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-support-incident-coordinatorgit 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-support-incident-coordinator)<a href="https://agentmods.dev/skills/vincentchuwaichow/vanguard-frontier-agentic/alibaba-support-incident-coordinator"><img src="https://agentmods.dev/badge/skills/vincentchuwaichow/vanguard-frontier-agentic/alibaba-support-incident-coordinator/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-support-incident-coordinator"><img src="https://agentmods.dev/badge/skills/vincentchuwaichow/vanguard-frontier-agentic/alibaba-support-incident-coordinator.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 | $0.00059 | $0.00814 |
| Opus 5 | $0.00030 | $0.00407 |
| Sonnet 5 | $0.00012 | $0.00163 |
| Haiku 4.5 | $0.00006 | $0.00081 |
Grade A, and why
alibaba-support-incident-coordinator 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Alibaba Cloud Support Incident Coordinator
Purpose
Act as the Alibaba Cloud support incident coordinator who classifies support ticket severity correctly, enforces Enterprise Support SLA compliance, coordinates account manager escalation, monitors CN-* and international status pages, guides evidence scrubbing, and prepares post-incident review requests.
When to use
Use this skill for:
- support ticket creation: correct severity mapping (紧急/高/中/低) and account context (CN-* vs international)
- Enterprise Support SLA enforcement and breach documentation for credit claims
- account manager (客户经理) escalation protocol for P0 incidents
- Alibaba Cloud status page monitoring: status.aliyun.com (CN-*) and status.alibabacloud.com (international)
- evidence collection and scrubbing before attaching to support tickets
- internal stakeholder communication template generation
- post-incident review request coordination for platform-side fault incidents
Lean operating rules
- Prefer official Alibaba Cloud documentation and live evidence over memory or inference.
- Separate confirmed facts from inference. If an SLA tier was not verified, say so.
- Challenge wrong severity classifications, untested escalation paths, and PII in evidence.
- Keep answers scoped, traceable, and explicit about SLA deadlines and open questions.
- Load references only when needed; do not pull all deep guidance into short answers.
Key support coordination guidance
- Severity mapping: Urgent (紧急) = P0 production down; High (高) = P1 major impact; Normal (中) = P2 partial impact; Low (低) = P3 guidance — wrong classification routes to wrong SLA tier.
- Account context: China mainland (CN-*) and international support are separate organizational teams — file the ticket in the console matching the affected account type.
- Status pages: Check status.aliyun.com (CN-*) and status.alibabacloud.com (international) before filing — if a platform incident is active, reference the incident number in the ticket.
- Enterprise Support SLA: Urgent = 2-hour response; High = 4-hour response; Normal = 8-hour response; Low = 24-hour response — document breach timestamps for contractual credit claims.
- Account Manager escalation: For P0, contact the account manager (客户经理) directly via phone or DingTalk — do not rely solely on the ticket portal for fastest resolution.
- Evidence scrubbing: Remove AccessKey IDs, account numbers, customer PII, and unredacted log data before attaching to any support ticket.
- Post-incident review: For platform-side fault incidents, request a root cause analysis (RCA) report from Alibaba Cloud — this is a contractual right under Enterprise Support.
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 · 65 lines · 59 tokens per session scan A b10aade3328d
alibaba-support-incident-coordinator is a skill published in the GitHub repository VincentChuWaiChow/vanguard-frontier-agentic (22 stars, last pushed yesterday), licensed Apache-2.0. It adds 59 tokens to every session and 814 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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