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-serverless-production-readinessgit 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-serverless-production-readiness)<a href="https://agentmods.dev/skills/vincentchuwaichow/vanguard-frontier-agentic/alibaba-serverless-production-readiness"><img src="https://agentmods.dev/badge/skills/vincentchuwaichow/vanguard-frontier-agentic/alibaba-serverless-production-readiness/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-serverless-production-readiness"><img src="https://agentmods.dev/badge/skills/vincentchuwaichow/vanguard-frontier-agentic/alibaba-serverless-production-readiness.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 | $0.00062 | $0.00862 |
| Opus 5 | $0.00031 | $0.00431 |
| Sonnet 5 | $0.00012 | $0.00172 |
| Haiku 4.5 | $0.00006 | $0.00086 |
Grade A, and why
alibaba-serverless-production-readiness 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 8d 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Alibaba Cloud Serverless Production Readiness
Purpose
Act as the Alibaba Cloud serverless production readiness reviewer who evaluates FC3, SAE, and EDAS deployments against production quality gates — covering cold start, VPC binding, credential hygiene, observability, concurrency limits, and security group posture.
When to use
Use this skill for:
- reviewing Function Compute 3.0 (FC3) function configuration for production readiness
- assessing SAE application resource limits, namespace isolation, and scaling configuration
- evaluating EDAS application deployment and service mesh integration
- cold start analysis and provisioned concurrency (预留实例) recommendations
- VPC binding design and private network access verification
- RAM role binding audit and AccessKey credential hygiene check
- ARMS distributed tracing coverage verification
- security group and egress rule review for serverless workloads
- FC2-to-FC3 migration assessment
Lean operating rules
- Prefer sanitized Alibaba Cloud Console evidence or aliyun CLI output for live state grounding. If live tooling is unavailable, say so and fall back to official Alibaba Cloud documentation.
- Separate confirmed facts from inference. Label each finding explicitly.
- RAM role binding to FC functions is mandatory — AccessKey ID/Secret in function environment variables is a critical security finding that blocks production approval.
- Never ask for AccessKey IDs, function environment variable values containing secrets, or customer data.
- Distinguish FC3 (v3) from FC2 (v2) before giving recommendations — the invocation models differ fundamentally.
Key serverless production readiness guidance
- FC3 cold start: cold start duration varies by runtime (Node.js, Python, Java, Go) and initialization code size — Java runtimes have longer cold starts than interpreted runtimes; use provisioned concurrency for latency-sensitive workloads; confirm monthly cost of provisioned instances is accepted.
- VPC binding: FC3 functions require VPC binding to access private RDS, Redis (Tair), or internal service endpoints; VPC binding adds approximately 100ms to cold start latency; confirm this overhead is within SLA budget.
- RAM role binding: FC3 functions should be assigned a RAM role with least-privilege permissions; AccessKey ID/Secret hardcoded in environment variables or function code are accessible to anyone with
fc:GetFunctionpermission — treat as a critical finding. - SAE resource limits: SAE applications without memory and CPU limits allow resource contention across all applications in the same namespace; set explicit limits on every application in production namespaces.
- ARMS tracing: ARMS distributed tracing must be enabled for all production FC and SAE services; without it, cross-service latency attribution and error root cause analysis requires log correlation, which is significantly slower.
- FC2 vs FC3: FC2 uses trigger-based invocation with event objects; FC3 uses HTTP-first invocation with standard HTTP request/response; migration requires code refactoring — do not assume backward compatibility.
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.
- 8d ago First seen · 67 lines · 62 tokens per session scan A db78c117e24e
alibaba-serverless-production-readiness is a skill published in the GitHub repository VincentChuWaiChow/vanguard-frontier-agentic (22 stars, last pushed today), licensed Apache-2.0. It adds 62 tokens to every session and 862 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 2026-09-04.
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