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aiq-deploy

Use when asked to install, deploy, run, validate, troubleshoot, or stop NVIDIA AI-Q Blueprint infrastructure.

67

Quality

81%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

The canonical home for this skill is aiq-deploy in NVIDIA/skills

SKILL.md
Quality
Evals
Security

Quality

Content

71%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 well-structured operational skill with executable commands, a clear validated workflow, and excellent progressive disclosure through one-level-deep references. Its main weakness is redundancy — the reference routing table and closing References table duplicate the same paths, and some troubleshooting guidance is restated inline.

Suggestions

Consolidate the Step 4 routing table and the closing References table into a single reference index to remove the duplicated 13-row listing.

Tighten the Common Issues section to point to references/troubleshooting.md instead of restating its diagnostic guidance inline.

Where the workflow says "read references/X.md" as a checkpoint, add a one-line inline validation command so the checkpoint is explicit rather than deferred.

DimensionReasoningScore

Conciseness

The body is mostly task-focused but repeats the same 13 reference paths in both the Step 4 routing table and the closing References table, and re-states troubleshooting guidance already delegated to references, adding padding that could be tightened.

3 / 5

Actionability

Concrete, executable commands with stated expected outputs appear throughout (git check-ignore, test -f, curl health, docker compose, lsof), with minor gaps where paths like Helm/FRAG defer to reference files.

4 / 5

Workflow Clarity

A clear 9-step sequence with validation checkpoints and feedback loops (health check → troubleshooting → diagnose before claiming ready) is present, but several checkpoints defer to "read references/X.md" rather than stating explicit inline validation.

4 / 5

Progressive Disclosure

The body is an overview pointing to 13 one-level-deep reference files, all verified to exist, clearly signaled via routing and reference tables, making navigation easy.

5 / 5

Total

16

/

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 tight, third-person description with an explicit "Use when" trigger and a concrete list of operational actions tied to a specific product niche. The only weakness is slightly limited synonym/variant coverage in trigger terms.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions — "install, deploy, run, validate, troubleshoot, or stop" — against a named domain (NVIDIA AI-Q Blueprint infrastructure), matching the comprehensive-coverage anchor.

5 / 5

Completeness

It explicitly answers what (install/deploy/run/validate/troubleshoot/stop NVIDIA AI-Q Blueprint infrastructure) and when ("Use when asked to...") with concrete trigger phrases.

5 / 5

Trigger Term Quality

Natural action verbs a user would say (install, deploy, run, validate, troubleshoot, stop) plus the product name give good keyword coverage, but synonyms and product-name variants (e.g., "AIQ") are absent.

4 / 5

Distinctiveness Conflict Risk

The named NVIDIA AI-Q Blueprint niche with product-specific triggers gives a clear niche with minimal conflict risk against other skills.

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

metadata_field

'metadata' should map string keys to string values

Warning

Total

15

/

16

Passed

Repository
openai/plugins
Reviewed

Table of Contents

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