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ai-gateway

Vercel AI Gateway guidance for setup, model discovery, authentication, routing, fallbacks, virtual models, evaluation models, BYOK, budgets, spend reporting, observability, compatible APIs, and coding-agent configuration. Use when adding AI Gateway to an app, migrating provider calls, choosing models or providers, centralizing model configuration, evaluating application state, debugging gateway requests, or running `vercel ai-gateway` commands.

80

1.00x
Quality

93%

Does it follow best practices?

Impact

88%

1.00x

1 of 3 eval scenarios. Add 2 more for a full score.

SecuritybySnyk

Passed

No findings from the security scan

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 well-engineered skill body: executable commands and code, a sequenced workflow with explicit validation and a verification checklist, and clean one-level-deep progressive disclosure into six substantive reference files. The only weakness is mild — a dense paragraph overlapping references/evaluation.md and inline version pins that could be trimmed or relocated.

DimensionReasoningScore

Conciseness

The body is efficient — lean tables, one short code block, detail pushed to references — with minor trimmable instances: the dense modality/decisions paragraph repeats detail owned by references/evaluation.md, and version pins ("CLI 59.13+", "ai 7.0.128+") sit inline though mostly framed with deprecation notes. Not 5 because a few tokens could still be cut; not 3 because padding is minor, not 'some unnecessary explanation'.

4 / 5

Actionability

Fully executable guidance throughout: `curl -fsSL https://ai-gateway.vercel.sh/v1/models`, a copy-paste-ready TypeScript example with an env-var guard, exact baseURL values per SDK, concrete env var names (AI_GATEWAY_API_KEY, VERCEL_OIDC_TOKEN), and a CLI command table. Specific examples cover the common integration cases with no execution gaps.

5 / 5

Workflow Clarity

The 9-step Implementation workflow is clearly sequenced with explicit validation checkpoints (formatter/type checker/focused tests, one authorized live request with metadata inspection, Logs verification), enumerated error outcomes to act on, and a dedicated Verification checklist; outward-facing spend actions are gated on user approval. This matches the anchor requiring explicit validation, error handling, and checklists.

5 / 5

Progressive Disclosure

The body is a true overview: the "Route the request to the right guide" table maps each user job to one of six real, substantive, one-level-deep reference files (all verified to exist with real content), and domain detail is appropriately split into them. Navigation is easy and references are clearly signaled.

5 / 5

Total

19

/

20

Passed

Description

95%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 strong description: it names the product niche, enumerates a comprehensive and specific capability surface, and pairs it with an explicit, trigger-rich "Use when" clause. The only improvement space is converting topic nouns into action verbs (e.g., "route requests across providers" rather than "routing").

DimensionReasoningScore

Specificity

Enumerates many specific capabilities — "setup, model discovery, authentication, routing, fallbacks, virtual models, evaluation models, BYOK, budgets, spend reporting, observability, compatible APIs, and coding-agent configuration" — but as topic nouns rather than the concrete action verbs of the 5 anchor. Coverage is well beyond the 1-2 actions of anchor 3, so it sits at 4 with minor gaps.

4 / 5

Completeness

Explicitly answers what ("Vercel AI Gateway guidance for setup, model discovery, authentication, routing, fallbacks…") and when ("Use when adding AI Gateway to an app, migrating provider calls… or running `vercel ai-gateway` commands") with concrete trigger phrases, matching the 5 anchor exactly. Neither half is vague or implied.

5 / 5

Trigger Term Quality

Natural trigger coverage is comprehensive: "adding AI Gateway to an app", "migrating provider calls", "choosing models or providers", "debugging gateway requests", "running `vercel ai-gateway` commands", plus "routing, fallbacks, BYOK, budgets, spend reporting". No meaningful natural phrasing a user would say for this product is missing, matching the comprehensive-synonyms anchor.

5 / 5

Distinctiveness Conflict Risk

"Vercel AI Gateway" anchors a clear product niche with product-specific triggers ("vmc/"-adjacent virtual models, `vercel ai-gateway` CLI, BYOK), giving minimal conflict risk. The only residual overlap is a generic "ai gateway" mention (e.g., Cloudflare's), which the consistent Vercel qualifier disambiguates — not enough to drop below the clear-niche anchor.

5 / 5

Total

19

/

20

Passed

Validation

81%

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

Validation — 13 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

metadata_field

'metadata' should map string keys to string values

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

13

/

16

Passed

Repository

vercel/vercel-plugin

Path

skills/ai-gateway/SKILL.md

Reviewed

Table of Contents

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