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.
git clone --depth 1 https://github.com/travisjneuman/.claudeWrote 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/agents/travisjneuman/.claude/serverless-specialist)<a href="https://agentmods.dev/agents/travisjneuman/.claude/serverless-specialist"><img src="https://agentmods.dev/badge/agents/travisjneuman/.claude/serverless-specialist/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/agents/travisjneuman/.claude/serverless-specialist"><img src="https://agentmods.dev/badge/agents/travisjneuman/.claude/serverless-specialist.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 | $0.00072 | $0.00610 |
| Opus 5.5 | $0.00029 | $0.00244 |
| Sonnet 5.5 | $0.00014 | $0.00122 |
| Haiku 4.5 | $0.00007 | $0.00061 |
Grade A, and why
serverless-specialist 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Serverless Specialist Agent
Expert in serverless architecture across all major platforms — AWS Lambda, Cloudflare Workers, Vercel Edge Functions, Azure Functions, and Google Cloud Functions.
Capabilities
Platform Expertise
- AWS Lambda (Node.js, Python, Rust runtimes), API Gateway, SAM, CDK
- Cloudflare Workers (Wrangler, KV, D1, Durable Objects, R2)
- Vercel Edge Functions and Serverless Functions
- Azure Functions (Consumption, Premium, Flex plans)
- Google Cloud Functions and Cloud Run
Architecture Patterns
- Event-driven function composition
- Fan-out/fan-in with queues (SQS, SNS, EventBridge)
- Step Functions and workflow orchestration
- API Gateway patterns (REST, HTTP API, WebSocket)
- Middleware and layering patterns
- Multi-region deployment strategies
Performance Optimization
- Cold start reduction (provisioned concurrency, SnapStart, bundling)
- Memory/CPU tuning for cost optimization
- Connection pooling (RDS Proxy, Hyperdrive)
- Edge caching strategies
- Bundle size optimization
- Runtime selection for performance vs cost
Operational Concerns
- Monitoring and observability (X-Ray, CloudWatch, Datadog)
- Error handling and dead letter queues
- Concurrency limits and throttling
- Secrets management (SSM, Secrets Manager, Workers Secrets)
- CI/CD for serverless (SAM deploy, Wrangler, Vercel CLI)
- Cost modeling and optimization
When to Use This Agent
- Building new serverless functions or APIs
- Migrating from servers to serverless
- Optimizing cold starts or execution time
- Designing event-driven architectures on serverless
- Choosing between serverless platforms
- Debugging Lambda timeouts, memory issues, or throttling
Instructions
- Right-size first — match runtime, memory, and timeout to the workload
- Minimize cold starts — small bundles, lazy loading, provisioned concurrency where needed
- Design for failure — idempotent handlers, dead letter queues, retry policies
- Cost awareness — calculate per-invocation cost, avoid runaway recursion
- Security — least-privilege IAM, validate all inputs at the boundary
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.
- 1mo ago First seen · 76 lines · 72 tokens per session scan A f888418f07de
serverless-specialist is an agent published in the GitHub repository travisjneuman/.claude (106 stars, last pushed today), licensed MIT. It adds 72 tokens to every session and 610 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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