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customerio-deploy-pipeline

Deploy Customer.io integrations to production cloud platforms. Use when deploying to Cloud Run, Vercel, AWS Lambda, or Kubernetes with proper secrets management and health checks. Trigger: "deploy customer.io", "customer.io cloud run", "customer.io kubernetes", "customer.io lambda", "customer.io vercel".

72

Quality

91%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

92%Weight 40%Scale 1-3

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

The body is highly actionable, lean, and well-sequenced with explicit validation gating for production deployments. Its main weakness is progressive disclosure: a reference bundle exists but is neither linked from the body nor used to offload the duplicated platform-deployment details that are inline.

Suggestions

Link references/implementation-guide.md from the body (e.g., 'For full platform-by-platform walkthroughs, see [implementation-guide.md](references/implementation-guide.md)') so the bundle is discoverable and signaled.

Move the duplicated platform deployment code (Cloud Run workflow, Vercel handler, K8s manifests, blue-green script) into the reference and keep SKILL.md as a concise overview with one representative example plus pointers, to avoid the inline/reference overlap.

Reconcile divergent details between the body and the reference (e.g., secret env var names CUSTOMERIO_TRACK_API_KEY vs CUSTOMERIO_API_KEY, container ports 3000 vs 8080, replicas 2 vs 3) so the two do not give conflicting instructions.

DimensionReasoningScore

Conciseness

The body is lean prose with no explanations of concepts Claude already knows (no 'what is Cloud Run'), and relies on direct, purposeful code/config blocks, a compact checklist, and a terse error-handling table — every section earns its place. It is above 2 because there is no unnecessary prose padding or concept explanation despite the volume of code.

3 / 3

Actionability

Every step provides fully executable, copy-paste-ready artifacts: a complete GitHub Actions workflow YAML, TypeScript health-check and Vercel handlers, Kubernetes manifests, and a runnable bash blue-green script with real gcloud commands. It is above 2 because the code is concrete and complete rather than pseudocode or vague direction.

3 / 3

Workflow Clarity

Steps are explicitly sequenced (Step 1-5) and the production/deployment risk is gated by a real validation checkpoint in the blue-green script ('if [ "${HEALTH}" != "200" ]; then ... exit 1') plus a deployment checklist and error-handling table. It is above 2 because explicit validation feedback loops are present for this destructive production operation, satisfying the cap exception.

3 / 3

Progressive Disclosure

A bundle file (references/implementation-guide.md) exists but is never referenced or linked from the body, and the body duplicates much of that reference's content (Cloud Run, Vercel, K8s, health check, blue-green) inline. It is above 1 because the body is well-sectioned into labeled steps with checklists and resources, but below 3 because the reference is un-signaled and content that belongs in it is repeated inline.

2 / 3

Total

11

/

12

Passed

Description

90%Weight 40%Scale 1-3

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, well-structured description that clearly states what it does, when to use it, and lists natural trigger phrases scoped to a distinct Customer.io deployment niche. Its only weakness is that the capability statement relies on a single verb ('deploy') plus a platform list rather than enumerating several distinct concrete actions.

DimensionReasoningScore

Specificity

The core verb is a single action — 'Deploy Customer.io integrations to production cloud platforms' — with the enumerated platforms (Cloud Run, Vercel, AWS Lambda, Kubernetes) and concerns ('secrets management and health checks') acting as scope/conditions rather than multiple distinct actions like 'extract, fill, merge'. It is below 3 because it names one main action with a platform list, not a list of several concrete distinct actions, and above 1 because it does name a specific domain and concrete operational concerns.

2 / 3

Completeness

It explicitly answers what ('Deploy Customer.io integrations to production cloud platforms ... with proper secrets management and health checks') and when ('Use when deploying to Cloud Run, Vercel, AWS Lambda, or Kubernetes ... Trigger: ...'), matching the anchor that clearly answers both with explicit triggers.

3 / 3

Trigger Term Quality

Trigger phrases 'deploy customer.io', 'customer.io cloud run', 'customer.io kubernetes', 'customer.io lambda', 'customer.io vercel' are natural phrasings a user would actually say and give good coverage across the supported platforms. It is above 2 because the terms are natural and platform-varied rather than technical jargon.

3 / 3

Distinctiveness Conflict Risk

The niche is clearly scoped to 'Customer.io' deployments on specific cloud platforms with distinct, brand-prefixed triggers ('customer.io cloud run', 'customer.io vercel'), making it unlikely to trigger for unrelated skills.

3 / 3

Total

11

/

12

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.

Validation13 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

allowed_tools_field

'allowed-tools' contains unusual tool name(s)

Warning

frontmatter_unknown_keys

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

Warning

referenced_paths_exist

Referenced path issues: 1 missing

Warning

Total

13

/

16

Passed

Repository
jeremylongshore/claude-code-plugins-plus-skills
Reviewed

Table of Contents

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