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vllm-sr

Install, configure, and verify vLLM Semantic Router on a Docker host (CPU, AMD, or NVIDIA GPU) or a Kubernetes cluster, then operate it through its CLI and Router API. Use for a first install, an upgrade, routing verification, configuration changes, recipe tuning, and single-model/MoM evaluation.

77

Quality

97%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

The canonical home for this skill is vllm-sr-agent-operations in vllm-project/semantic-router

SKILL.md
Quality
Evals
Security

Quality

Content

92%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 high-quality operational skill: fully executable commands with explicit pass/fail criteria at every step, a clearly sequenced install-to-handoff workflow with feedback loops, and clean one-level-deep offloading of advanced topics to real reference files. The only deduction is minor verbosity around version/channel drift handling and slight flag-rationale repetition.

Suggestions

Move the 0.4.0/stable-vs-dev version drift guidance in step 3 into a compact 'Older releases' note or the deployment reference, keeping time-sensitive version details out of the main flow.

State the platform and gateway flag choices once (step 2) and reference that decision from steps 4-5 instead of re-explaining when to use --gateway extproc and --platform.

DimensionReasoningScore

Conciseness

The body is lean and operational throughout — commands, pass criteria, and otherwise-branches with no explanations of concepts Claude already knows. It falls short of 5 because the inline version-sensitive channel negotiation ("If the user insists on `0.4.0`, its stack always runs Envoy and has no `--gateway`...") is time-sensitive guidance outside any deprecated/old-patterns section, and platform/gateway flag rationale repeats slightly across steps 2, 4, and 5.

4 / 5

Actionability

Every step is copy-paste executable: a preflight command block, a complete config.yaml, per-platform serve invocations, verification curls with expected response headers, and an end-to-end probe command. The common cases (cpu/rocm/cuda, Ollama and vLLM backends) are all covered with concrete commands rather than pseudocode.

5 / 5

Workflow Clarity

Steps 1-7 are strictly sequenced, each with explicit "Pass"/"Otherwise" validation criteria (tables in steps 1-2, six numbered checks in step 6), and an explicit feedback loop ("find the symptom in Troubleshooting, fix one thing, rerun that step, and report the change"). This matches the anchor with validation checkpoints and error-recovery loops.

5 / 5

Progressive Disclosure

The body keeps install/config/verify inline and splits deeper material (GPU details, Kubernetes, troubleshooting, configuration changes, recipe tuning, sr-bench) into six real one-level-deep reference files, summarized in a clear "After the install" navigation table. Spot-checks confirm the reference files exist locally and do not nest further, fitting the well-signaled one-level-deep anchor.

5 / 5

Total

19

/

20

Passed

Description

100%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.

The description is exemplary: concrete third-person actions, an explicit "Use for" clause enumerating natural trigger scenarios, product-specific distinctiveness, and no filler. It clearly separates what the skill does from when to invoke it.

DimensionReasoningScore

Specificity

Multiple concrete actions are named ("Install, configure, and verify", "operate it through its CLI and Router API") across specific environments ("Docker host (CPU, AMD, or NVIDIA GPU) or a Kubernetes cluster"), giving comprehensive coverage in third-person voice. Not the 4 anchor, since action coverage spans install, configuration, verification, operation, and evaluation with no notable gaps.

5 / 5

Completeness

The first sentence explicitly answers "what" (install, configure, verify, and operate the router) and "Use for a first install, an upgrade, routing verification..." explicitly answers "when" with concrete trigger phrases, matching the 5 anchor structure exactly.

5 / 5

Trigger Term Quality

Phrases like "a first install", "an upgrade", "routing verification", "configuration changes", "recipe tuning", and "single-model/MoM evaluation" are exactly what a user would naturally say when needing this skill, alongside the product name and platform terms. Only trivial variants (e.g., the "vLLM SR" shorthand) are absent, so it sits at the comprehensive anchor rather than 4.

5 / 5

Distinctiveness Conflict Risk

"vLLM Semantic Router" names a clear niche and every trigger (install/upgrade/routing verification/recipe tuning for this product) is product-specific, so it is unlikely to fire for an unrelated skill.

5 / 5

Total

20

/

20

Passed

Validation

100%

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

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

vllm-project/semantic-router

Path

website/static/install/agent/vllm-sr/SKILL.md

Reviewed

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