Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/techequitycloud/rad-modules/google-cloud-waf-reliabilitynpx skills add techequitycloud/rad-modules --skill google-cloud-waf-reliabilitygit clone --depth 1 https://github.com/techequitycloud/rad-modulesWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/techequitycloud/rad-modules/google-cloud-waf-reliability)<a href="https://agentmods.dev/skills/techequitycloud/rad-modules/google-cloud-waf-reliability"><img src="https://agentmods.dev/badge/skills/techequitycloud/rad-modules/google-cloud-waf-reliability.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00064 | $0.01338 |
| Opus 5 | $0.00032 | $0.00669 |
| Sonnet 5 | $0.00013 | $0.00268 |
| Haiku 4.5 | $0.00006 | $0.00134 |
Grade A, and why
google-cloud-waf-reliability scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
89% identical to google-cloud-waf-reliability — 67 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Google Cloud Well-Architected Framework skill for the Reliability pillar
Overview
The Reliability pillar of the Google Cloud Well-Architected Framework provides principles and recommendations to help you design, deploy, and manage reliable, resilient, and highly available workloads in Google Cloud. A reliable system consistently performs its intended functions under defined conditions, is resilient to failures, and recovers gracefully from disruptions, thereby minimizing downtime, enhancing user experience, and ensuring data integrity.
Core principles
The recommendations in the reliability pillar of the Well-Architected Framework are aligned with the following core principles:
-
Define reliability based on user-experience goals: Measurement of reliability should reflect the actual experience of the system's users rather than merely relying on infrastructure metrics. Focus on outcomes that matter most to users. Grounding document: https://docs.cloud.google.com/architecture/framework/reliability/define-reliability-based-on-user-experience-goals
-
Set realistic targets for reliability: Determine appropriate Service Level Objectives (SLOs) that balance the cost and complexity of maximizing availability against business requirements. Utilize error budgets to manage feature velocity. Grounding document: https://docs.cloud.google.com/architecture/framework/reliability/set-targets
-
Build highly available systems through resource redundancy: Eliminate single points of failure by duplicating critical components across zones and regions to maintain operations during localized outages. Grounding document: https://docs.cloud.google.com/architecture/framework/reliability/build-highly-available-systems
-
Take advantage of horizontal scalability: Design system architectures to scale horizontally (adding more instances) to seamlessly accommodate load fluctuations and improve overall fault tolerance. Grounding document: https://docs.cloud.google.com/architecture/framework/reliability/horizontal-scalability
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 131 lines · 64 tokens per session scan A 6da26b6c18b0
google-cloud-waf-reliability is a skill published in the GitHub repository techequitycloud/rad-modules (2 stars, last pushed yesterday), licensed MPL-2.0. It adds 64 tokens to every session and 1,338 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to google-cloud-waf-reliability, differing in 67 lines, and is treated as a copy.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…