsnake_casenemo_relay_tool_call
C FFInemo_relay_ prefixnemo_relay_tool_call
Pythonsnake_casenemo_relay.tools.call
GoPascalCasenemo_relay.ToolCall
Node.jscamelCasetoolCall

Parity Checklist

  • Core function with doc comment in crates/core/src/api/
  • Runtime callback/state, codec, JSON, or event/tool/LLM/scope types added in the relevant core module if needed
  • FFI wrapper and generated header updated if the C ABI changes
  • Python native binding, wrapper, docstring, and stubs updated if exposed
  • Go wrapper and shorthand package updated if the experimental Go surface exposes the capability
  • Node.js native binding and wrapper updated if exposed
  • Typed wrapper or adaptive/plugin helper surfaces updated when applicable
  • Meaningful tests added in every affected language surface
  • SPDX license header on any new files
  • Relevant pages under docs/reference/ updated
  • README.md, docs/getting-started/, or binding-level READMEs updated if behavior differs by language
  • Relevant getting-started, README, or example docs updated if usage changed

Decision Points

Lock these before implementing:

  • Which bindings actually expose the new surface?
  • Is the change part of the plain JSON API, typed wrappers, adaptive/plugin helpers, or observability helpers?
  • Does the new API need manual lifecycle and managed execute variants, or only one of them?
  • Does the new behavior change event fields, metadata, or scope expectations?
  • If tool execution is affected, does every callback, continuation, managed return, and manual end surface use the canonical ToolExecutionResult contract and preserve its opaque annotation?
  • Are docs/examples required because the intended usage changed?

Key References

  • Architecture: docs/about-nemo-relay/architecture.mdx
  • Reference index: docs/reference/api/index.mdx
  • Getting started and binding status: README.md, docs/getting-started/quick-start/index.mdx, docs/reference/support-matrix.mdx
  • Typed wrappers and codecs: docs/integrate-into-frameworks/using-codecs.mdx, docs/integrate-into-frameworks/provider-codecs.mdx
  • Adaptive config/plugins: docs/configure-plugins/about.mdx, docs/build-plugins/about.mdx, docs/configure-plugins/adaptive/configuration.mdx
  • Existing pattern: follow a surface already implemented across core, FFI, Python, Go, and Node.js rather than inventing a new shape

Plus de skills de nvidia

fhir-basics
nvidia
Apprend aux agents comment fonctionnent les API FHIR R4, quelles ressources sont disponibles, comment les interroger avec des paramètres de recherche, et comment analyser correctement tous les formats de réponse…
compileiq-validate-result
nvidia
Utiliser APRÈS qu'une recherche soit terminée et AVANT de réclamer un accélérateur ou d'expédier un ACF. Charge le CSV dump_results, extrait les K meilleurs candidats (mono-objectif)…
changelog-audit
nvidia
Auditer le CHANGELOG.md de Warp avant une publication : récupérer les entrées perdues, trier par impact utilisateur, affiner le langage des entrées, ajuster les retours à la ligne et (en mode branche de publication) mettre à jour la comparaison…
dgx-diagnose
nvidia
Diagnostiquer les problèmes courants du DGX Station GB300 — plantages CUDA, ciblage incorrect du GPU, bugs de conteneur vLLM/SGLang, problèmes d'état MIG, erreurs NVLink/Fabric Manager,…
aicr-managing-openvex
nvidia
Use when adding, updating, or removing CVE/GHSA suppressions in `.openvex.json` — the OpenVEX document consumed by the daily image vulnerability scan workflow.…
aicr-creating-slide-decks
nvidia
À utiliser lors de la création d'un diaporama HTML autonome ou d'un support visuel pour un concept technique ou un flux de travail (par exemple un demos/*.html) — affiché en plein écran ou…
aicr-creating-guided-demos
nvidia
Génère un script de démonstration guidée interactive (demos/*.sh), en direct ou à son rythme, avec le modèle Frame → Tell → Show → Close. Se déclenche sur « script de démonstration », « guidé…
aicr-analyzing-snapshots
nvidia
À utiliser lors de l'analyse d'un fichier YAML de snapshot AICR, de l'examen de l'état du cluster, de la comparaison des caractéristiques des fournisseurs, de l'extraction d'informations sur la topologie GPU/réseau, ou…