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Construct RTVI VSS CV Service · nvidia | DecimalAI

ai mlby nvidia

Construct RTVI VSS CV Service

nvidia/rtvi-cv-scaffold-vss-service

Source nvidia/skills ↗License Apache-2.0

Scaffold a standalone RTVI CV microservice that plugs into VSS Search and Alerts profiles via Kafka mdx-raw. The shipped scaffold script is a YOLO26 reference implementation (ONNX, labels, custom parser required).

SkillScore86Maintained

Automatic

AI Engineer pack

Last verified 9/8/2026

What it changes

Passed 17 of 20 test cases with the skill, and 5 of 20 without it.

Without skill23%

With skill86%

Checks it passed that the model alone missed

Specifies msg-conv-payload-type equal to 2.
Specifies msg-conv-msg2p-new-api equal to 1.
Designates mdx-raw as the target Kafka topic.

and 19 more in the full report

14 fixed5 passed either way3 still failing0 broke

Pass-rate lift: +64 pp
Tokens: +120%
Agent turns: 0%
Response time: -18%

Model gemini-3.6-flashMeasured 9/8/2026v119 of 22 cases passed with skill · 20 comparable

Tokens, turns and time describe resource use, not a dollar price.

Use this skill

Save it into your project's skills folder. Claude Code picks it up in its next session.

curl -fsSL --create-dirs -o .claude/skills/nvidia-rtvi-cv-scaffold-vss-service/SKILL.md https://app.decimal.ai/s/nvidia-rtvi-cv-scaffold-vss-service/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add nvidia-rtvi-cv-scaffold-vss-service, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"

1 · One-time — install the CLI (docs ↗)

pip install "decimalai>=0.15"

2 · Get the skill — writes .agents/skills/nvidia-rtvi-cv-scaffold-vss-service/ and pins it in .decimal/skills.lock

decimalai skills add nvidia-rtvi-cv-scaffold-vss-service

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/nvidia-rtvi-cv-scaffold-vss-service/SKILL.md https://app.decimal.ai/s/nvidia-rtvi-cv-scaffold-vss-service/SKILL.md

Raw file: /s/nvidia-rtvi-cv-scaffold-vss-service/SKILL.md ↗ · machine-readable summary at /s/nvidia-rtvi-cv-scaffold-vss-service.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 12 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 12

Prompt

In the nvinfer configuration file pgie-yolo26-config.txt for YOLO26 primary inference, what custom bounding box parsing function name must be specified?

What was checked, without and with the skill
Checked	Without skill	With skill
Sets the custom parse function name to NvDsInferParseYolo26.	Missed	Passed

case-17 · gemini-3.6-flash · 9/8/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md301 lines5 filesincludes scripts

Construct RTVI VSS CV Service

Scaffolds a deployable custom perception microservice that:

runs a DeepStream pipeline with YOLO26 primary inference + tracker,
converts detection metadata to the VSS protobuf schema and publishes it to the mdx-raw Kafka topic, and
drops into the existing VSS compose stack via the bp_developer_search_2d and bp_developer_alerts_2d_cv profile flags so the downstream Search Workflow, Alert Verification, and Behavior Analytics services consume it without further changes.

The scaffolded output is a runnable repo, not a design document.

Scope boundaries

This skill name describes the service type (a VSS-bound RTVI CV microservice), not a model family. What is generic vs YOLO26-specific:

Layer	Scope
VSS integration	Generic — compose profiles, host networking, `mdx-raw`, protobuf-2 payload, tests, smoketest
Scaffold script output	YOLO26 reference — `pgie-yolo26-config.txt`, `YOLO26_*` mount paths, `NvDsInferParseYolo26`
Other ONNX detectors	Adapt the scaffold manually, or use `rtvi-cv-customize-model` to swap the model inside the stock `vss-rt-cv` perception container
Segmentation frame masks	Documented in `integration-contract.md`; not auto-generated by the scaffold — extend msgconv/wrapper after scaffolding

Do not treat the scaffold as a model-agnostic generator. Agents should either run the YOLO26 scaffold as-is or consciously edit pgie/compose paths for another detector while keeping the VSS contract fixed.

When to use

Use this skill when the user wants to:

replace VSS's default perception service (RT-DETR / GDINO / YOLOv11) with a custom YOLO26-based detector,
add new object classes or domain-specific tracking logic while keeping the VSS Search / Alerts / Behavior Analytics workflows intact,
ship a perception microservice on a customer's hardware that integrates with a VSS deployment they manage.

Track record

Benchmark

17 / 20

test cases passed, vs 5 / 20 without

Adoption

Users: 0
Times used: 0

Safety and source details

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v5 — 8/17/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

nvidia / skills

skills/rtvi-cv-scaffold-vss-service/SKILL.md

View on GitHub ↗

License NVIDIA ProprietaryImported 8/17/2026Version v1Bundled 4 files · scripts

More skills from the same source and nearby in the registry, with their headline benchmark lift.

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See it in action

What's inside

Construct RTVI VSS CV Service

Scope boundaries

When to use

Track record

Benchmark

Adoption

SkillSafety

Source

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