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Agent skill

Gcloud Usage

by fcakyon in fcakyon/claude-codex-settings

This skill should be used when user asks about "GCloud logs", "Cloud Logging queries", "Google Cloud metrics", "GCP observability", "trace analysis", or "debugging production issues on GCP".

Apache-2.0Auto-check passedDevOps & Cloud

Install Gcloud Usage

skills CLI
$ npx skills add fcakyon/claude-codex-settings --skill gcloud-usage -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install fcakyon/claude-codex-settings gcloud-usage --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/fcakyon/claude-codex-settings.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/gcloud-tools/skills/gcloud-usage .claude/skills/gcloud-usage && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
gcloud-usage
GitHub stars
1.2k
Token cost
~871 tokens
SKILL.md length
281 words
Files
1
Skills in repo
43
Repo updated
First seen
Licence
Apache-2.0

At a glance

This skill should be used when user asks about "GCloud logs", "Cloud Logging queries", "Google Cloud metrics", "GCP observability", "trace analysis", or "debugging production issues on GCP".

  • Works in 5 steps: Start with metrics: Identify when issues… → Correlate with logs: Filter logs around… → Use traces: Follow specific requests… → …
  • Asks about GCloud logs
  • SKILL.md covers Structured Logging, Log Filtering Queries, Metrics vs Logs vs Traces and Alert Policy Design, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Gcloud Usage is an agent skill from fcakyon/claude-codex-settings. This skill should be used when user asks about "GCloud logs", "Cloud Logging queries", "Google Cloud metrics", "GCP observability", "trace analysis", or "debugging production issues on GCP".

Its SKILL.md is about 870 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in DevOps & Cloud, covering Observability and Debugging. It works with Google Cloud. The repository describes itself as: Battle-tested Claude Code, OpenAI Codex, Cursor configs, plugins, hooks and agents with Kimi, MiniMax and GLM API support. The licence is Apache-2.0.

When your agent uses it

  • Asks about GCloud logs
  • Cloud Logging queries
  • Google Cloud metrics
  • GCP observability

Example prompts

  • “GCloud logs”
  • “Cloud Logging queries”
  • “Google Cloud metrics”
  • “/gcloud-usage”

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Start with metrics: Identify when issues started
  2. Correlate with logs: Filter logs around problem time
  3. Use traces: Follow specific requests across services
  4. Check resource logs: Look for infrastructure issues
  5. Compare baselines: Check against known-good periods

What it can do on your machine

Read from SKILL.md and the folder at commit a035b4e. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are json).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Gcloud Usage loads about 871 tokens when it runs. Until then it costs about 51 tokens; SKILL.md has 281 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~51
When it runs · the whole SKILL.md, loaded when a task matches
~871

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from fcakyon/claude-codex-settings at commit a035b4e, republished under its Apache-2.0 licence (© fcakyon). 281 words, ~871 tokens.

Download SKILL.mdSave it as .claude/skills/gcloud-usage/SKILL.md (or your agent's skills folder).
name
gcloud-usage
description
This skill should be used when user asks about "GCloud logs", "Cloud Logging queries", "Google Cloud metrics", "GCP observability", "trace analysis", or "debugging production issues on GCP".

GCP Observability Best Practices

Structured Logging

JSON Log Format

Use structured JSON logging for better queryability:

json
{
  "severity": "ERROR",
  "message": "Payment failed",
  "httpRequest": { "requestMethod": "POST", "requestUrl": "/api/payment" },
  "labels": { "user_id": "123", "transaction_id": "abc" },
  "timestamp": "2025-01-15T10:30:00Z"
}
Severity Levels

Use appropriate severity for filtering:

  • DEBUG: Detailed diagnostic info
  • INFO: Normal operations, milestones
  • NOTICE: Normal but significant events
  • WARNING: Potential issues, degraded performance
  • ERROR: Failures that don't stop the service
  • CRITICAL: Failures requiring immediate action
  • ALERT: Person must take action immediately
  • EMERGENCY: System is unusable

Log Filtering Queries

Common Filters
# By severity
severity >= WARNING

# By resource
resource.type="cloud_run_revision"
resource.labels.service_name="my-service"

# By time
timestamp >= "2025-01-15T00:00:00Z"

# By text content
textPayload =~ "error.*timeout"

# By JSON field
jsonPayload.user_id = "123"

# Combined
severity >= ERROR AND resource.labels.service_name="api"
Advanced Queries
# Regex matching
textPayload =~ "status=[45][0-9]{2}"

# Substring search
textPayload : "connection refused"

# Multiple values
severity = (ERROR OR CRITICAL)

Metrics vs Logs vs Traces

When to Use Each

Metrics: Aggregated numeric data over time

  • Request counts, latency percentiles
  • Resource utilization (CPU, memory)
  • Business KPIs (orders/minute)

Logs: Detailed event records

  • Error details and stack traces
  • Audit trails
  • Debugging specific requests

Traces: Request flow across services

  • Latency breakdown by service
  • Identifying bottlenecks
  • Distributed system debugging

Alert Policy Design

Alert Best Practices
  • Avoid alert fatigue: Only alert on actionable issues
  • Use multi-condition alerts: Reduce noise from transient spikes
  • Set appropriate windows: 5-15 min for most metrics
  • Include runbook links: Help responders act quickly
Common Alert Patterns

Error rate:

  • Condition: Error rate > 1% for 5 minutes
  • Good for: Service health monitoring

Latency:

  • Condition: P99 latency > 2s for 10 minutes
  • Good for: Performance degradation detection

Resource exhaustion:

  • Condition: Memory > 90% for 5 minutes
  • Good for: Capacity planning triggers

Cost Optimization

Reducing Log Costs
  • Exclusion filters: Drop verbose logs at ingestion
  • Sampling: Log only percentage of high-volume events
  • Shorter retention: Reduce default 30-day retention
  • Downgrade logs: Route to cheaper storage buckets
Exclusion Filter Examples
# Exclude health checks
resource.type="cloud_run_revision" AND httpRequest.requestUrl="/health"

# Exclude debug logs in production
severity = DEBUG

Debugging Workflow

  1. Start with metrics: Identify when issues started
  2. Correlate with logs: Filter logs around problem time
  3. Use traces: Follow specific requests across services
  4. Check resource logs: Look for infrastructure issues
  5. Compare baselines: Check against known-good periods

© fcakyon, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in plugins/gcloud-tools/skills/gcloud-usage of fcakyon/claude-codex-settings.

Open the folder on GitHubat commit a035b4e

Compare with similar skills

Gcloud Usage next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Gcloud Usage compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Gcloud Usage this skillfcakyon/claude-codex-settings1.2k—~871Automated safety check: PassApache-2.0
Motel Debugkitlangton/motel298—~2.2kAutomated safety check: PassMIT
Codex Session Debuggingweave-os/router5.6k—~4.5kAutomated safety check: WarnApache-2.0
Log Aggregationaspectrr/deer405—~1.4kAutomated safety check: PassMIT
Dspy Debugging ObservabilityOmidZamani/dspy-skills1241 repos~2.1kAutomated safety check: WarnMIT
Axiom SRE Investigatoropenclaw/clawhub9.5k—~7.1kAutomated safety check: PassMIT

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Works with

Categories

Questions about Gcloud Usage

What does Gcloud Usage do?

This skill should be used when user asks about "GCloud logs", "Cloud Logging queries", "Google Cloud metrics", "GCP observability", "trace analysis", or "debugging production issues on GCP". Gcloud Usage is an agent skill from fcakyon/claude-codex-settings. This skill should be used when user asks about "GCloud logs", "Cloud Logging queries", "Google Cloud metrics", "GCP observability", "trace analysis", or "debugging production issues on GCP".

When should I use Gcloud Usage?

Gcloud Usage fits situations like: asks about GCloud logs; cloud Logging queries; google Cloud metrics; GCP observability.

How do I install Gcloud Usage in Claude Code?

Run `npx skills add fcakyon/claude-codex-settings --skill gcloud-usage -a claude-code`. Or copy the skill folder (plugins/gcloud-tools/skills/gcloud-usage in fcakyon/claude-codex-settings) into .claude/skills/gcloud-usage in your project. Claude Code loads it when a task matches its description.

How do I install Gcloud Usage in Codex?

Run `npx skills add fcakyon/claude-codex-settings --skill gcloud-usage -a codex`. Or copy the skill folder (plugins/gcloud-tools/skills/gcloud-usage in fcakyon/claude-codex-settings) into .agents/skills/gcloud-usage in your project. Codex loads it when a task matches its description.

Can I use Gcloud Usage in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add fcakyon/claude-codex-settings --skill gcloud-usage -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/gcloud-usage, .gemini/skills/gcloud-usage, .github/skills/gcloud-usage and .opencode/skills/gcloud-usage in your project.

What does Gcloud Usage need to run?

SKILL.md names no scripts, command-line tools or credentials: Gcloud Usage is instructions for the agent only.

Does Gcloud Usage access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Gcloud Usage safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Gcloud Usage use?

Gcloud Usage is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Gcloud Usage use?

About 871 tokens (SKILL.md is roughly 3.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Gcloud Usage?

Skills that share tags, products or a category with Gcloud Usage: Motel Debug (kitlangton/motel, 298 stars), Codex Session Debugging (weave-os/router, 5.6k stars), Log Aggregation (aspectrr/deer, 405 stars) and Dspy Debugging Observability (OmidZamani/dspy-skills, 124 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Gcloud Usage?

fcakyon (a GitHub user) maintains it in fcakyon/claude-codex-settings, which has 1,163 GitHub stars. The repository holds 43 skills in this directory. The repository was last updated on October 6, 2026.

Source: fcakyon/claude-codex-settings on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.