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customerio-observability

Set up Customer.io monitoring and observability. Use when implementing metrics, structured logging, alerting, or Grafana dashboards for Customer.io integrations. Trigger: "customer.io monitoring", "customer.io metrics", "customer.io dashboard", "customer.io alerts", "customer.io observability".

67

Quality

82%

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SecuritybySnyk

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SKILL.md
Quality
Evals
Security

Quality

Content

65%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 — packed with executable, copy-paste-ready TypeScript/YAML/JSON for every part of the observability stack — and sensibly sequenced. Its weaknesses are structure, not substance: the full implementation is inlined in SKILL.md while two reference files sit orphaned and unreferenced, the workflow lacks validation checkpoints, and the code carries some repetition that could be tightened.

Suggestions

Move the bulk implementation (the instrumented client, Grafana dashboard JSON, and alerting YAML) into the existing references/ files and replace the inline blocks with a concise overview plus clearly signaled one-level-deep links (e.g., 'Full client instrumentation: See references/implementation-guide.md'), so SKILL.md becomes a lean overview rather than a 350-line monolith.

Add explicit validation checkpoints to the workflow — e.g., after Step 5 a 'Verify Prometheus scrapes /metrics and returns cio_* series' step, and after Step 6 a 'Confirm each Grafana panel query resolves in Explore before saving' step — to close the validation gaps that currently cap workflow_clarity at 2.

Tighten the repetitive InstrumentedCioClient by showing the timer/inc/error pattern once on a representative method and noting the others follow it, and drop the Step 3 usage block that spells out pino's expected log output, since Claude can infer it from the config.

DimensionReasoningScore

Conciseness

The body is mostly efficient code without concept explanations Claude already knows, but at ~350 lines it could be tightened — the InstrumentedCioClient repeats the same timer/inc/error pattern across three near-identical methods, and the Step 3 usage block spelling out pino's log output is unnecessary. It is not anchor 3 ('every token earns its place') because of this repetition, and not anchor 1 because it contains no padded conceptual prose.

2 / 3

Actionability

Nearly the entire body is fully executable, copy-paste-ready code: prom-client metric definitions, a complete InstrumentedCioClient class, a pino logger config, an express /metrics endpoint, a Grafana panel JSON model, and Prometheus alerting YAML. It is concrete and specific rather than descriptive or pseudocode, matching the anchor 3 example.

3 / 3

Workflow Clarity

The seven steps (Metrics → Client → Logging → Webhooks → Endpoint → Dashboard → Alerting) are clearly numbered and logically sequenced, but there are no validation checkpoints, feedback loops, or checklists — no 'verify /metrics scrapes', 'confirm dashboard queries resolve', or 'test an alert fires'. The Error Handling table is reactive troubleshooting, not an in-workflow validation step, so it does not reach anchor 3.

2 / 3

Progressive Disclosure

Two bundle files exist (references/implementation-guide.md and references/implementation.md) but neither is referenced or linked anywhere in the body, while the full implementation is inlined as ~350 lines of code across seven steps — the anchor 2 anti-pattern of 'content that should be separate is inline' with references present but not signaled. It is not anchor 1 because the body is well-organized with clear sections and no nested references, and not anchor 3 because the content is not split out and the existing references are orphaned.

2 / 3

Total

9

/

12

Passed

Description

100%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: third-person, concise, with an explicit Use-when clause, several concrete capabilities, and a set of natural triggers tightly scoped to Customer.io observability. No fluff, no over-claims, and low conflict risk.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions — 'metrics, structured logging, alerting, or Grafana dashboards' — under the overall 'Set up Customer.io monitoring and observability' task, matching the multiple-specific-actions anchor rather than the single-action anchor 2.

3 / 3

Completeness

It explicitly answers both what ('Set up Customer.io monitoring and observability') and when (an explicit 'Use when implementing...' clause plus a Trigger list), so it is not capped at 2 for a missing Use-when clause.

3 / 3

Trigger Term Quality

The Trigger clause supplies natural phrases a user would say — 'customer.io monitoring', 'customer.io metrics', 'customer.io dashboard', 'customer.io alerts', 'customer.io observability' — covering the common entry points rather than only jargon.

3 / 3

Distinctiveness Conflict Risk

Every trigger is qualified with 'customer.io', scoping it to a specific SaaS integration, so it occupies a clear niche unlikely to fire for generic monitoring skills.

3 / 3

Total

12

/

12

Passed

Validation

87%

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

Validation14 / 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

Total

14

/

16

Passed

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

Table of Contents

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