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wrangler

Cloudflare Workers CLI for deploying, developing, and managing Workers, KV, R2, D1, Vectorize, Hyperdrive, Workers AI, Containers, Queues, Workflows, Pipelines, and Secrets Store. Load before running wrangler commands to ensure correct syntax and best practices. Biases towards retrieval from Cloudflare docs over pre-trained knowledge.

68

Quality

85%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

78%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.

This is a highly actionable, token-efficient command reference with genuine validation checkpoints (wrangler check, --dry-run, types --check) and useful non-obvious notes. Its main structural weakness is the absence of any progressive disclosure: with no reference files in the bundle, the entire 15-product command reference lives inline in SKILL.md and loads into every invocation, with some binding examples duplicated between the full-config section and per-product sections.

Suggestions

Move per-product command references (KV, R2, D1, Vectorize, Hyperdrive, Containers, Workflows, Pipelines, Secrets Store) into separate files like references/d1.md, references/kv.md, etc., and keep SKILL.md as an overview with one-line pointers (e.g., "**D1**: See [references/d1.md](references/d1.md)") so only the relevant product's details load on demand.

Deduplicate binding shapes: the full-config example already shows kv_namespaces, r2_buckets, d1_databases, vectorize, and hyperdrive bindings, so the later per-product "Config Binding" sections that merely repeat those shapes can be dropped or merged into the moved-out reference files.

Add an explicit feedback loop for the deploy path, e.g., "Run `wrangler check` → fix any config errors → `wrangler deploy --dry-run` → only then `wrangler deploy`", and note that `wrangler rollback <VERSION_ID>` is the recovery step if a deploy misbehaves.

DimensionReasoningScore

Conciseness

The body is almost entirely executable commands and config snippets with terse comments, and non-obvious notes like "Workers AI always runs remotely and incurs usage charges even in local dev" earn their tokens; there is no explaining of concepts Claude already knows. It falls just short of anchor 5 because of redundancy: binding shapes for KV/R2/D1 appear both in the full config example and again in per-product "Config Binding" sections, which duplicates earlier material — but it is well above anchor 3, since there is essentially no padded prose.

4 / 5

Actionability

Every section is copy-paste ready: "wrangler d1 create my-database --location wnam", "echo "secret-value" | wrangler secret put API_KEY", complete jsonc config blocks, a runnable vitest-pool-workers config, and a troubleshooting table mapping concrete errors to concrete fixes. This matches anchor 5 (fully executable, specific examples covering common cases); there is no pseudocode or hand-waving anywhere in the body.

5 / 5

Workflow Clarity

The flow is sequenced and checkpointed: "FIRST: Verify Wrangler Installation" with `wrangler --version`, "Validate config before deploy: Run `wrangler check`", "wrangler types --check" for CI, and "Use `--dry-run` before major deploys" — so destructive/batch operations (delete, rollback, deploy) do have adjacent validation guidance, avoiding the cap at 3, and unlike anchor 3 the checkpoints are explicit rather than implicit. It stops short of anchor 5 only because no validate->fix->retry feedback loop is spelled out for the deploy or rollback paths.

4 / 5

Progressive Disclosure

The skill ships no references/ or scripts/ files at all (only unreferenced assets/cloudflare.png and assets/cloudflare-small.svg), so ~900 lines covering 15+ products are inlined in SKILL.md — per the judging guideline, scored against the actual bundle structure: no reference files exist, so all detail is forced into the always-loaded body. Section headers give reasonable navigation, matching anchor 3's "some structure... content that should be separate is inline" (e.g., the full KV/R2/D1/Containers/Workflows command references belong in per-product reference files); it is above anchor 2 because the inline content is well-organized with clear headers rather than a structureless dump, and below anchor 4 because nothing is offloaded to separate files.

3 / 5

Total

16

/

20

Passed

Description

87%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 strong: it states a clear 'what' with an enumerated product scope, an explicit 'when' ("Load before running wrangler commands"), and highly distinctive Cloudflare-specific trigger terms. The only soft spot is that its action verbs (deploying, developing, managing) are generic compared to its otherwise excellent product-level specificity.

DimensionReasoningScore

Specificity

Phrases like "Cloudflare Workers CLI for deploying, developing, and managing Workers, KV, R2, D1, Vectorize, Hyperdrive, Workers AI, Containers, Queues, Workflows, Pipelines, and Secrets Store" enumerate a comprehensive, concrete list of managed resources, but the action verbs themselves (deploying, developing, managing) are generic. It matches anchor 4 (several specific actions, minor gaps) rather than 5, whose exemplar lists multiple distinct concrete actions; it is well above anchor 3, which covers only 1-2 actions in a single domain.

4 / 5

Completeness

The 'what' is explicit ("Cloudflare Workers CLI for deploying, developing, and managing Workers, KV, R2, D1...") and the 'when' is explicit and concrete ("Load before running wrangler commands to ensure correct syntax and best practices"). Both are answered with concrete trigger phrases, matching anchor 5 exactly; anchor 4 would require the 'when' to be merely adequate rather than this direct a load-trigger.

5 / 5

Trigger Term Quality

"Load before running wrangler commands" supplies the primary natural trigger term ("wrangler"), and product names like KV, R2, D1, and Workers AI are terms users actually say. Good keyword coverage with a few natural variations missing (e.g., no mention of "deploy my Worker" phrasing or Pages), matching anchor 4 rather than anchor 5's comprehensive synonym/extension coverage, and clearly above anchor 3's partial coverage.

4 / 5

Distinctiveness Conflict Risk

"Cloudflare Workers CLI" plus the product-specific names (KV, R2, D1, Vectorize, Hyperdrive, Secrets Store) and the command "wrangler" form a clear niche with minimal overlap risk against generic cloud or CLI skills. This matches anchor 5 (clear niche, distinct triggers); no neighboring skill would plausibly capture these triggers.

5 / 5

Total

18

/

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.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (898 lines); consider splitting into references/ and linking

Warning

Total

15

/

16

Passed

Repository

openai/plugins

Path

plugins/cloudflare/skills/wrangler/SKILL.md

Reviewed

Table of Contents

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