contribute-adapter

par nvidia

Ajouter ou modifier substantiellement un adaptateur de harnais NeMo Fabric, y compris son architecture, les revendications du descripteur, le câblage des paquets, le mappage des capacités et des politiques,…

npx skills add https://github.com/nvidia/nemo-fabric --skill contribute-adapter

Contribute a First-Party NVIDIA NeMo Fabric Adapter

Use the public nemo-fabric-build-adapter skill for adapter-contract semantics, descriptor design, configuration mapping, lifecycle behavior, and conformance evidence. This maintainer skill adds only the repository integration required for adapters shipped by NVIDIA NeMo Fabric.

Do not use this skill for a consumer that selects an existing adapter. Use the consumer nemo-fabric-integrate skill instead.

Companion Guidance

Use karpathy-guidelines to keep the change scoped, python-tests for test design, maintain-packaging for package or dependency changes, contribute-docs and review-doc-style for public text, validate-change for the validation matrix, and prepare-pr for review handoff.

Repository Integration

Follow these repository-specific requirements after applying the public skill:

  1. Place a Python adapter under adapters/python/<name>/ with LICENSE -> ../../../LICENSE, README.md, <name>.fabric-adapter.json, Python package and lock files, a source entry point, and focused tests. Place TypeScript packages under adapters/typescript/<name>/ and wire them into that npm workspace.
  2. Give each Python leaf adapter a small base installation, a harness extra for package-installable target packages, and a full extra for package-installable integrations. The Hermes adapter is the sole source-only exception and omits harness. Add a relay extra only when the adapter imports NVIDIA NeMo Relay Python APIs.
  3. Add one canonical root extra that delegates to the matching leaf adapter and its harness extra. The Hermes root extra delegates to the bare adapter because users install Hermes Agent separately from source. Keep nemo-fabric-runtime an exact-version, unconditional root dependency.
  4. Add the package to the root adapter-test dependency group, [tool.uv.sources], python_projects in justfile, applicable catalogs, and CI enumerations. Ship its descriptor under share/nemo-fabric/adapters/<name>.
  5. Update examples/code_review_agent/ and examples/harbor/calculator/ to support the new adapter.
  6. If the new adapter provides a coding harness, update examples/harbor/swebench/ to support it. Skip this step for adapters with non-coding harnesses.
  7. Regenerate lockfiles and inspect the root and leaf wheel metadata. Verify root-to-leaf delegation and every published leaf extra.

Keep descriptor claims, implementation, focused tests, public documentation, catalog entries, and packaged metadata synchronized. Start with the narrowest truthful capability set.

For usage changes, verify invocation-local accounting through the adapter contract and consumer SDK, including warm-session deltas, unknown counters, cache semantics, and unsuccessful results. Keep generated schemas and language bindings in parity; use the shared cached_input_tokens and input_tokens_include_cache fields instead of consumer-specific parsing of native output.

For instructions.system, keep config.system_instruction_modes, planning behavior, direct adapter validation, and target-native composition synchronized. New descriptors must declare their exact replace and append support rather than relying on the legacy omitted-value behavior.

Repository Evidence

In addition to the evidence required by the public skill, include:

  • A subprocess test of the packaged entry point.
  • Exact descriptor assertions for every claimed capability.
  • A credential-free fixture that exercises plan, doctor, and run.
  • Wheel inspection when package data, dependencies, or extras change.
  • Deterministic CI coverage; keep credentialed live-target tests opt-in.

Validation

Use validate-change to select the complete matrix. The common adapter checks are:

uv sync --group adapter-tests
uv run --no-sync pytest tests/adapters/test_<name>*.py
just test-python
just lock-python && just wheels
just schemas
cargo fmt --all -- --check && just test-rust
just docs
uv run pre-commit run --all-files --show-diff-on-failure
git diff --check

References

  • Public contract: docs/adapter-contract/ and schemas/adapter-contract/.
  • Descriptor schema: schemas/adapter-contract/adapter-descriptor.schema.json.
  • Repository packaging: root pyproject.toml, justfile, adapter catalogs, and CI workflows.
  • Shared first-party Python host patterns: adapters/python/common/ and the closest adapter with the same target boundary.

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…