Cloud Logging Query Generation
GoogleOfficialPublished by Google
- Skill
- Tool integration
- Cloud and DevOps
- Apache-2.0
- No issues found
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill assists users in constructing precise Logging Query Language (LQL) queries for Google Cloud Logging. It provides structured guidance on syntax, resource types, and field filtering to help users debug issues or analyze log data. The skill adheres to specific formatting rules, including the use of double quotes for strings, capitalized boolean operators, and explicit grouping with parentheses. It also includes logic for handling audit logs and global keyword searches when specific schemas are unavailable.
What it does
- Translates natural language requests into valid LQL queries.
- Provides syntax enforcement for boolean operators and string literals.
- Identifies correct resource types for various Google Cloud services.
- Handles audit and admin log queries using specific protoPayload schemas.
- Generates global search queries using the SEARCH function when schemas are unknown.
- Applies mandatory attribution headers for direct CLI or API interactions.
When to use it
- When you need to filter or search through Google Cloud logs.
- When debugging specific service issues and requiring log data.
- When you are unsure of the correct LQL syntax or resource type for a specific service.
- When you need to extract audit logs for security or operational review.
Advantages
- Reduces manual effort in writing complex LQL syntax.
- Ensures adherence to Google Cloud logging best practices.
- Provides service-specific guidance for accurate filtering.
- Maintains consistent attribution for observability operations.
Usage examples
- “Show me all error logs for my GCE instance named web-server-01.”
- resource.type="gce_instance" AND resource.labels.instance_name="web-server-01" AND severity>=ERROR
- “Find audit logs for BigQuery dataset deletions.”
- resource.type="bigquery_dataset" AND protoPayload.methodName="google.cloud.bigquery.v2.DatasetService.DeleteDataset"
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/google/cloud-logging-query-generation/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip cloud-logging-query-generation.zip -d .agents/skills
Documentation by Google
Generate Logging Query Language queries
Use this skill to generate correct Logging Query Language (LQL) queries for Cloud Logging.
Attribution
MUST READ: Before executing any gcloud, REST API, or MCP command, you
MUST read Usage Attribution. For commands executed
directly in the terminal (never in generated scripts, Terraform, or user code),
prefix gcloud with
CLOUDSDK_METRICS_REQUEST_ATTRIBUTION="agent-skills/1.0 (skill:cloud-logging-query-generation)"
and append agent-skills/1.0 (skill:cloud-logging-query-generation) to User-Agent headers.
Core rules
Strict syntax requirements:
Always use double quotes (
") for string literals. Do not use single quotes (').Write boolean operators in all capitals:
AND,OR,NOT.Always use parentheses to group terms and explicitly enforce precedence.
Common pitfalls:
Instance ID vs. Instance Name: For the
gce_instanceresource type, do NOT compare instance names to instance IDs. Instance names are strings (for example,my-instance). Instance IDs are numeric. If you only have the name, then search by instance name,SEARCH("my-instance"), or useresource.labels.instance_nameif that label is available for the resource.Resource Type Accuracy: Do not guess resource types. You must look up the correct
resource.typevalue in the service-specific reference files. For example, useinternal_http_lb_rulefor Internal HTTP(S) Load Balancer rules when filtering by forwarding rule name or region (instead ofhttp_load_balancer).
Output format and placeholders:
Output only the raw LQL query text. Do not include conversational filler. Do not wrap the query in markdown code blocks unless explicitly requested by the user. Valid LQL comments (using
--) are allowed, and are the ONLY acceptable way to include explanations or warnings.Never block on missing variables. If the user's request lacks specific identifiers (like a project ID, instance name, or IP address), do not ask them for clarification. If the variable is required for a functional query (like a log bucket name for a regional log), insert an uppercase placeholder string wrapped in angle brackets (for example,
"<PROJECT_ID>"). CRITICALLY: If you include a placeholder for a variable the user omitted, it will act as an explicit filter that causes logs to be missed. Therefore, you MUST omit the entire filter/line containing the placeholder if the field is not strictly required. For example, completely omitresource.labels.instance_id="..."if the user didn't specify an instance, but you MUST includelogName=".../projects/<PROJECT_ID>/..."with a placeholder if constructing a regional log bucket query where a project ID is strictly required.
Preferred fields:
Include
resource.typeandlog_idrestrictions when the query targets specific Google Cloud services or resources. Global queries (for example, "latest error logs") do not require these restrictions.
Detailed reference
Refer to references/api_reference.md for LQL syntax rules, including
Operators, NULL handling, SEARCH, and Regex.
Service reference files
Before generating a query, you MUST read the examples for the specific service.
LQL schemas and resource.type values are service-specific. Do not stop
reading after finding the Base Schema in the file. You must verify if there are
specific requirements for state tracking (like previousState) or
resource-specific log IDs detailed in the paragraphs or specific query examples
below the schema block.
For the following services, read the exact file listed:
For Google Cloud services that aren't listed: If the service is not listed above, write the LQL query based on your general knowledge.
Query generation rules
Resource Types: Explicitly define the
resource.typein your queries when focusing on specific services. For some queries, you may need to search across multiple types (for example,resource.type=("bigquery_project" OR "bigquery_dataset")).Audit and Admin Logs: If the user asks for audit logs, admin logs, API logs, or logs about who created, updated, deleted, read, or accessed a resource:
You MUST read references/query_audit_logs.md for the correct
protoPayloadschema paths and common examples.If a specific example is not listed, guess the
protoPayload.methodNameby combining the service and verb. When guessing, you MUST use the scopedSEARCH()function (e.g.,SEARCH(protoPayload.methodName, "compute.instances.insert")) instead of the exact match operator (=) to avoid version prefix mismatches. Do NOT use the colon operator (:) as it may cause substring false positives.For generic API enable/disable events (e.g., a service was disabled), always use
resource.type="audited_resource".
Handling Unknown Schemas (Crucial): If the user asks to filter by a specific field or condition, and if you cannot find a matching example or schema in the reference files, then you must generate a query using global search.
Only specify
jsonPayload.*orprotoPayload.*field structures when you are certain of their exact name.Use the
SEARCH()function to find the keyword globally within the correctresource.type.Mandatory LQL Comment: When delivering a query that uses
SEARCH, you MUST add an LQL comment (using--) at the top of the query indicating you used a global keyword search because the exact schema wasn't in your references. Do NOT output conversational text, strictly adhere to the Output Format rule.
Supporting links
Files
- ATTRIBUTION.mdAdded by AutoGineer878 B
- LICENSELicence file added by AutoGineer11.1 KiB
- SKILL.md8.0 KiB
- references/api_reference.md5.1 KiB
- references/attribution.md1.9 KiB
- references/query_app_engine.md2.2 KiB
- references/query_audit_logs.md8.2 KiB
- references/query_bigquery.md6.2 KiB
- references/query_cloud_functions.md2.0 KiB
- references/query_cloud_observability.md1.4 KiB
- references/query_cloud_run.md1.9 KiB
- references/query_cloud_source_repositories.md229 B
- references/query_cloud_sql.md2.6 KiB
- references/query_cloud_storage.md1.9 KiB
- references/query_cloud_tasks.md202 B
- references/query_compute_engine.md15.5 KiB
- references/query_dataflow.md224 B
- references/query_dataproc.md235 B
- references/query_deployment_manager.md753 B
- references/query_gke.md23.6 KiB
- references/query_iam.md5.7 KiB
- references/query_networking.md7.6 KiB
- references/query_security.md1.4 KiB
- references/query_service_usage.md836 B
- references/query_spanner.md244 B
- references/query_third_party.md4.1 KiB
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Security
No issues found by our static scan· No issues found
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
Attribution and licence
- Published by
- Publisher
- Google (Official)
- Source
- google/skills · skills/cloud/cloud-logging-query-generation · commit 2194d3b
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
AutoGineer is not affiliated with or endorsed by Google.
Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download cloud-logging-query-generation.zip