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vss-deploy-dense-captioning

Use this skill when deploying standalone RT-VLM dense captioning or calling its REST API (uploads, captions, streams, chat-completions, Kafka). Not for VSS profile deploy or video-search ingestion.

76

Quality

96%

Does it follow best practices?

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SecuritybySnyk

Medium

Suggest reviewing before use

SKILL.md
Quality
Evals
Security

Quality

Content

100%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A dense, actionable skill body with executable workflows, explicit validation checkpoints, and clean one-level-deep reference separation. It respects Claude's intelligence and routes complex detail to verified bundle files.

DimensionReasoningScore

Conciseness

The body is lean and assumes Claude's competence — no padding about what Docker, Kafka, SSE, or VLMs are — and every code block earns its place; only a couple of minor near-duplications (OpenAPI source-of-truth, alias clarification) could be trimmed, fitting the score-5 anchor best.

5 / 5

Actionability

It provides copy-paste-ready curl/bash with real endpoints, exact model-id retrieval via jq, env-var guards such as '${API_KEY:?}', and concrete RTSP validation, matching the score-5 anchor for fully executable guidance covering common cases.

5 / 5

Workflow Clarity

The standalone deployment flow is explicitly numbered with a 'Never skip the dry-run' checkpoint, preflights before pull, a smoke test after ready, and troubleshooting feedback loops (401 -> docker login retry; OOM -> switch variant / compose down); validation is present for this infra operation, matching the score-5 anchor.

5 / 5

Progressive Disclosure

SKILL.md acts as a clear overview with one-level-deep, well-signaled markdown links to real files (deploy-rt-vlm-service.md, api-surface-26.05.md, kafka-workflows.md), plus an upfront routing decision, matching the score-5 anchor.

5 / 5

Total

20

/

20

Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A precise, well-scoped description that states both capabilities and trigger conditions while explicitly disambiguating from sibling VSS skills. Minor room for additional natural synonyms, but otherwise strong.

DimensionReasoningScore

Specificity

The description names the domain and enumerates multiple concrete actions — 'deploying standalone RT-VLM dense captioning' and 'uploads, captions, streams, chat-completions, Kafka' — giving comprehensive coverage, matching the score-5 anchor.

5 / 5

Completeness

It explicitly answers both what ('deploying standalone RT-VLM dense captioning or calling its REST API...') and when ('Use this skill when...') with concrete trigger phrases, matching the score-5 anchor.

5 / 5

Trigger Term Quality

Natural user terms are well covered ('deploying', 'dense captioning', 'REST API', 'uploads', 'captions', 'streams', 'chat-completions', 'Kafka'), but a few common variations a user might say (e.g. 'vision-language model', 'VLM') are missing, fitting the score-4 anchor better than 5.

4 / 5

Distinctiveness Conflict Risk

The explicit exclusion clause ('Not for VSS profile deploy or video-search ingestion') carves a clear niche with distinct triggers and minimal conflict risk with sibling deploy skills, matching the score-5 anchor.

5 / 5

Total

19

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

relative_links

Relative link issues: 1 suspicious

Warning

Total

15

/

16

Passed

Repository
NVIDIA/skills
Reviewed

Table of Contents

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