Copaw Ops
chujianyun/skills
CoPaw 运维助手。用于用户提到 copaw 运维、服务无响应、渠道断连、MCP 失败、模型调用失败、cron 不执行、Docker 部署、重载、重启或重置恢复时使用。优先执行状态检查与故障分流;涉及重启、重载、重置、配置修改等高影响动作时,先向用户说明再执行。
Manages Cloud Run services, jobs, and worker pools. An agent skill from google/skills.
$ npx skills add google/skills --skill cloud-run-basics -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install google/skills cloud-run-basics --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-basics .claude/skills/cloud-run-basics && 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-basics" agent skill from https://github.com/google/skills/tree/main/skills/cloud/cloud-run-basics into .claude/skills/cloud-run-basics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cloud-run-basics", 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-basicsType 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-basics -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install google/skills cloud-run-basics --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-basics .agents/skills/cloud-run-basics && 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-basics" agent skill from https://github.com/google/skills/tree/main/skills/cloud/cloud-run-basics into .agents/skills/cloud-run-basics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cloud-run-basics", 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-basics -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install google/skills cloud-run-basics --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-basics .cursor/skills/cloud-run-basics && 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-basics" agent skill from https://github.com/google/skills/tree/main/skills/cloud/cloud-run-basics into .cursor/skills/cloud-run-basics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cloud-run-basics", 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-basics--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-basics -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install google/skills cloud-run-basics --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-basics .gemini/skills/cloud-run-basics && 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-basics" agent skill from https://github.com/google/skills/tree/main/skills/cloud/cloud-run-basics into .gemini/skills/cloud-run-basics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cloud-run-basics", 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-basicsInstalls 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-basics -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-basics .github/skills/cloud-run-basics && 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-basics" agent skill from https://github.com/google/skills/tree/main/skills/cloud/cloud-run-basics into .github/skills/cloud-run-basics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cloud-run-basics", 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-basics -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-basics --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-basics .opencode/skills/cloud-run-basics && 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-basics" agent skill from https://github.com/google/skills/tree/main/skills/cloud/cloud-run-basics into .opencode/skills/cloud-run-basics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "cloud-run-basics", 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.
cloud-run-basicsManages Cloud Run services, jobs, and worker pools. An agent skill from google/skills.
Cloud Run Basics is an agent skill from google/skills, published by the product's own GitHub organization. Manages Cloud Run services, jobs, and worker pools. Use when you need to deploy applications responding to HTTP requests (services), run event-triggered or scheduled tasks (jobs), or handle always-on pull-based background processing (worker pools).
Its SKILL.md is about 4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including reference files (for example `references/cli-usage.md`, `references/client-library-usage.md` and `references/core-concepts.md`).
It sits in Productivity & Automation, covering Scheduled and recurring tasks and Containers. It works with Cloud Run. The repository describes itself as: Agent Skills for Google products and technologies. The licence is Apache-2.0.
3 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 7d97937. It shows what the files ask for, not the result of running them.
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.
Shell commands in SKILL.md call:
gcloudFrom the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
docs.cloud.google.comhub.docker.comdocs.docker.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Cloud Run Basics loads about 4k tokens when it runs, and up to ~11k if it reads all its reference files. Until then it costs about 66 tokens; SKILL.md has 1,788 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.
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.
The full file from google/skills at commit 7d97937, republished under its Apache-2.0 licence (© google). 1,788 words, ~3,968 tokens.
.claude/skills/cloud-run-basics/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.Cloud Run is a fully managed application platform for running your code, function, or container on top of Google's highly scalable infrastructure. It abstracts away infrastructure management, providing three primary resource types:
Enable the Cloud Run Admin API and Cloud Build APIs:
gcloud services enable run.googleapis.com cloudbuild.googleapis.com --quietIf you are under a domain restriction organization policy restricting unauthenticated invocations for your project, you will need to access your deployed service as described under Testing private services.
You need the following roles to deploy your Cloud Run resource:
roles/run.admin) on the projectroles/run.sourceDeveloper) on the projectroles/iam.serviceAccountUser) on the service
identityroles/logging.viewer) on the projectCloud Build automatically uses the Compute Engine default service account as the default Cloud Build service account to build your source code and Cloud Run resource, unless you override this behavior.
For Cloud Build to build your sources, grant the Cloud Build service account the
Cloud Run Builder (roles/run.builder) role on your project:
gcloud projects add-iam-policy-binding PROJECT_ID \
--member=serviceAccount:SERVICE_ACCOUNT_EMAIL_ADDRESS \
--role=roles/run.builder \
--quietReplace PROJECT_ID with your Google Cloud project ID and
SERVICE_ACCOUNT_EMAIL_ADDRESS with the email address of the Cloud Build
service account.
You can deploy your service to Cloud Run by using a container image or deploy directly from source code using a single Google Cloud CLI command.
CRITICAL RULE: Any deployed code MUST listen on 0.0.0.0 (not 127.0.0.1) and use the injected $PORT environment variable (defaults to 8080), or it will crash on boot.
Cloud Run imports your container image during deployment. Cloud Run keeps this copy of the container image as long as it is used by a serving revision. Container images are not pulled from their container repository when a new Cloud Run instance is started.
You can directly use container images stored in the Artifact Registry, or Docker Hub. Google recommends the use of Artifact Registry since Docker Hub images are cached for up to one hour.
You can use container images from other public or private registries (like JFrog Artifactory, Nexus, or GitHub Container Registry), by setting up an Artifact Registry remote repository.
You should only consider Docker Hub for deploying popular container images such as Docker Official Images or Docker Sponsored OSS images. For higher availability, Google recommends deploying these Docker Hub images using an Artifact Registry remote repository.
To deploy a container image, run the following command:
gcloud run deploy SERVICE_NAME \
--image IMAGE_URL \
--region us-central1 \
--allow-unauthenticated \
--quietReplace the following:
us-docker.pkg.dev/cloudrun/container/hello:latest. If you use Artifact
Registry, the repository REPO_NAME must already be created. The URL follows
the format of LOCATION-docker.pkg.dev/PROJECT_ID/REPO_NAME/PATH:TAG. Note
that if you don't supply the --image flag, the deploy command will attempt
to deploy from source code.There are two different ways to deploy your service from source:
Deploy from source with build (default): This option uses Google Cloud's buildpacks and Cloud Build to automatically build container images from your source code without having to install Docker on your machine or set up buildpacks or Cloud Build. By default, Cloud Run uses the default machine type provided by Cloud Build.
To deploy from source with automatic base image updates enabled, run the following command:
gcloud run deploy SERVICE_NAME --source . \
--base-image BASE_IMAGE \
--automatic-updates \
--quietCloud Run only supports automatic base images that use Google Cloud's buildpacks base images.
gcloud run deploy SERVICE_NAME --source . --quietWhen you provide a Dockerfile, Cloud Build runs it in the cloud, and
deploys the service.Deploy from source without build (Preview): This option deploys artifacts directly to Cloud Run, bypassing the Cloud Build step. This allows for rapid deployment times. To deploy from source without build, run the following command:
gcloud beta run deploy SERVICE_NAME \
--source APPLICATION_PATH \
--no-build \
--base-image=BASE_IMAGE \
--command=COMMAND \
--args=ARG \
--quietReplace the following:
us-central1-docker.pkg.dev/serverless-runtimes/google-24-full/runtimes/nodejs24.
You can also deploy a pre-compiled binary without configuring additional
language-specific runtime components using the OS only base image, such
as osonly24.For examples on deploying from source without build, see Examples of deploying from source without build.
To create a new job, run the following command:
gcloud run jobs create JOB_NAME --image IMAGE_URL OPTIONS --quietAlternatively, use the deploy command:
gcloud run jobs deploy JOB_NAME --image IMAGE_URL OPTIONS --quietReplace the following:
JOB_NAME: the name of the job you want to create. If you omit this parameter, you will be prompted for the job name when you run the command.
IMAGE_URL: a reference to the container image—for example,
us-docker.pkg.dev/cloudrun/container/job:latest.
Optionally, replace OPTIONS with any of the following flags:
--tasks: Accepts integers greater or equal to 1. Defaults to 1;
maximum is 10,000. Each task is provided the environment variables
CLOUD_RUN_TASK_INDEX with a value between 0 and the number of tasks
minus 1, along with CLOUD_RUN_TASK_COUNT, which is the number of
tasks.--max-retries: The number of times a failed task is retried. Once any
task fails beyond this limit, the entire job is marked as failed. For
example, if set to 1, a failed task will be retried once, for a total of
two attempts. The default is 3. Accepts integers from 0 to 10.--task-timeout: Accepts a duration like "2s". Defaults to 10 minutes;
maximum is 168 hours (7 days). For tasks using GPUs, the maximum
available timeout is 1 hour.--parallelism: The maximum number of tasks that can execute in
parallel. By default, tasks will be started as quickly as possible in
parallel.gcloud run jobs create
followed by gcloud run jobs execute.In addition to these preceding options, you also specify more configuration such as environment variables or memory limits.
For a full list of available options when creating a job, refer to the gcloud run jobs create
command line documentation.
Wait for the job creation to finish. You'll see a success message upon a successful completion.
To execute an existing job, run the following command:
gcloud run jobs execute JOB_NAME --quietIf you want the command to wait until the execution completes, run the following command:
gcloud run jobs execute JOB_NAME --wait --region=REGION --quietReplace the following:
europe-west1. Alternatively, set the run/region property.You can deploy a Cloud Run worker pool using container images or deploy directly from the source.
You can specify a container image with a tag (for example,
us-docker.pkg.dev/my-project/container/my-image:latest) or with an exact
digest (for example,
us-docker.pkg.dev/my-project/container/my-image@sha256:41f34ab970ee...).
You can directly use container images stored in the Artifact Registry, or Docker Hub. Google recommends the use of Artifact Registry since Docker Hub images are cached for up to one hour.
You can use container images from other public or private registries (like JFrog Artifactory, Nexus, or GitHub Container Registry), by setting up an Artifact Registry remote repository.
You should only consider Docker Hub for deploying popular container images such as Docker Official Images or Docker Sponsored OSS images. For higher availability, Google recommends deploying these Docker Hub images using an Artifact Registry remote repository.
To deploy a container image, run the following command:
gcloud run worker-pools deploy WORKER_POOL_NAME --image IMAGE_URL --quietReplace the following:
WORKER_POOL_NAME: the name of the worker pool you want to deploy to. If the worker pool does not exist yet, this command creates the worker pool during the deployment. You can omit this parameter entirely, but you will be prompted for the worker pool name if you omit it.
IMAGE_URL: a reference to the container image that contains the worker pool,
such as us-docker.pkg.dev/cloudrun/container/worker-pool:latest. Note that
if you don't supply the --image flag, the deploy command attempts to
deploy from source code.
Wait for the deployment to finish. Upon successful completion, Cloud Run displays a success message along with the revision information about the deployed worker pool.
You can deploy a new worker pool or worker pool revision to Cloud Run directly
from source code using a single gcloud CLI command, gcloud run worker-pools
deploy with the --source flag.
The deploy command defaults to source deployment if you don't supply the
--image or --source flags.
Behind the scenes, this command uses Google Cloud's buildpacks and Cloud Build to automatically build container images from your source code without having to install Docker on your machine or set up buildpacks or Cloud Build. By default, Cloud Run uses the default machine type provided by Cloud Build.
To deploy a worker pool from source, run the following command:
gcloud run worker-pools deploy WORKER_POOL_NAME --source . --quietReplace WORKER_POOL_NAME with the name you want for your worker pool.
gcloud logging read "resource.labels.service_name=SERVICE_NAME" --limit=20
to find the exact runtime error.--no-build, switch to
--source . (Buildpacks) to compile native extensions properly for Linux.Core Concepts: Services vs. Jobs vs. Worker pools, resource model, and auto-scaling behavior for services.
CLI Usage: Essential gcloud run commands for
deployment and management.
Client Libraries: Using Google Cloud client libraries to interact with Cloud Run.
MCP Usage: Using the Cloud Run remote MCP server.
Infrastructure as Code: Terraform examples for services, jobs, worker pools, and IAM bindings.
IAM & Security: Roles, service identities, and ingress/egress controls.
Networking Best Practices & Cost Optimization: Cost optimization strategies, Direct VPC egress, IP address and port exhaustion strategies, performance throughput tuning, and MTU settings.
If you need product information not found in these references, use the
Developer Knowledge MCP server search_documents tool.
© 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
SKILL.md and 7 other files (references) in skills/cloud/cloud-run-basics of google/skills.
Open the folder on GitHubat commit 7d97937
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in google/skills, which our catalogue first saw on October 7, 2026.
Cloud Run Basics 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 Basics this skillgoogle/skills | 21k | 1 repos | ~4k | Automated safety check: Pass | Apache-2.0 | |
| Copaw Opschujianyun/skills | 740 | — | ~1.3k | Automated safety check: Pass | Custom licence | |
| GitHub Actions CreatorFNOSP/FlyNarwhal | 495 | 1 repos | ~2.4k | Automated safety check: Pass | AGPL-3.0 | |
| Cron Opsczl9707/build-your-own-openclaw | 1.9k | — | ~593 | Automated safety check: Pass | MIT | |
| Devopsnicepkg/auto-company | 192 | 2 repos | ~814 | Automated safety check: Pass | MIT | |
| Wp Wpcli And OpsAutomattic/agent-skills | 211 | 2 repos | ~988 | Automated safety check: Pass | None |
chujianyun/skills
CoPaw 运维助手。用于用户提到 copaw 运维、服务无响应、渠道断连、MCP 失败、模型调用失败、cron 不执行、Docker 部署、重载、重启或重置恢复时使用。优先执行状态检查与故障分流;涉及重启、重载、重置、配置修改等高影响动作时,先向用户说明再执行。
FNOSP/FlyNarwhal
A skill your agent uses when the user wants to create, generate, or set up a GitHub Actions workflow.
czl9707/build-your-own-openclaw
Create, list, and delete scheduled cron jobs. An agent skill from czl9707/build-your-own-openclaw.
nicepkg/auto-company
Deploy to Cloudflare (Workers, R2, D1), Docker, GCP (Cloud Run, GKE), Kubernetes (kubectl, Helm).
Automattic/agent-skills
A skill your agent uses when working with WP-CLI (wp) for WordPress operations: safe search-replace, db export/import, plugin/theme/user/content management, cron, cache flushing, multisite, and…
superset-sh/superset
Turns a recurring chore into a scheduled or event-triggered Superset agent, drafting its prompt, picking a target and trigger, and reviewing the first run.
google/skills
Query Cloud Trace spans, filter by latency thresholds or error status, correlate distributed traces with Cloud Logging, and diagnose latency bottlenecks across Google Cloud services.
google/skills
Manages Google Cloud Privileged Access Manager entitlements and grants: create and edit entitlements, request temporary access, and approve or deny pending grants.
google/skills
Writes Terraform alerting policies for AI agents that emit OpenTelemetry metrics, covering reliability, cost, safety, security and quality signals on Google Cloud.
google/skills
Deploys open models or custom weights from Model Garden to Agent Platform endpoints, checks deployment status and cleans up endpoints, confirming before any change.
google/skills
Searches, manages and scaffolds skills in the Gemini Enterprise Agent Platform Skill Registry using bundled Python scripts and Google Cloud credentials.
google/skills
Designs GCP infrastructure as local Terraform, validates and scans it against best practices, then imports it to Application Design Center for deployment and troubleshooting.
Works with
Categories
Manages Cloud Run services, jobs, and worker pools. An agent skill from google/skills. Cloud Run Basics is an agent skill from google/skills, published by the product's own GitHub organization. Manages Cloud Run services, jobs, and worker pools.
Cloud Run Basics fits situations like: you need to deploy applications responding to HTTP requests (services); run event-triggered; scheduled tasks (jobs); handle always-on pull-based background processing (worker pools).
Run `npx skills add google/skills --skill cloud-run-basics -a claude-code`. Or copy the skill folder (skills/cloud/cloud-run-basics in google/skills) into .claude/skills/cloud-run-basics in your project. Claude Code loads it when a task matches its description.
Run `npx skills add google/skills --skill cloud-run-basics -a codex`. Or copy the skill folder (skills/cloud/cloud-run-basics in google/skills) into .agents/skills/cloud-run-basics in your project. Codex loads it when a task matches its description.
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-basics -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-basics, .gemini/skills/cloud-run-basics, .github/skills/cloud-run-basics and .opencode/skills/cloud-run-basics in your project.
Going by SKILL.md and its folder, Cloud Run Basics needs the command-line tools its instructions call (gcloud). Our summary lists: Docker.
SKILL.md names 3 domains. As links in the text: docs.cloud.google.com, hub.docker.com and docs.docker.com. This is read from the text; nothing was executed.
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.
Cloud Run Basics 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.
About 4k tokens (SKILL.md is roughly 16k 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 7k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Cloud Run Basics: Copaw Ops (chujianyun/skills, 740 stars), GitHub Actions Creator (FNOSP/FlyNarwhal, 495 stars), Cron Ops (czl9707/build-your-own-openclaw, 1.9k stars) and Devops (nicepkg/auto-company, 192 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
google (a GitHub organization, an official publisher) maintains it in google/skills, which has 21,032 GitHub stars. The repository holds 147 skills in this directory. The repository was last updated on October 8, 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.