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aiq-deploy

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

74

Quality

92%

Does it follow best practices?

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Adds up to 20 points to the overall score

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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

85%

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

A well-structured, highly actionable multi-mode deployment skill with clear sequencing, validation checkpoints, and excellent progressive disclosure into real one-level-deep references. Its main weakness is conciseness: a duplicated reference table and an over-explained version-compatibility section add tokens that do not earn their place.

Suggestions

Collapse the Step 4 routing table and the final References table into a single source of truth to remove the duplicated reference listing.

Tighten the Version Compatibility section: keep the compatibility rule and one compatible + one incompatible example instead of five worked examples.

Trim the Prerequisites list by moving per-runtime toolchain details (kubectl/Helm/Node version pins) into the corresponding reference files, keeping only the runtime-selection summary inline.

DimensionReasoningScore

Conciseness

Largely efficient and free of basic-concept padding, but carries redundancy (the Step 4 routing table and the final References table overlap heavily) and a verbose semver-compatibility section with five worked examples that could be trimmed, matching 'mostly efficient but could be tightened' rather than fully lean.

2 / 3

Actionability

Provides copy-paste-ready bash throughout (git check-ignore, test -f, cp, curl, docker compose, lsof) with explicit expected outputs per block, matching the 'fully executable code/commands; copy-paste ready' anchor.

3 / 3

Workflow Clarity

A numbered 9-step sequence with explicit validation checkpoints (gitignore check before writing secrets, /health before handoff) and a validate->diagnose->retry feedback loop, satisfying the 'clear sequence with explicit validation steps' anchor; destructive cleanup is gated on user approval.

3 / 3

Progressive Disclosure

SKILL.md is an overview that routes to 13 real one-level-deep reference files via well-signaled tables, with content appropriately split by deployment mode (compose, helm, CLI, web, skill backend) and concern (validation, troubleshooting, shutdown), matching the 'clear overview with well-signaled one-level-deep references' anchor.

3 / 3

Total

11

/

12

Passed

Description

100%

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 concise, third-person description that pairs six concrete operational verbs with an explicit 'Use when asked to' trigger and a tightly scoped target. It fully satisfies the what/when/who guidance with no fluff or over-claims.

DimensionReasoningScore

Specificity

Lists multiple concrete actions ("install, deploy, run, validate, troubleshoot, or stop") tied to a specific target ("NVIDIA AI-Q Blueprint infrastructure"), matching the 'lists multiple specific concrete actions' anchor.

3 / 3

Completeness

Explicitly answers both what (the six infra operations on AI-Q Blueprint) and when ("Use when asked to..."), satisfying the 'clearly answers both what AND when with explicit triggers' anchor rather than capping at 2 for a missing trigger clause.

3 / 3

Trigger Term Quality

Natural verbs a user would say ("install", "deploy", "run", "validate", "troubleshoot", "stop") give good coverage of likely request phrasings, matching the 'good coverage of natural terms' anchor.

3 / 3

Distinctiveness Conflict Risk

Scoped to "NVIDIA AI-Q Blueprint infrastructure" with a clear niche and distinct triggers, unlikely to fire for unrelated skills; matches the 'clear niche with distinct triggers' anchor.

3 / 3

Total

12

/

12

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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