Deploying
GoogleCloudPlatform/race-condition
Guides deployment of Race Condition to a GCP project. An agent skill from GoogleCloudPlatform/race-condition.
Configures best-practice, high-signal alerting policies for Google Cloud Run resources (services, jobs, and worker pools) based on seasoned SRE practices.
Install Cloud Run Alert Configuration
$ npx skills add google/skills --skill cloud-run-alert-configuration -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install google/skills cloud-run-alert-configuration --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/cloud/cloud-run-alert-configuration .claude/skills/cloud-run-alert-configuration && rm -rf skills-srcUse ~/.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/
Install the "cloud-run-alert-configuration" agent skill from https://github.com/google/skills/tree/main/skills/cloud/cloud-run-alert-configuration into .claude/skills/cloud-run-alert-configuration/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cloud-run-alert-configuration", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/google/skills/tree/main/skills/cloud/cloud-run-alert-configurationType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add google/skills --skill cloud-run-alert-configuration -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install google/skills cloud-run-alert-configuration --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/cloud/cloud-run-alert-configuration .agents/skills/cloud-run-alert-configuration && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "cloud-run-alert-configuration" agent skill from https://github.com/google/skills/tree/main/skills/cloud/cloud-run-alert-configuration into .agents/skills/cloud-run-alert-configuration/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cloud-run-alert-configuration", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add google/skills --skill cloud-run-alert-configuration -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install google/skills cloud-run-alert-configuration --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/cloud/cloud-run-alert-configuration .cursor/skills/cloud-run-alert-configuration && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "cloud-run-alert-configuration" agent skill from https://github.com/google/skills/tree/main/skills/cloud/cloud-run-alert-configuration into .cursor/skills/cloud-run-alert-configuration/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cloud-run-alert-configuration", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/google/skills.git --path skills/cloud/cloud-run-alert-configuration--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add google/skills --skill cloud-run-alert-configuration -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install google/skills cloud-run-alert-configuration --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/cloud/cloud-run-alert-configuration .gemini/skills/cloud-run-alert-configuration && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "cloud-run-alert-configuration" agent skill from https://github.com/google/skills/tree/main/skills/cloud/cloud-run-alert-configuration into .gemini/skills/cloud-run-alert-configuration/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cloud-run-alert-configuration", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install google/skills cloud-run-alert-configurationInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add google/skills --skill cloud-run-alert-configuration -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/cloud/cloud-run-alert-configuration .github/skills/cloud-run-alert-configuration && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "cloud-run-alert-configuration" agent skill from https://github.com/google/skills/tree/main/skills/cloud/cloud-run-alert-configuration into .github/skills/cloud-run-alert-configuration/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cloud-run-alert-configuration", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add google/skills --skill cloud-run-alert-configuration -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install google/skills cloud-run-alert-configuration --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/google/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/cloud/cloud-run-alert-configuration .opencode/skills/cloud-run-alert-configuration && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "cloud-run-alert-configuration" agent skill from https://github.com/google/skills/tree/main/skills/cloud/cloud-run-alert-configuration into .opencode/skills/cloud-run-alert-configuration/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cloud-run-alert-configuration", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
cloud-run-alert-configuration- GitHub stars
- 21k
- Token cost
- ~1.8k tokens
- SKILL.md length
- 658 words
- Files
- 4 (incl. references)
- Skills in repo
- 145
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Configures best-practice, high-signal alerting policies for Google Cloud Run resources (services, jobs, and worker pools) based on seasoned SRE practices.
- Works in 3 steps: Discovery & Target Identification → Configure Alerts → Terraform Generation & Review
- Deploying Terraform PromQL alerting policies to monitor Cloud Run error rates (4xx/5xx)
- SKILL.md covers CRITICAL RULES, WORKFLOW STEPS and Additional Resources
- Calls gcloud
What it does
Cloud Run Alert Configuration is an agent skill from google/skills, published by the product's own GitHub organization. Configures best-practice, high-signal alerting policies for Google Cloud Run resources (services, jobs, and worker pools) based on seasoned SRE practices. Use when analyzing, recommending, writing, or deploying Terraform PromQL alerting policies to monitor Cloud Run error rates (4xx/5xx), request latency, container instance saturation (warning/critical), container CPU/memory utilization and allocation, billable instance time, job execution status, and worker pool queue backlog. Don't use for GKE workloads (use…
Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `references/jobs.md`, `references/services.md` and `references/worker_pools.md`).
It sits in DevOps & Cloud, covering Infrastructure as code and Site reliability engineering. It works with Cloud Run, Terraform, Google Kubernetes Engine and Prometheus. The repository describes itself as: Agent Skills for Google products and technologies. The licence is Apache-2.0.
When your agent uses it
- Deploying Terraform PromQL alerting policies to monitor Cloud Run error rates (4xx/5xx)
- Request latency
- Container instance saturation (warning/critical)
- Container CPU/memory utilization and allocation
Example prompts
- “Use the cloud-run-alert-configuration skill to configure best-practice, high-signal alerting policies for Google Cloud Run resources (services…”
- “/cloud-run-alert-configuration”
Requirements
- Pre-approved tools (allowed-tools): terraform, gcloud
Workflow steps
3 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 8a1ac05. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
terraformgcloud
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
gcloud
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
docs.cloud.google.comsre.google
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
Cloud Run Alert Configuration loads about 1.8k tokens when it runs, and up to ~13k if it reads all its reference files. Until then it costs about 148 tokens; SKILL.md has 658 words of instructions outside code blocks.
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 google/skills at commit 8a1ac05, republished under its Apache-2.0 licence (© google). 658 words, ~1,751 tokens.
Download SKILL.mdSave it as
.claude/skills/cloud-run-alert-configuration/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- cloud-run-alert-configuration
- description
- Configures best-practice, high-signal alerting policies for Google Cloud Run resources (services, jobs, and worker pools) based on seasoned SRE practices. Use when analyzing, recommending, writing, or deploying Terraform PromQL alerting policies to monitor Cloud Run error rates (4xx/5xx), request latency, container instance saturation (warning/critical), container CPU/memory utilization and allocation, billable instance time, job execution status, and worker pool queue backlog. Don't use for GKE workloads (use gke-alert-configuration) or Compute Engine VMs.
- allowed-tools
- terraform, gcloud
- metadata.version
- 1.0.0
- metadata.category
- Serverless
Cloud Run Alert Configuration
Production-grade observability for Google Cloud Run using Terraform and PromQL (Cloud Monitoring). Grounded in SRE practices, this skill focuses strictly on actionable user impact and scaling bounds.
CRITICAL RULES
- Prompt-First Fast Path (Skip Discovery When Named):
- If the user prompt explicitly specifies the target Cloud Run service, job, or worker pool name (e.g.,
'video-encoder','nightly-reconciliation','web-frontend','catalog-service','api-gateway','order-processor'), SKIP all workspace.tffile scanning (find_by_name,code_search,list_dir) andgcloudCLI discovery commands entirely. - Do NOT run
gcloud,terraform, or file search tools when the target name is already provided in the prompt. Instead, parameterize the project ID (variable "scoping_project_id" { default = "my-gcp-project" }) and target resource name in Terraform variables and proceed immediately to Step 2 (Configure Alerts).
- If the user prompt explicitly specifies the target Cloud Run service, job, or worker pool name (e.g.,
- Autonomous Discovery (Only When Target Name is Omitted):
- Never Scan Root Monorepo or Unbounded Directories: Never run
find_by_nameorlsacross root workspace directories. - Config First: Only if the prompt omits the resource name, check
.tffiles in the immediate working directory forgoogle_cloud_run_v2_service,google_cloud_run_service, orgoogle_cloud_run_v2_job. - CLI Second (Graceful Fallback): Only if unconfigured in prompt or local
.tffiles, attemptgcloud config get-value projectandgcloud run services list. If anygcloudcommand fails (e.g., auth or metadata errors) orterraformis missing, immediately stop running CLI commands and output parameterized HCL using explicit variable defaults.
- Never Scan Root Monorepo or Unbounded Directories: Never run
- Workload Routing: Always classify the workload target and follow its
specific reference guide:
- For HTTP Services follow services.md
- For Cloud Run Jobs follow jobs.md
- For Worker Pools follow worker_pools.md
- Explicit Defaults & User Overrides:
- Always use explicit defaults for all constants specified in the target workload's reference file (SLO targets, latency thresholds, SLAs, saturation ceilings, rate guards).
- State the defaults being applied in the final summary output and clearly notify the user that any default constant can be customized or overridden via Terraform variables or prompt input.
- Metric Scope Centralization: Parameterize
project = var.scoping_project_idin all Terraformgoogle_monitoring_alert_policyresources so the policy can target either a single project or a centralized Cloud Monitoring Metrics Scope. - PromQL
duration(Retest Window) Rules:- Lookbacks $\le$ 25h: Set
duration = "300s"(5m buffer) to absorb transient blips and scale-up lag (except immediate job failure alerts which useduration = "0s"). - Lookbacks $> 25$h (e.g. 3d/7d Slow Burn): Omit
durationentirely (or set to0s). Cloud Monitoring rejects PromQL queries withdurationset on lookbacks >25h (INVALID_ARGUMENT).
- Lookbacks $\le$ 25h: Set
- Terraform Standards & Mandatory Labels:
- Output clean, complete
.tfconfigurations usinggoogle_monitoring_alert_policyandcondition_prometheus_query_languagedirectly in your response. - Mandatory User Labels: Every
google_monitoring_alert_policyresource MUST include auser_labelsblock containing:hcl user_labels = { created-with-google-skill = "cloud-run-alert-configuration" } - Include
alert_strategy { auto_close = "604800s" }and parameterizenotification_channels = var.notification_channels.
- Output clean, complete
Show full SKILL.md (232 more words)Show less
WORKFLOW STEPS
1. Discovery & Target Identification
- Fast Path (Target Named in Prompt): If the user prompt names the target Cloud Run service, job, or worker pool, skip all discovery commands and file searches and proceed directly to Step 2.
- Discovery Fallback (Target Unnamed): Only if no resource name is provided in the prompt, check local
.tffiles or rungcloudto identify the target workload type and name. Ifgcloudauth fails, fall back immediately to default Terraform variables (var.scoping_project_id).
2. Configure Alerts
- Route to the corresponding guide to generate the alert policies:
- HTTP Services: Open services.md. Apply the requested alerting policy or standard suite covering availability SLOs (5xx), request latency (P95/P99), client errors (4xx), container instance saturation, container CPU/memory utilization, traffic anomalies (drop/surge), and billable instance time.
- Batch Jobs: Open jobs.md. Apply immediate job
execution failure alerts (
duration = "0s"). - Worker Pools: Open worker_pools.md. Apply the 4-policy standard suite (Task Success SLO Fast/Slow Burn, Backlog ETD, Message Age SLA).
3. Terraform Generation & Review
- Provide the complete HCL configuration in your response with explicitly parameterized defaults and the mandatory
user_labelsblock (created-with-google-skill = "cloud-run-alert-configuration"). - State the applied defaults and remind the user of their ability to override any constant.
- Provide a clear plain-English breakdown of the PromQL logic and triggering thresholds.
Additional Resources
© google, 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
SKILL.md and 3 other files (references) in skills/cloud/cloud-run-alert-configuration of google/skills.
- SKILL.md
- references/jobs.md
- references/services.md
- references/worker_pools.md
Open the folder on GitHubat commit 8a1ac05
Compare with similar skills
Cloud Run Alert Configuration 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Cloud Run Alert Configuration this skillgoogle/skills | 21k | — | ~1.8k | Automated safety check: Pass | Apache-2.0 | |
| DeployingGoogleCloudPlatform/race-condition | 234 | — | ~3k | Automated safety check: Pass | Custom licence | |
| Dd GCP Integrationdatadog-labs/agent-skills | 177 | — | ~8k | Automated safety check: Notes | MIT | |
| Expert OpsReJeCtAll/ExpertTeam-Codex | 113 | — | ~625 | Automated safety check: Pass | MIT | |
| GCP To AWSaws/agent-toolkit-for-aws | 2.8k | — | ~14k | Automated safety check: Pass | Apache-2.0 | |
| Senior DevOps Toolkitmaslennikov-ig/claude-code-orchestrator-kit | 259 | 6 repos | ~1.1k | Automated safety check: Notes | Custom licence |
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Related
Categories
Questions about Cloud Run Alert Configuration
What does Cloud Run Alert Configuration do?
Configures best-practice, high-signal alerting policies for Google Cloud Run resources (services, jobs, and worker pools) based on seasoned SRE practices. Cloud Run Alert Configuration is an agent skill from google/skills, published by the product's own GitHub organization. Configures best-practice, high-signal alerting policies for Google Cloud Run resources (services, jobs, and worker pools) based on seasoned SRE practices.
When should I use Cloud Run Alert Configuration?
Cloud Run Alert Configuration fits situations like: deploying Terraform PromQL alerting policies to monitor Cloud Run error rates (4xx/5xx); request latency; container instance saturation (warning/critical); container CPU/memory utilization and allocation.
How do I install Cloud Run Alert Configuration in Claude Code?
Run `npx skills add google/skills --skill cloud-run-alert-configuration -a claude-code`. Or copy the skill folder (skills/cloud/cloud-run-alert-configuration in google/skills) into .claude/skills/cloud-run-alert-configuration in your project. Claude Code loads it when a task matches its description.
How do I install Cloud Run Alert Configuration in Codex?
Run `npx skills add google/skills --skill cloud-run-alert-configuration -a codex`. Or copy the skill folder (skills/cloud/cloud-run-alert-configuration in google/skills) into .agents/skills/cloud-run-alert-configuration in your project. Codex loads it when a task matches its description.
Can I use Cloud Run Alert Configuration 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 google/skills --skill cloud-run-alert-configuration -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cloud-run-alert-configuration, .gemini/skills/cloud-run-alert-configuration, .github/skills/cloud-run-alert-configuration and .opencode/skills/cloud-run-alert-configuration in your project.
What does Cloud Run Alert Configuration need to run?
Going by SKILL.md and its folder, Cloud Run Alert Configuration needs the command-line tools its instructions call (gcloud). Its frontmatter pre-approves these tools: terraform, gcloud.
Does Cloud Run Alert Configuration access the network?
SKILL.md names 2 domains. As links in the text: docs.cloud.google.com and sre.google. This is read from the text; nothing was executed.
Is Cloud Run Alert Configuration 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 Cloud Run Alert Configuration use?
Cloud Run Alert Configuration 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 Cloud Run Alert Configuration use?
About 1.8k tokens (SKILL.md is roughly 7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 11k tokens, read only when the agent opens those files.
What are the alternatives to Cloud Run Alert Configuration?
Skills that share tags, products or a category with Cloud Run Alert Configuration: Deploying (GoogleCloudPlatform/race-condition, 234 stars), Dd GCP Integration (datadog-labs/agent-skills, 177 stars), Expert Ops (ReJeCtAll/ExpertTeam-Codex, 113 stars) and GCP To AWS (aws/agent-toolkit-for-aws, 2.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Cloud Run Alert Configuration?
google (a GitHub organization, an official publisher) maintains it in google/skills, which has 20,994 GitHub stars. The repository holds 145 skills in this directory. The repository was last updated on October 6, 2026.
Source: google/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.