contribute-adapter

tarafından nvidia

NeMo Fabric harness adaptörünü ekleyin veya önemli ölçüde değiştirin; mimarisi, tanımlayıcı iddiaları, paket bağlantısı, yetenek ve politika eşlemesi dahil,…

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.

nvidia tarafından daha fazla skill

fhir-basics
nvidia
Ajanlara FHIR R4 API'lerinin nasıl çalıştığını, hangi kaynakların mevcut olduğunu, arama parametreleriyle nasıl sorgulanacağını ve tüm yanıt formatlarının nasıl doğru şekilde ayrıştırılacağını öğretir…
compileiq-validate-result
nvidia
Bir arama tamamlandıktan SONRA ve herhangi bir hızlandırma talep etmeden veya bir ACF göndermeden ÖNCE kullanın. dump_results CSV dosyasını yükler, en iyi K adayı (tek amaçlı) çıkarır…
changelog-audit
nvidia
Bir sürüm öncesinde Warp CHANGELOG.md dosyasını denetle: kayıp girdileri kurtar, kullanıcı etkisine göre sırala, girdi dilini iyileştir, satır kaydırma yap ve (sürüm dalı modunda) karşılaştırmayı artır…
dgx-diagnose
nvidia
Yaygın DGX Station GB300 sorunlarını teşhis edin — CUDA çökmeleri, yanlış GPU hedefleme, vLLM/SGLang konteyner hataları, MIG durumu sorunları, NVLink/Fabric Manager hataları,…
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
Teknik bir kavram veya iş akışı için kendi kendine yeten bir HTML slayt sunumu veya görsel konuşma noktası oluştururken kullanın (ör. demos/*.html) — tam ekran gösterilir veya…
aicr-creating-guided-demos
nvidia
Etkileşimli rehberli demo scripti (demos/*.sh) hazırlar, canlı veya kendi hızında, Frame → Tell → Show → Close deseniyle. "demo script", "guided…" üzerine tetiklenir.
aicr-analyzing-snapshots
nvidia
AICR snapshot YAML dosyasını analiz ederken, küme durumunu incelerken, sağlayıcı özelliklerini karşılaştırırken, GPU/ağ topolojisi içgörüleri çıkarırken veya… kullanın.