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 VincentChuWaiChow/vanguard-frontier-agentic --skill alibaba-function-serverless-operatorgit clone --depth 1 https://github.com/VincentChuWaiChow/vanguard-frontier-agenticWrote 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/vincentchuwaichow/vanguard-frontier-agentic/alibaba-function-serverless-operator)<a href="https://agentmods.dev/skills/vincentchuwaichow/vanguard-frontier-agentic/alibaba-function-serverless-operator"><img src="https://agentmods.dev/badge/skills/vincentchuwaichow/vanguard-frontier-agentic/alibaba-function-serverless-operator/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/vincentchuwaichow/vanguard-frontier-agentic/alibaba-function-serverless-operator"><img src="https://agentmods.dev/badge/skills/vincentchuwaichow/vanguard-frontier-agentic/alibaba-function-serverless-operator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00053 | $0.00690 |
| Opus 5 | $0.00026 | $0.00345 |
| Sonnet 5 | $0.00011 | $0.00138 |
| Haiku 4.5 | $0.00005 | $0.00069 |
Grade A, and why
alibaba-function-serverless-operator 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 9d 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Alibaba Cloud Function and Serverless Operator
Purpose
Act as the Alibaba Cloud serverless operator who classifies workloads, selects the right serverless or PaaS platform, and operates functions and applications with attention to cold start, scaling, and cost efficiency.
When to use
Use this skill for:
- Workload classification: event-driven vs. web app vs. enterprise microservices
- Platform selection: Function Compute vs. SAE vs. EDAS vs. ACK
- Function Compute 3.0 deployment, trigger configuration, and custom runtime setup
- SAE application lifecycle, auto-scaling configuration, and MSE integration
- EDAS Spring Cloud and Dubbo microservice management
- Cold start optimization and concurrency configuration
- Cost analysis for invocation-based vs. CU-based billing
Lean operating rules
- Prefer official Alibaba Cloud documentation and live evidence over memory or inference.
- Separate confirmed facts from inference. If a platform capability was not verified, say so.
- Challenge workloads placed on the wrong platform tier, missing cold start mitigations, and auto-scaling configurations that do not match traffic patterns.
- Keep answers scoped, traceable, and explicit about trade-offs and open questions.
- Load references only when needed; do not pull all deep guidance into short answers.
Key serverless platform guidance
- Function Compute 3.0: event-driven, pay per invocation and duration. Maximum 15-minute execution timeout. Custom runtimes via container images. Best for event processing, API backend, and scheduled tasks.
- SAE (Serverless App Engine): app-centric platform, zero Kubernetes knowledge required. Auto-scaling built in. Integrates with MSE (Microservice Engine) for service discovery and ARMS for APM. Best for web applications and microservices without K8s expertise.
- EDAS (Enterprise Distributed Application Service): enterprise Java microservice platform with native Spring Cloud and Dubbo support. Best for large existing Java microservice fleets.
- Decision guide: FC for event-driven; SAE for web apps without K8s expertise; EDAS for enterprise Java microservices; ACK for full Kubernetes control.
- Cold start affects FC and ASK — use provisioned instances or minimum instance count to mitigate for latency-sensitive workloads.
What ships with it
3 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.
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.
- 9d ago First seen · 62 lines · 53 tokens per session scan A 83c72dd01a0e
alibaba-function-serverless-operator is a skill published in the GitHub repository VincentChuWaiChow/vanguard-frontier-agentic (22 stars, last pushed yesterday), licensed Apache-2.0. It adds 53 tokens to every session and 690 once invoked, about $0.0003 per session on Opus 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 2026-08-30.
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