What does this skill do, and when should you use it?
This skill generates Logging Query Language (LQL) queries for Google Cloud Logging from natural-language requests. It is intended for querying log data and debugging issues, including filtering by Google Cloud service or resource. Its instructions enforce LQL syntax, service-specific resource types, audit-log fields, and placeholder handling for missing identifiers. It is scoped to Cloud Logging and is not intended for SQL, Spanner, or other databases.
It reads the relevant service query examples and LQL API reference, then produces raw LQL query text. It selects fields such as resource.type, log_id, protoPayload, or jsonPayload when supported, and applies rules for quoting, boolean operators, parentheses, instance names versus instance IDs, and audit-log methodName matching. When identifiers such as project IDs, instance names, or IP addresses are missing, it inserts uppercase angle-bracket placeholders. For unknown field schemas, it can use global SEARCH() with an explanatory LQL comment.
- A Google Cloud operator needs to filter logs for a particular service, resource, or log ID.
- A developer is debugging a Google Cloud issue and wants an LQL query generated from a natural-language description.
- An infrastructure engineer needs correct resource.type filtering for Compute Engine, Cloud Run, networking, or another supported service.
- A security or platform team needs to find audit logs for resource creation, updates, deletions, or API calls.
- A user needs a keyword-based global search when the requested field is not documented in the available service references.
How do you install this skill?
- Do not treat the output as an execution-verified query; manually check resource.type, field paths, and protoPayload.methodName, especially for audit logs.
- The skill inserts placeholders and forbids clarification for missing identifiers, which can produce non-runnable or overly broad queries.
- Logs may contain sensitive information; confirm access scope and disclosure risks before using global SEARCH.
- Chinese users should provide explicit service names, resource types, fields, and time ranges, then review the generated English LQL syntax.
- Local filesystem
Run npx skills add google/skills, then select the desired skill from the installation prompt. The repository contains about 90 skills; this profile covers only skills/cloud/cloud-logging-query-generation. The source does not document the final installation directory.
tmp="$(mktemp -d)"
git clone --depth 1 https://github.com/google/skills.git "$tmp"
mkdir -p ~/.claude/skills
cp -R "$tmp/skills/cloud/cloud-logging-query-generation" ~/.claude/skills/
rm -rf "$tmp"Generated from the source repository and skill path; it copies only this skill's folder. If the author's install steps above differ, follow those first. To scope it to one project, replace ~/.claude/skills with that project's .claude/skills.
How do you use this skill?
After installation, provide a natural-language Cloud Logging request, for example: Generate an LQL query for error logs from Cloud Run in project <PROJECT_ID>. The skill should return only the raw LQL query text and should use uppercase angle-bracket placeholders for missing identifiers.
What are this skill's strengths and limitations?
- Provides explicit rules for double-quoted strings, uppercase boolean operators, and parenthesized terms.
- Includes service-specific query references for many Google Cloud services.
- Addresses audit-log methodName matching and resource-type accuracy.
- Avoids blocking on missing identifiers by inserting placeholders.
- It is limited to Google Cloud Logging LQL and is not for SQL, Spanner, or other databases.
- The source provides no test suite, query-validation workflow, or platform testing evidence.
- For services not covered by the listed references, query generation relies on general knowledge and may require review.
- The reference-file contents are not included in the supplied material, so actual results depend on the complete skill package.
How does this skill compare with similar options?
Side by side with related skills; every score comes from the same FSRS standard.
| Skill | FS score | Stars | Last updated | License |
|---|---|---|---|---|
| Google Cloud Logging Query Builder this page ✓ Google · Official | 52 · Use with care | ★ 21k | 12d ago | Apache-2.0 |
| GouvernAI — Runtime Guardrails for Claude Code | 57 · Use with care | ★ 23 | 3mo ago | MIT |
| Google Cloud gcloud CLI Safety Skill ✓ Google · Official | 51 · Use with care | ★ 21k | 12d ago | Apache-2.0 |
| Google Cloud Performance Advisor ✓ Google · Official | 50 · Use with care | ★ 21k | 12d ago | Apache-2.0 |
| Google Cloud Sustainability Advisor ✓ Google · Official | 48 · Use with care | ★ 21k | 12d ago | Apache-2.0 |
How did FollowSkills review this skill?
The skill only generates query text; it does not execute queries, request credentials, or modify resources, so permissions and external effects are limited. However, it provides no guidance for sensitive log data, redaction, least disclosure, rollback, or user confirmation, so points are deducted.
The rules, examples, and references are inconsistent: the skill requires uppercase boolean operators and parentheses, while many examples omit parentheses or use inconsistent formatting. Audit method names may be guessed, and there are no tests, edge-case coverage, or failure-feedback rules; the score therefore remains below the static-review ceiling.
The audience, main use cases, and exclusion of other databases are reasonably clear, with defined placeholders and service-reference triggers. However, there are no Chinese examples or Chinese-input guidance, semantic trigger boundaries are incomplete, and unlisted services rely on general knowledge, so points are deducted.
The documentation is readable and layered, with core rules, reference files, examples, supporting links, installation guidance, an Apache-2.0 license, and an issue path. The selected skill lacks its own version, changelog, explicit maintenance responsibility, and complete troubleshooting guidance; referenced service coverage is also incomplete.
The raw LQL output is directly copyable into Cloud Logging, and service examples and placeholders add practical value. Still, the supplied material does not verify query executability; unknown fields fall back to broad SEARCH queries, and guessed audit method names may be wrong, requiring manual review, so the score is capped at the static-review limit.
The skill includes LQL guidance, service examples, and links to official documentation, providing some auditability. It includes no committed tests, CI execution evidence, versioned validation results, or independent cross-source reproduction, so the evidence remains thin.
Open a dimension to read why it scored that way
Evidence confidence：Low — Mostly static review, author material or a limited demo; useful for discovery, not high-risk decisions.
See the full review method →