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google/cloud-logging-query-generation

google

cloud-logging-query-generation

Generates Logging Query Language (LQL) queries for Google Cloud Logging from natural language. Use this skill when you need to query log data or when you are debugging issues. You can filter log data by Google Cloud service. Don't use this skill to query other databases, such as SQL or Spanner.

global
New~1.6k
v1.0Saved Jul 14, 2026

Generate Logging Query Language queries

Use this skill to generate correct Logging Query Language (LQL) queries for Cloud Logging.

Core rules

  1. 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.
  2. Common pitfalls:

    • Instance ID vs. Instance Name: For the gce_instance resource 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 use resource.labels.instance_name if that label is available for the resource.
    • Resource Type Accuracy: Do not guess resource types. You must look up the correct resource.type value in the service-specific reference files. For example, use internal_http_lb_rule for Internal HTTP(S) Load Balancer rules when filtering by forwarding rule name or region (instead of http_load_balancer).
  3. 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. Instead, insert uppercase placeholder strings wrapped in angle brackets (for example, "<PROJECT_ID>", "<YOUR_SERVICE_NAME>") directly into the query.
  4. Preferred fields:

    • Include resource.type and log_id restrictions 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.

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

  1. Resource Types: Explicitly define the resource.type in 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")).
  2. Audit and admin logs: Google Cloud Audit logs (Admin Activity, Data Access) always follow a standard structure inside protoPayload. If the user asks for logs about who created, updated, or deleted a resource, or an API being called:
    • Do NOT fall back to SEARCH(). Instead, use protoPayload.methodName.
    • Construct the method name by guessing the service and the verb. Example: protoPayload.methodName:"compute.instances.insert".
    • Always use the colon operator (:) instead of equals (=) for methodName. The colon operator results in substring matching, which is the only feasible option when the exact API string isn't known.
    • For generic API enable/disable events, use resource.type="audited_resource".
  3. 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.* or protoPayload.* field structures when you are certain of their exact name.
    • Use the SEARCH() function to find the keyword globally within the correct resource.type.
    • Agent Prompt to User: 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.
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Overall Score

87/100

Grade

A

Excellent

Safety

88

Quality

88

Clarity

86

Completeness

85

Summary

This skill generates Logging Query Language (LQL) queries for Google Cloud Logging from natural language descriptions. It provides strict syntax rules, service-specific reference files with pre-built query templates, and guidance on resource types, operators, and query construction patterns. The agent reads reference documentation and generates raw LQL output without modification.

Static Analysis Findings

1 finding

Patterns detected by deterministic static analysis before AI scoring. Hover over any finding code for detailed information and remediation guidance.

Credential Exposure
SEC-020Direct .env File Access

Direct .env file access

references/api_reference.md.env

Detected Capabilities

file readmarkdown reference parsingstring templating with placeholders

Trigger Keywords

Phrases that MCP clients use to match this skill to user intent.

generate logging queriescloud logging querydebug cloud logslql syntaxgke audit logscompute engine logsbigquery audit logs

Risk Signals

INFO

Direct .env file access referenced in api_reference.md

references/api_reference.md (mentioned in static pre-scan)

Referenced Domains

External domains referenced in skill content, detected by static analysis.

docs.cloud.google.comwww.apache.org

Use Cases

  • Generate Cloud Logging queries from natural language requests
  • Debug issues by querying log data for specific Google Cloud services
  • Build audit log queries for compliance and security investigations
  • Filter logs by resource type, severity, and custom fields
  • Create queries for specific services like GKE, Compute Engine, or Cloud SQL without memorizing syntax

Quality Notes

  • Excellent scope definition: skill is narrowly focused on LQL query generation for Cloud Logging only—explicitly excludes SQL, Spanner, and other databases
  • Comprehensive reference architecture: 21 service-specific markdown files with pre-built query templates, syntax rules, and resource type mappings reduce ambiguity and errors
  • Clear output format rules: agent must produce raw LQL only, no conversational text, with documented use of comments for SEARCH-based fallback queries
  • Strong error handling guidance: placeholders for missing variables prevent agent from blocking, explicit fallback to SEARCH() when exact schemas are unknown
  • Well-documented limitations: pinpoints exact distinctions (instance name vs. ID, resource type accuracy, NULL handling) to prevent common mistakes
  • All supporting files present: 21 referenced query files all exist in the manifest, no missing dependencies
  • Practical examples throughout: every reference file includes concrete LQL queries with variable placeholders, reducing trial-and-error
  • Audit log handling is well-specified: methodName patterns, protoPayload structures documented in detail
Model: claude-haiku-4-5-20251001Analyzed: Jul 14, 2026

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