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 skills add williamzujkowski/standards --skill serverlessgit clone --depth 1 https://github.com/williamzujkowski/standardsWrote 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/williamzujkowski/standards/serverless)<a href="https://agentmods.dev/skills/williamzujkowski/standards/serverless"><img src="https://agentmods.dev/badge/skills/williamzujkowski/standards/serverless/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/williamzujkowski/standards/serverless"><img src="https://agentmods.dev/badge/skills/williamzujkowski/standards/serverless.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00005 | $0.03446 |
| Opus 5.5 | $0.00002 | $0.01378 |
| Sonnet 5.5 | $0.00001 | $0.00689 |
| Haiku 4.5 | $0.00001 | $0.00345 |
Grade A, and why
serverless 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 yesterday.
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 graphql-api-design — 551 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 — 570 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Serverless Computing
Level 1: Quick Reference
Serverless Benefits and Tradeoffs
Benefits:
- Zero Server Management: No OS patching, scaling, or capacity planning
- Automatic Scaling: Scales from zero to thousands of concurrent executions
- Pay-Per-Use: Only charged for actual execution time (100ms granularity)
- Built-in HA: Multi-AZ deployment by default
- Fast Time-to-Market: Focus on code, not infrastructure
Tradeoffs:
- Cold Starts: 100ms-5s latency for new container initialization
- Execution Limits: 15 min max (Lambda), 60 min (Cloud Functions)
- Vendor Lock-in: Platform-specific APIs and deployment models
- Debugging Complexity: Distributed tracing across ephemeral environments
- State Management: Stateless by design, requires external persistence
Common Serverless Patterns
1. API Backend (HTTP Trigger)
Client → API Gateway → Lambda → Database
- RESTful APIs, GraphQL endpoints
- Authentication/authorization at gateway
- Response caching, throttling, API keys
2. Event-Driven Processing (Event Trigger)
S3 Upload → Lambda → Process File → Store Result
SQS Queue → Lambda → Transform Data → Publish Event
DynamoDB Stream → Lambda → Aggregate Metrics
3. Scheduled Tasks (Cron Trigger)
EventBridge Rule (cron) → Lambda → Cleanup/Report/Backup
- Data aggregation (hourly, daily)
- Automated backups and archival
- Health checks and monitoring
4. Stream Processing
Kinesis/Kafka → Lambda → Real-time Analytics → Dashboard
- Log processing and filtering
- Clickstream analysis
- IoT data ingestion
Essential Serverless Checklist
Architecture:
- Function size < 50 MB (Lambda), memory 128-10240 MB
- Single responsibility per function
- Async patterns for long-running tasks (SQS, Step Functions)
- Idempotent handlers (retry-safe)
Cold Start Optimization:
- Provisioned concurrency for latency-sensitive APIs
- Minimize dependencies (slim packages)
- Initialize SDK clients outside handler
- Use compiled languages (Go, Rust) for sub-100ms starts
What ships with it
10 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- REFERENCE.md 21 KB
- resources/README.md 27 B
- resources/serverless-patterns.md 9.8 KB
- scripts/deploy-lambda.sh 6.6 KB runs code
- scripts/README.md 25 B
- templates/api-gateway.yaml 7.1 KB
- templates/lambda-function.py 6.2 KB runs code
- templates/README.md 27 B
- templates/sam-template.yaml 6.4 KB
- templates/serverless.yml 3.4 KB
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.
- yesterday First seen · 570 lines · 5 tokens per session scan A 510d04de60d3
serverless is a skill published in the GitHub repository williamzujkowski/standards (18 stars, last pushed 1mo ago), licensed MIT. It adds 5 tokens to every session and 3,446 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 89% identical to graphql-api-design, differing in 551 lines, and is treated as a copy.
Other skills, from other repositories
serverless-expert
Design and implement production-grade serverless applications with optimal performance, cost efficiency, and scalability. Use when the user mentions serverless or FaaS, AWS Lambda, Azure Functions, Cloud Functions, cold starts, event-driven architecture, or API Gateway-fronted workloads.
architecture-paradigm-serverless
Applies serverless FaaS patterns for event-driven workloads. Use when designing bursty workloads with minimal infrastructure and pay-per-execution cost model.
gcp-essentials
Use when running a small product on core Google Cloud via the gcloud CLI: a project, Cloud Run deploys, a locked-down Cloud Storage bucket, managed Cloud SQL, and least-privilege IAM wiring them together. NOT AWS (that is aws-essentials), NOT the CI pipeline that ships the image (that is deployment), NOT Postgres…
architecture-patterns
Software architecture patterns and best practices.
hookdeck-event-gateway
Hookdeck Event Gateway — webhook infrastructure that replaces your queue. Use when receiving webhooks and need guaranteed delivery, automatic retries, replay, rate limiting, filtering, or observability. Eliminates the need for your own message queue for webhook processing.
vercel-log-drains-webhooks
Receive and verify Vercel Log Drains deliveries. Use when setting up a Vercel log drain HTTP endpoint, debugging x-vercel-signature verification, handling the x-vercel-verify endpoint handshake, or processing batched log entries from sources like lambda, edge, build, static, external, firewall, and redirect.