Agent skill

GCP Cloud Functions

by sickn33 in sickn33/agentic-awesome-skills

Deploy serverless functions on Google Cloud Functions. An agent skill from sickn33/agentic-awesome-skills.

MITAuto-check passedBackend & APIs

Install GCP Cloud Functions

skills CLI
$ npx skills add sickn33/agentic-awesome-skills --skill gcp-cloud-functions -a claude-code

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

GitHub CLI
$ gh skill install sickn33/agentic-awesome-skills gcp-cloud-functions --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/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/gcp-cloud-functions .claude/skills/gcp-cloud-functions && 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
gcp-cloud-functions
GitHub stars
47k
Used in
2 other repos
Token cost
~2.3k tokens
SKILL.md length
314 words
Files
1
Skills in repo
1,493
Repo updated
First seen
Licence
MIT

At a glance

Deploy serverless functions on Google Cloud Functions. An agent skill from sickn33/agentic-awesome-skills.

  • Manage deployments
  • SKILL.md covers When to Use, Prerequisites, Gen1 vs Gen2 Comparison and Deploy an HTTP Function (Gen2), plus 10 more sections
  • Calls gcloud
  • Implementing serverless workloads on GCP

What it does

GCP Cloud Functions is an agent skill from sickn33/agentic-awesome-skills. Deploy serverless functions on Google Cloud Functions. Configure triggers and manage deployments. Use when implementing serverless workloads on GCP.

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Requires the relevant OS/platform tooling and privileged access where noted. Docs-only; helper scripts and templates not bundled.

It sits in Backend & APIs, covering Serverless and Deployment. It works with Google Cloud and Cloud Run. The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is MIT.

When your agent uses it

  • Manage deployments
  • Implementing serverless workloads on GCP

Example prompts

  • “/gcp-cloud-functions”

Requirements

  • Python 3
  • Node.js
  • Compatibility (from SKILL.md): Requires the relevant OS/platform tooling and privileged access where noted. Docs-only; helper scripts and templates not bundled.

What it can do on your machine

Read from SKILL.md and the folder at commit 680176d. 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

    Shell commands in SKILL.md call:

    • gcloud

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

  • Network

    No URLs in SKILL.md. Its commands use gcloud, which can reach the network depending on how they are called.

    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.

  • Compatibility

    Requires the relevant OS/platform tooling and privileged access where noted. Docs-only; helper scripts and templates not bundled.

    From compatibility in the SKILL.md frontmatter.

Context cost

GCP Cloud Functions loads about 2.3k tokens when it runs. Until then it costs about 42 tokens; SKILL.md has 314 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~42
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k

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 sickn33/agentic-awesome-skills at commit 680176d, republished under its MIT licence (© sickn33). 314 words, ~2,325 tokens.

Download SKILL.mdSave it as .claude/skills/gcp-cloud-functions/SKILL.md (or your agent's skills folder).
name
gcp-cloud-functions
description
Deploy serverless functions on Google Cloud Functions. Configure triggers and manage deployments. Use when implementing serverless workloads on GCP.
compatibility
Requires the relevant OS/platform tooling and privileged access where noted. Docs-only; helper scripts and templates not bundled.
category
devops
risk
critical
source
https://github.com/BagelHole/DevOps-Security-Agent-Skills
source_repo
BagelHole/DevOps-Security-Agent-Skills
source_type
community
date_added
2026-09-20
license
MIT
license_source
https://github.com/BagelHole/DevOps-Security-Agent-Skills/blob/main/LICENSE
metadata.author
devops-skills
metadata.version
1.0

GCP Cloud Functions

Build and deploy event-driven serverless applications with Google Cloud Functions (Gen1 and Gen2).

When to Use

  • Processing webhooks, API endpoints, or lightweight HTTP backends
  • Reacting to events from Pub/Sub, Cloud Storage, Firestore, or Eventarc
  • Running scheduled tasks (cron) without maintaining a server
  • Building data-processing pipelines triggered by file uploads
  • Prototyping microservices before committing to Cloud Run or GKE

Prerequisites

  • Google Cloud SDK (gcloud) installed and authenticated
  • APIs enabled: Cloud Functions, Cloud Build, Artifact Registry, Cloud Run (Gen2)
  • IAM role roles/cloudfunctions.developer (or roles/run.developer for Gen2)
bash
gcloud services enable cloudfunctions.googleapis.com cloudbuild.googleapis.com \
  artifactregistry.googleapis.com run.googleapis.com eventarc.googleapis.com

Gen1 vs Gen2 Comparison

FeatureGen1Gen2 (recommended)
RuntimeCloud Functions infraBuilt on Cloud Run
Max timeout9 minutes60 minutes
Max memory8 GB32 GB
Concurrency1 request/instanceUp to 1000/instance
Traffic splittingNoYes
Eventarc triggersNoYes

Deploy an HTTP Function (Gen2)

bash
# Python HTTP function
gcloud functions deploy hello-http \
  --gen2 --region=us-central1 --runtime=python312 \
  --trigger-http --allow-unauthenticated \
  --entry-point=hello_http \
  --memory=256Mi --timeout=60s \
  --min-instances=0 --max-instances=100 \
  --set-env-vars=APP_ENV=production --source=.

# Node.js HTTP function
gcloud functions deploy hello-node \
  --gen2 --region=us-central1 --runtime=nodejs20 \
  --trigger-http --allow-unauthenticated \
  --entry-point=helloNode --memory=256Mi --source=.

Deploy a Pub/Sub Triggered Function

bash
gcloud pubsub topics create order-events

gcloud functions deploy process-order \
  --gen2 --region=us-central1 --runtime=python312 \
  --trigger-topic=order-events \
  --entry-point=process_order \
  --memory=512Mi --timeout=120s --retry \
  --service-account=order-processor@${PROJECT_ID}.iam.gserviceaccount.com \
  --source=.

Deploy a Cloud Storage Triggered Function

bash
gcloud functions deploy process-upload \
  --gen2 --region=us-central1 --runtime=python312 \
  --trigger-event-filters="type=google.cloud.storage.object.v1.finalized" \
  --trigger-event-filters="bucket=my-upload-bucket" \
  --entry-point=process_upload \
  --memory=1Gi --timeout=300s --source=.

Deploy a Scheduled Function

bash
gcloud functions deploy daily-cleanup \
  --gen2 --region=us-central1 --runtime=python312 \
  --trigger-http --no-allow-unauthenticated \
  --entry-point=daily_cleanup --source=.

gcloud scheduler jobs create http daily-cleanup-job \
  --schedule="0 2 * * *" \
  --uri="https://us-central1-${PROJECT_ID}.cloudfunctions.net/daily-cleanup" \
  --http-method=POST \
  --oidc-service-account-email=scheduler-sa@${PROJECT_ID}.iam.gserviceaccount.com \
  --location=us-central1

Python Function Examples

python
# main.py
import functions_framework
import base64, json
from flask import jsonify
from google.cloud import firestore

@functions_framework.http
def hello_http(request):
    """HTTP Cloud Function."""
    name = request.args.get("name", "World")
    return jsonify({"message": f"Hello, {name}!", "status": "ok"}), 200

@functions_framework.cloud_event
def process_order(cloud_event):
    """Triggered by a Pub/Sub message."""
    data = base64.b64decode(cloud_event.data["message"]["data"]).decode("utf-8")
    order = json.loads(data)
    db = firestore.Client()
    db.collection("orders").document(order["id"]).set({
        "status": "processing", "items": order["items"], "total": order["total"],
    })

@functions_framework.cloud_event
def process_upload(cloud_event):
    """Triggered when a file is uploaded to Cloud Storage."""
    data = cloud_event.data
    bucket_name, file_name = data["bucket"], data["name"]
    if not file_name.lower().endswith((".png", ".jpg", ".jpeg")):
        return
    from google.cloud import vision
    client = vision.ImageAnnotatorClient()
    image = vision.Image(source=vision.ImageSource(
        gcs_image_uri=f"gs://{bucket_name}/{file_name}"))
    labels = [l.description for l in client.label_detection(image=image).label_annotations]
    print(f"Labels for {file_name}: {labels}")
# requirements.txt
functions-framework==3.*
google-cloud-firestore==2.*
google-cloud-storage==2.*
google-cloud-vision==3.*
flask>=2.0

Node.js Function Examples

javascript
// index.js
const functions = require("@google-cloud/functions-framework");

functions.http("helloNode", (req, res) => {
  const name = req.query.name || "World";
  res.json({ message: `Hello, ${name}!`, status: "ok" });
});

functions.cloudEvent("processMessage", (cloudEvent) => {
  const data = Buffer.from(cloudEvent.data.message.data, "base64").toString();
  console.log(`Processing: ${JSON.parse(data)}`);
});

Managing Deployed Functions

bash
gcloud functions list --gen2 --region=us-central1
gcloud functions describe hello-http --gen2 --region=us-central1
gcloud functions logs read hello-http --gen2 --region=us-central1 --limit=50
gcloud functions delete hello-http --gen2 --region=us-central1 --quiet

# Update env vars without redeploying code
gcloud functions deploy hello-http --gen2 --region=us-central1 \
  --update-env-vars=APP_ENV=staging

# Test locally before deploying
functions-framework --target=hello_http --port=8080

Terraform Configuration

hcl
resource "google_cloudfunctions2_function" "api" {
  name     = "hello-http"
  location = "us-central1"

  build_config {
    runtime     = "python312"
    entry_point = "hello_http"
    source {
      storage_source {
        bucket = google_storage_bucket.source.name
        object = google_storage_bucket_object.source.name
      }
    }
  }

  service_config {
    min_instance_count    = 0
    max_instance_count    = 100
    available_memory      = "256Mi"
    timeout_seconds       = 60
    service_account_email = google_service_account.fn.email
    environment_variables = { APP_ENV = "production" }
  }
}

resource "google_cloud_run_service_iam_member" "invoker" {
  location = google_cloudfunctions2_function.api.location
  service  = google_cloudfunctions2_function.api.name
  role     = "roles/run.invoker"
  member   = "allUsers"
}

resource "google_cloudfunctions2_function" "processor" {
  name     = "process-order"
  location = "us-central1"

  build_config {
    runtime     = "python312"
    entry_point = "process_order"
    source {
      storage_source {
        bucket = google_storage_bucket.source.name
        object = google_storage_bucket_object.source.name
      }
    }
  }

  service_config {
    max_instance_count    = 50
    available_memory      = "512Mi"
    timeout_seconds       = 120
    service_account_email = google_service_account.fn.email
  }

  event_trigger {
    trigger_region = "us-central1"
    event_type     = "google.cloud.pubsub.topic.v1.messagePublished"
    pubsub_topic   = google_pubsub_topic.orders.id
    retry_policy   = "RETRY_POLICY_RETRY"
  }
}

Troubleshooting

SymptomCauseFix
PERMISSION_DENIED on deployMissing Cloud Build or Artifact Registry permsGrant roles/cloudbuild.builds.builder to Cloud Build SA
Function deploys but returns 403Missing roles/run.invoker for Gen2Add --allow-unauthenticated or grant invoker role
Cold start latency > 5sLarge dependencies or no min instancesSet --min-instances=1; reduce deps; use lazy imports
Pub/Sub messages redeliveredFunction errors or times outIncrease --timeout; fix error handling; add dead-letter topic
Build failed during deploySyntax error or missing dependencyCheck gcloud builds log; verify requirements.txt
Cannot connect to VPC resourceFunction not on VPC connectorAdd --vpc-connector=my-connector to deploy
  • gcp-networking - VPC connectors for accessing private resources from functions
  • gcp-cloud-sql - Connecting Cloud Functions to managed databases
  • terraform-gcp - Deploy Cloud Functions with Infrastructure as Code
  • gcp-gke - When workloads outgrow serverless and need Kubernetes

Limitations

  • Infrastructure commands can disrupt services: confirm target host/scope and have backups/snapshots before mutating state.
  • Docs-only import: upstream scripts and templates not bundled.

© sickn33, MIT. 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 skills/gcp-cloud-functions of sickn33/agentic-awesome-skills.

Open the folder on GitHubat commit 680176d

Used in 2 other repositories

We found 6 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

GCP Cloud Functions 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.

GCP Cloud Functions compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
GCP Cloud Functions this skillsickn33/agentic-awesome-skills47k2 repos~2.3kAutomated safety check: PassMIT
GCP Cloud Rundavila7/claude-code-templates32k7 repos~1.7kAutomated safety check: PassMIT
Google Cloud Solution N Tier Serverless Web Appgoogle/skills21k—~5.5kAutomated safety check: PassApache-2.0
Deploying On GCPancoleman/ai-design-components526—~3.9kAutomated safety check: PassMIT
Apollo Deploy Integrationjeremylongshore/tons-of-skills-marketplace2.8k—~1.8kAutomated safety check: PassMIT
Retail Product Search Agentgoogle/adk-recipes10k—~3kAutomated safety check: PassApache-2.0

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Categories

Questions about GCP Cloud Functions

What does GCP Cloud Functions do?

Deploy serverless functions on Google Cloud Functions. An agent skill from sickn33/agentic-awesome-skills. GCP Cloud Functions is an agent skill from sickn33/agentic-awesome-skills. Deploy serverless functions on Google Cloud Functions.

When should I use GCP Cloud Functions?

GCP Cloud Functions fits situations like: manage deployments; implementing serverless workloads on GCP.

How do I install GCP Cloud Functions in Claude Code?

Run `npx skills add sickn33/agentic-awesome-skills --skill gcp-cloud-functions -a claude-code`. Or copy the skill folder (skills/gcp-cloud-functions in sickn33/agentic-awesome-skills) into .claude/skills/gcp-cloud-functions in your project. Claude Code loads it when a task matches its description.

How do I install GCP Cloud Functions in Codex?

Run `npx skills add sickn33/agentic-awesome-skills --skill gcp-cloud-functions -a codex`. Or copy the skill folder (skills/gcp-cloud-functions in sickn33/agentic-awesome-skills) into .agents/skills/gcp-cloud-functions in your project. Codex loads it when a task matches its description.

Can I use GCP Cloud Functions 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 sickn33/agentic-awesome-skills --skill gcp-cloud-functions -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/gcp-cloud-functions, .gemini/skills/gcp-cloud-functions, .github/skills/gcp-cloud-functions and .opencode/skills/gcp-cloud-functions in your project.

What does GCP Cloud Functions need to run?

Going by SKILL.md and its folder, GCP Cloud Functions needs the command-line tools its instructions call (gcloud). Our summary lists: Python 3; Node.js. Compatibility (from SKILL.md): Requires the relevant OS/platform tooling and privileged access where noted. Docs-only; helper scripts and templates not bundled..

Does GCP Cloud Functions 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 GCP Cloud Functions 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 GCP Cloud Functions use?

GCP Cloud Functions is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does GCP Cloud Functions use?

About 2.3k tokens (SKILL.md is roughly 9.3k 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 GCP Cloud Functions?

Skills that share tags, products or a category with GCP Cloud Functions: GCP Cloud Run (davila7/claude-code-templates, 32k stars), Google Cloud Solution N Tier Serverless Web App (google/skills, 21k stars), Deploying On GCP (ancoleman/ai-design-components, 526 stars) and Apollo Deploy Integration (jeremylongshore/tons-of-skills-marketplace, 2.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains GCP Cloud Functions?

sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,379 GitHub stars. The repository holds 1,493 skills in this directory. The repository was last updated on October 9, 2026.

Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.