GCP DrawIO Diagram Generator
a5c-ai/babysitter
Creates DrawIO XML diagrams of Google Cloud architectures from text or images, and analyzes existing .drawio files to list their GCP components.
Generates performance-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Performance Optimization pillar of the Google Cloud Well-Architected…
Install Google Cloud Waf Performance Optimization
$ npx skills add google/skills --skill google-cloud-waf-performance-optimization -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install google/skills google-cloud-waf-performance-optimization --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/google-cloud-waf-performance-optimization .claude/skills/google-cloud-waf-performance-optimization && 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 "google-cloud-waf-performance-optimization" agent skill from https://github.com/google/skills/tree/main/skills/cloud/google-cloud-waf-performance-optimization into .claude/skills/google-cloud-waf-performance-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "google-cloud-waf-performance-optimization", 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/google-cloud-waf-performance-optimizationType 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 google-cloud-waf-performance-optimization -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install google/skills google-cloud-waf-performance-optimization --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/google-cloud-waf-performance-optimization .agents/skills/google-cloud-waf-performance-optimization && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "google-cloud-waf-performance-optimization" agent skill from https://github.com/google/skills/tree/main/skills/cloud/google-cloud-waf-performance-optimization into .agents/skills/google-cloud-waf-performance-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "google-cloud-waf-performance-optimization", 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 google-cloud-waf-performance-optimization -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install google/skills google-cloud-waf-performance-optimization --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/google-cloud-waf-performance-optimization .cursor/skills/google-cloud-waf-performance-optimization && 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 "google-cloud-waf-performance-optimization" agent skill from https://github.com/google/skills/tree/main/skills/cloud/google-cloud-waf-performance-optimization into .cursor/skills/google-cloud-waf-performance-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "google-cloud-waf-performance-optimization", 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/google-cloud-waf-performance-optimization--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 google-cloud-waf-performance-optimization -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install google/skills google-cloud-waf-performance-optimization --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/google-cloud-waf-performance-optimization .gemini/skills/google-cloud-waf-performance-optimization && 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 "google-cloud-waf-performance-optimization" agent skill from https://github.com/google/skills/tree/main/skills/cloud/google-cloud-waf-performance-optimization into .gemini/skills/google-cloud-waf-performance-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "google-cloud-waf-performance-optimization", 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 google-cloud-waf-performance-optimizationInstalls 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 google-cloud-waf-performance-optimization -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/google-cloud-waf-performance-optimization .github/skills/google-cloud-waf-performance-optimization && 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 "google-cloud-waf-performance-optimization" agent skill from https://github.com/google/skills/tree/main/skills/cloud/google-cloud-waf-performance-optimization into .github/skills/google-cloud-waf-performance-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "google-cloud-waf-performance-optimization", 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 google-cloud-waf-performance-optimization -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 google-cloud-waf-performance-optimization --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/google-cloud-waf-performance-optimization .opencode/skills/google-cloud-waf-performance-optimization && 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 "google-cloud-waf-performance-optimization" agent skill from https://github.com/google/skills/tree/main/skills/cloud/google-cloud-waf-performance-optimization into .opencode/skills/google-cloud-waf-performance-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "google-cloud-waf-performance-optimization", 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
google-cloud-waf-performance-optimization- GitHub stars
- 21k
- Token cost
- ~1.8k tokens
- SKILL.md length
- 733 words
- Files
- 1
- Skills in repo
- 147
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Generates performance-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Performance Optimization pillar of the Google Cloud Well-Architected…
- Evaluate a workload
- SKILL.md covers Overview, Core principles, Relevant Google Cloud products and Workload assessment questions, plus 1 more section
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Identify performance requirements
What it does
Google Cloud Waf Performance Optimization is an agent skill from google/skills, published by the product's own GitHub organization. Generates performance-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Performance Optimization pillar of the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify performance requirements, and provide actionable recommendations for resource allocation, modular design, and elasticity.
Its SKILL.md is about 1.8k 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 Development, covering Performance optimization and Cloud architecture. It works with Google Cloud. The repository describes itself as: Agent Skills for Google products and technologies. The licence is Apache-2.0.
When your agent uses it
- Evaluate a workload
- Identify performance requirements
- Provide actionable recommendations for resource allocation
Example prompts
- “Use the google-cloud-waf-performance-optimization skill to generate performance-focused guidance for Google Cloud workloads based on the design…”
- “/google-cloud-waf-performance-optimization”
What it can do on your machine
Read from SKILL.md and the folder at commit 7d97937. 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.
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.com
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
Google Cloud Waf Performance Optimization loads about 1.8k tokens when it runs. Until then it costs about 105 tokens; SKILL.md has 733 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 7d97937, republished under its Apache-2.0 licence (© google). 733 words, ~1,835 tokens.
Download SKILL.mdSave it as
.claude/skills/google-cloud-waf-performance-optimization/SKILL.md (or your agent's skills folder).- name
- google-cloud-waf-performance-optimization
- description
- Generates performance-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Performance Optimization pillar of the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify performance requirements, and provide actionable recommendations for resource allocation, modular design, and elasticity.
- metadata.version
- 1.0.0
- metadata.category
- WellArchitectedFramework
Google Cloud Well-Architected Framework skill for the Performance Optimization pillar
Overview
The Performance Optimization pillar of the Google Cloud Well-Architected Framework provides principles and recommendations to help you design, build, and operate high-performing workloads. It focuses on efficiently allocating resources, leveraging modular architectures, and using data-driven insights to continuously monitor and improve performance as your business needs evolve.
Core principles
The recommendations in the performance optimization pillar of the Well-Architected Framework are aligned with the following core principles:
Plan resource allocation: Carefully select and configure the compute, storage, and networking resources that best match the specific requirements of your workload. Grounding document: https://docs.cloud.google.com/architecture/framework/performance-optimization/plan-resource-allocation.md.txt
Take advantage of elasticity: Utilize automated scaling and serverless technologies to dynamically adjust resource capacity in response to real-time demand fluctuations. Grounding document: https://docs.cloud.google.com/architecture/framework/performance-optimization/elasticity.md.txt
Promote modular design: Architect systems using independent, loosely coupled components to enhance scalability and allow individual parts to be optimized without affecting the entire system. Grounding document: https://docs.cloud.google.com/architecture/framework/performance-optimization/promote-modular-design.md.txt
Continuously monitor and improve performance: Implement robust observability to identify bottlenecks and use performance data to drive iterative enhancements throughout the software development lifecycle. Grounding document: https://docs.cloud.google.com/architecture/framework/performance-optimization/continuously-monitor-and-improve-performance.md.txt
Relevant Google Cloud products
The following are examples of Google Cloud products and features that are relevant to performance optimization:
Compute and scaling
- Compute Engine (MIGs): Managed instance groups that support autoscaling and load balancing for VM-based workloads.
- Google Kubernetes Engine (GKE): Provides container orchestration with horizontal and vertical pod autoscaling.
- Cloud Run: A fully managed serverless platform that automatically scales containers to zero or up based on traffic.
Data and caching
- Cloud CDN: Low-latency content delivery network to cache static and dynamic content closer to end-users.
- Memorystore: Managed in-memory data store for Valkey and Redis to provide sub-millisecond data access.
- Bigtable: NoSQL database service for analytical and operational workloads requiring low latency and high throughput.
- Spanner: RDBMS that provides global consistency, high availability, and horizontal scaling for mission-critical transactional applications.
Performance analysis and monitoring
- Cloud Trace: Distributed tracing system that helps identify latency bottlenecks.
- Cloud Profiler: Continuous CPU and memory profiling to identify resource-heavy application code.
- Cloud Monitoring: Provides dashboards and alerts based on performance KPIs like latency and throughput.
Show full SKILL.md (380 more words)Show less
Workload assessment questions
Ask appropriate questions to understand the performance-related requirements and constraints of the workload and the user's organization. Choose questions from the following list:
Plan resource allocation
- When initially provisioning compute resources for a new application, which approach do you use to determine the required capacity for expected peak loads?
- Which caching strategies (browser, in-memory, CDN, database) do you utilize to improve performance and responsiveness?
- How do you optimize the performance of your data storage solutions (e.g., SSD vs HDD, storage classes) for your applications?
Promote modular design
- Which architectural patterns (microservices, asynchronous messaging, stateless servers) do you employ to enhance performance and resilience?
- How do you design your application to minimize the impact of failures in one part of the system on other parts?
Continuously monitor and improve performance
- How frequently do you review and analyze the performance of your production applications and infrastructure?
- Which tools or techniques (APM, distributed tracing, load testing) do you use to proactively identify and diagnose performance bottlenecks?
- How do you incorporate performance considerations into your software development lifecycle (SDLC)?
Take advantage of elasticity
- Which methods do you use to manage and optimize the cost of your cloud resources while maintaining performance?
- How do you typically handle sudden spikes in traffic or workload on your applications?
Validation checklist
Use the following checklist to evaluate the architecture's alignment with performance optimization recommendations:
Resource allocation
- Initial provisioning is based on load testing or historical data rather than general estimates.
- Caching is implemented at multiple layers (CDN, in-memory, or browser) to offload backend systems.
- Storage types (SSD/HDD) and classes are selected based on the specific I/O requirements of the workload.
Modular design
- The architecture uses microservices or decoupled components to allow independent scaling.
- Circuit breakers or bulkheads are implemented to isolate failures and prevent performance degradation across the system.
Monitoring and continuous improvement
- Automated dashboards and alerts are configured for key performance indicators (KPIs).
- Distributed tracing and profiling tools are used to identify code-level bottlenecks.
- Performance testing (unit and integration) is integrated into the software development lifecycle.
Elasticity
- Auto-scaling rules are configured and validated to handle variable demand.
- The architecture leverages serverless or managed services to dynamically match capacity to load.
- Resource utilization is reviewed regularly to eliminate idle overhead and balance cost with performance.
© 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
Just SKILL.md in skills/cloud/google-cloud-waf-performance-optimization of google/skills.
Open the folder on GitHubat commit 7d97937
Compare with similar skills
Google Cloud Waf Performance Optimization 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 |
|---|---|---|---|---|---|---|
| Google Cloud Waf Performance Optimization this skillgoogle/skills | 21k | — | ~1.8k | Automated safety check: Pass | Apache-2.0 | |
| GCP DrawIO Diagram Generatora5c-ai/babysitter | 1.8k | — | ~3.7k | Automated safety check: Pass | MIT | |
| Architect For Startupsaws/agent-toolkit-for-aws | 2.8k | — | ~3.7k | Automated safety check: Pass | Apache-2.0 | |
| Cloud Cost Optimizationwshobson/agents | 40k | 14 repos | ~1.7k | Automated safety check: Pass | MIT | |
| Thesvgglincker/thesvg | 2.8k | — | ~1.5k | Automated safety check: Pass | MIT | |
| Dangling DNS Finderanirudhbiyani/findmytakeover | 180 | — | ~1.8k | Automated safety check: Pass | GPL-3.0 |
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Questions about Google Cloud Waf Performance Optimization
What does Google Cloud Waf Performance Optimization do?
Generates performance-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Performance Optimization pillar of the Google Cloud Well-Architected…. Google Cloud Waf Performance Optimization is an agent skill from google/skills, published by the product's own GitHub organization. Generates performance-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Performance Optimization pillar of the Google Cloud Well-Architected Framework (WAF).
When should I use Google Cloud Waf Performance Optimization?
Google Cloud Waf Performance Optimization fits situations like: evaluate a workload; identify performance requirements; provide actionable recommendations for resource allocation.
How do I install Google Cloud Waf Performance Optimization in Claude Code?
Run `npx skills add google/skills --skill google-cloud-waf-performance-optimization -a claude-code`. Or copy the skill folder (skills/cloud/google-cloud-waf-performance-optimization in google/skills) into .claude/skills/google-cloud-waf-performance-optimization in your project. Claude Code loads it when a task matches its description.
How do I install Google Cloud Waf Performance Optimization in Codex?
Run `npx skills add google/skills --skill google-cloud-waf-performance-optimization -a codex`. Or copy the skill folder (skills/cloud/google-cloud-waf-performance-optimization in google/skills) into .agents/skills/google-cloud-waf-performance-optimization in your project. Codex loads it when a task matches its description.
Can I use Google Cloud Waf Performance Optimization 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 google-cloud-waf-performance-optimization -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/google-cloud-waf-performance-optimization, .gemini/skills/google-cloud-waf-performance-optimization, .github/skills/google-cloud-waf-performance-optimization and .opencode/skills/google-cloud-waf-performance-optimization in your project.
What does Google Cloud Waf Performance Optimization need to run?
SKILL.md names no scripts, command-line tools or credentials: Google Cloud Waf Performance Optimization is instructions for the agent only.
Does Google Cloud Waf Performance Optimization access the network?
SKILL.md names 1 domain. As links in the text: docs.cloud.google.com. This is read from the text; nothing was executed.
Is Google Cloud Waf Performance Optimization 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 Google Cloud Waf Performance Optimization use?
Google Cloud Waf Performance Optimization 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 Google Cloud Waf Performance Optimization use?
About 1.8k tokens (SKILL.md is roughly 7.3k 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 Google Cloud Waf Performance Optimization?
Skills that share tags, products or a category with Google Cloud Waf Performance Optimization: GCP DrawIO Diagram Generator (a5c-ai/babysitter, 1.8k stars), Architect For Startups (aws/agent-toolkit-for-aws, 2.8k stars), Cloud Cost Optimization (wshobson/agents, 40k stars) and Thesvg (glincker/thesvg, 2.8k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Google Cloud Waf Performance Optimization?
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.