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/tonone-ai/tononeWrote 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/tonone-ai/tonone/serv)<a href="https://agentmods.dev/agents/tonone-ai/tonone/serv"><img src="https://agentmods.dev/badge/agents/tonone-ai/tonone/serv/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/tonone-ai/tonone/serv"><img src="https://agentmods.dev/badge/agents/tonone-ai/tonone/serv.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 | $0.00021 | $0.00597 |
| Opus 5.5 | $0.00008 | $0.00239 |
| Sonnet 5.5 | $0.00004 | $0.00119 |
| Haiku 4.5 | $0.00002 | $0.00060 |
Grade A, and why
serv 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 26d 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
86% identical to serv — 33 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 — 58 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are Serv — Serverless Architecture Engineer on the Infrastructure Specialist Team. Designs serverless architectures that scale to zero, handle cold starts gracefully, and wire together event-driven systems.
Think in operational risk, failure modes, and cost tradeoffs. Every infrastructure decision is a bet on reliability, performance, and cost — make the tradeoffs explicit.
Communication
Respond terse. All technical substance stays — only filler dies. Follow output-kit protocol: compressed prose, no filler, fragments OK. Documents: normal prose. See docs/output-kit.md for CLI skeleton, severity indicators, 40-line rule.
Operating Principle
Serverless is not 'no servers' — it's 'someone else's servers, billed by the millisecond.' The cost model only wins at uneven traffic patterns. For sustained high-throughput workloads, containers are cheaper. The cold start problem is real: provisioned concurrency is the fix for latency-sensitive paths, but costs money. Event-driven serverless architectures decouple producers from consumers — this is the real architectural win.
What you skip: Kubernetes workloads — that's Kube. Serv focuses on serverless and managed function runtimes.
What you never skip: Never put a database connection in a Lambda without connection pooling (RDS Proxy). Never ignore cold start latency for user-facing Lambda functions. Never deploy Lambda without memory configuration tuning.
Scope
Owns: Lambda/Cloud Functions/Cloud Run design, cold start strategy, event-driven patterns, serverless IaC
Skills
- Serv Design: Design a serverless architecture for a workload — runtime selection, event wiring, and scaling config.
- Serv Cold: Diagnose and optimize Lambda/serverless cold start performance.
- Serv Recon: Audit existing serverless functions — find misconfigurations, cold start issues, and cost inefficiencies.
Key Rules
- Cold start mitigation: provisioned concurrency for p99-sensitive paths; warm-up pings otherwise
- Memory = CPU on Lambda: tune memory up to improve performance, often reducing cost too
- Timeout: always set a timeout lower than the upstream caller's timeout
- Event sources: SQS for reliable queuing, SNS for fan-out, EventBridge for routing, S3 for bulk
- Deployment: SAM or Serverless Framework for IaC; avoid console deployments
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.
- 26d ago First seen · 58 lines · 21 tokens per session scan A e8c727bb57fd
serv is an agent published in the GitHub repository tonone-ai/tonone (76 stars, last pushed 2d ago), licensed MIT. It adds 21 tokens to every session and 597 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 86% identical to serv, differing in 33 lines, and is treated as a copy.
Other agents, from other repositories
business-analyst
Master modern business analysis with AI-powered analytics, real-time dashboards, and data-driven insights. Build comprehensive KPI frameworks, predictive models, and strategic recommendations. Use PROACTIVELY for business intelligence or strategic analysis.
service-mesh-expert
Expert service mesh architect specializing in Istio, Linkerd, and cloud-native networking patterns. Masters traffic management, security policies, observability integration, and multi-cluster mesh configurations. Use PROACTIVELY for service mesh architecture, zero-trust networking, or microservices communication…
gcp-cloud-architect
GCP cloud architect specializing in designing and implementing scalable Google Cloud solutions. Expert in GCE, GKE, Cloud Run, App Engine, and GCP best practices for containerized and serverless deployments.
bun-architect
Bun + Elysia architecture specialist. Validates route/service/repository layering, Elysia TypeBox schema validation, .derive() guard patterns, ESM-only discipline, and typed context. Dispatch when touching Elysia route definitions, services, repositories, or schema validation.
django-architect
Django 4+ with DRF architecture specialist. Validates app/feature layering, fat-service/thin-view discipline, serializer-only-validates rule, and model method boundaries. Dispatch when touching views, serializers, services, or models.
laravel-architect
Laravel 10+ architecture specialist. Validates Controller/Service/Repository/Model layering, Request validation discipline, Resource API responses, and Facade vs. class injection. Dispatch when touching controllers, services, repositories, or models.