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cloud-monitoring-promql-query

Generates valid PromQL queries from Cloud Monitoring metric descriptors and resource parameters. Use when asked to create, generate, write, or format PromQL queries, PromQL strings, or PromQL aggregations for Cloud Monitoring metrics and resources. Don't use for raw metric discovery or metric selection.

Quality

88%

Does it follow best practices?

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

88%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.

The body is a highly actionable, well-sequenced workflow with real references and an explicit validate-and-retry loop. Its weaknesses are moderate emphasis padding and some detailed mapping content inlined in SKILL.md that could live in the aggregations reference.

Suggestions

Trim the repeated MUST/CRITICAL emphasis in the project-ID and attribution sections to single concise statements.

Move the detailed normalization recipe or state-label filtering rules into references/basic_aggregations.md (or a dedicated reference) and keep a one-line summary in the body, since that file is already declared the single source of truth.

DimensionReasoningScore

Conciseness

Nearly all content is actionable rules, commands, and examples with no explanations of concepts Claude already knows, but repeated heavy emphasis ("MUST READ", "CRITICAL & BLOCKING", "Do NOT generate... do not run... do not use") pads several sections. Not 5 because the emphasis and restatement in the project-ID and attribution sections could be trimmed without losing clarity.

4 / 5

Actionability

Fully executable guidance: a copy-paste curl command for resource descriptors, a dependency-install one-liner, a batch linter invocation, and a six-step metric-name normalization recipe with a worked example at every step, plus incorrect/correct PromQL snippets. Covers the common cases concretely.

5 / 5

Workflow Clarity

Clear sequence (resolve project -> inspect descriptors -> resolve resource filters -> choose aggregation -> format and validate) with a blocking gate when the project ID is missing, an explicit validation step, and a feedback loop that routes failures through the error-recovery reference before retrying. Not 4 because both checkpoints and error-recovery loops are explicit.

5 / 5

Progressive Disclosure

Three real, well-signaled, one-level-deep references plus a validation script, with clear section headers for navigation. Not 5 because the ~190-line body inlines sizable material (the full normalization recipe, state-label filtering rules) alongside a reference declared 'the single source of truth', a minor organization gap.

4 / 5

Total

18

/

20

Passed

Description

82%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: third-person voice, an explicit what/when pair with concrete trigger verbs, and a negative boundary that sharply reduces conflict risk. The main weakness is specificity — it names only one capability rather than several concrete actions.

Suggestions

Enumerate 2-3 concrete capabilities in the 'what' sentence (e.g., mapping metric kinds/value types to aggregations, resource-label scoping, syntax validation) to raise specificity.

Add one or two natural user phrasings to the trigger clause, such as 'query Cloud Monitoring metrics with PromQL' or 'convert Cloud Monitoring metrics to PromQL'.

DimensionReasoningScore

Specificity

"Generates valid PromQL queries from Cloud Monitoring metric descriptors and resource parameters" names the domain and one concrete action, but does not enumerate several distinct capabilities. Not 4 because coverage is limited to a single action rather than a list with only minor gaps.

3 / 5

Completeness

Explicitly answers what ("Generates valid PromQL queries from Cloud Monitoring metric descriptors and resource parameters") and when ("Use when asked to create, generate, write, or format PromQL queries...") with concrete trigger phrases. Matches the anchor-5 example; not below because neither half is missing or vague.

5 / 5

Trigger Term Quality

"create, generate, write, or format PromQL queries, PromQL strings, or PromQL aggregations" gives good natural keyword coverage across verb and object variations. Not 5 because a few natural phrasings users might say (e.g., charting or querying Cloud Monitoring metrics) are absent.

4 / 5

Distinctiveness Conflict Risk

Clear niche (PromQL generation for Cloud Monitoring) with an explicit negative boundary ("Don't use for raw metric discovery or metric selection") that separates it from the sibling metric-selection skill. Minimal conflict risk with other skills.

5 / 5

Total

17

/

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

google/skills

Path

skills/cloud/cloud-monitoring-promql-query/SKILL.md

Reviewed

Table of Contents

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