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 aliyun/alibabacloud-agent-toolkit --skill alibabacloud-ram-permission-diagnosegit clone --depth 1 https://github.com/aliyun/alibabacloud-agent-toolkitWrote 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/aliyun/alibabacloud-agent-toolkit/alibabacloud-ram-permission-diagnose)<a href="https://agentmods.dev/skills/aliyun/alibabacloud-agent-toolkit/alibabacloud-ram-permission-diagnose"><img src="https://agentmods.dev/badge/skills/aliyun/alibabacloud-agent-toolkit/alibabacloud-ram-permission-diagnose/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/aliyun/alibabacloud-agent-toolkit/alibabacloud-ram-permission-diagnose"><img src="https://agentmods.dev/badge/skills/aliyun/alibabacloud-agent-toolkit/alibabacloud-ram-permission-diagnose.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 | $0.00133 | $0.02651 |
| Opus 5 | $0.00067 | $0.01326 |
| Sonnet 5 | $0.00027 | $0.00530 |
| Haiku 4.5 | $0.00013 | $0.00265 |
Grade C, and why
alibabacloud-ram-permission-diagnose scanned grade C with 2 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 12d 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.
Downloads and executes remote codehighSupply chain
curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.
> run `curl -fsSL https://aliyuncli.alicdn.com/setup.sh | bash` to update, Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
> run `curl -fsSL https://aliyuncli.alicdn.com/setup.sh | bash` to update, How it starts
The opening of the file, as written. The whole thing — 185 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RAM Permission Diagnosis and Repair
Installation
Pre-check: Aliyun CLI >= 3.3.3 required
Run
aliyun versionto verify >= 3.3.3. If not installed or version too low, runcurl -fsSL https://aliyuncli.alicdn.com/setup.sh | bashto update, or seereferences/cli-installation-guide.mdfor installation instructions.
Pre-check: Aliyun CLI plugin update required
[MUST] run
aliyun configure set --auto-plugin-install trueto enable automatic plugin installation. [MUST] runaliyun plugin updateto ensure that any existing plugins are always up-to-date.
At the start of the Core Workflow (before any CLI invocation): [MUST] Enable AI-Mode — AI-mode is required for Agent Skill execution. Run the following commands before any CLI invocation:
aliyun configure ai-mode enable
aliyun configure ai-mode set-user-agent --user-agent "AlibabaCloud-Agent-Skills/alibabacloud-ram-permission-diagnose"
[MUST] Disable AI-Mode at EVERY exit point — Before delivering the final response for ANY reason, always disable AI-mode first. This applies to ALL exit paths: workflow success, workflow failure, error/exception, user cancellation, session end, or any other scenario where no further CLI commands will be executed. AI-mode is only used for Agent Skill invocation scenarios and MUST NOT remain enabled after the skill stops running.
aliyun configure ai-mode disable
[MUST] CLI User-Agent — Every aliyun CLI command invocation must include:
--user-agent AlibabaCloud-Agent-Skills/alibabacloud-ram-permission-diagnose
Execution constraint: When executing
aliyunCLI commands directly (not generating commands for the user to copy), always append--user-agent AlibabaCloud-Agent-Skills/alibabacloud-ram-permission-diagnose. Do not add this flag to commands shown to users in Path B output or Path C console guidance.
Overview
When a RAM permission error is detected, run through these steps:
- Quick Analysis — parse raw error fields (no tool calls), output a brief summary, ask the user to choose analysis depth
- Deep Analysis — (only if user selects path B) decode if needed, run gap analysis, classify root cause
- Generate Recommendations — least-privilege authorization plan
- Execute Repair — present repair options and wait for user to choose
What ships with it
5 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.
- 12d ago First seen · 185 lines · 133 tokens per session scan C 51dd47aa2949
alibabacloud-ram-permission-diagnose is a skill published in the GitHub repository aliyun/alibabacloud-agent-toolkit (21 stars, last pushed yesterday), licensed Apache-2.0. It adds 133 tokens to every session and 2,651 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it C with 2 findings (downloads and executes remote code, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
alibabacloud-ecs-windows-os-troubleshooting
Troubleshoot and repair Alibaba Cloud ECS Windows instances from inside the GuestOS or remotely via Cloud Assistant. Use whenever the user reports any Windows symptom or asks for a health check on an ECS Windows instance, even vague ones like "check this machine": boot failures (BSOD, black screen, boot loop, stuck at…
alibabacloud-ecs-linux-os-troubleshooting
Troubleshoot an Alibaba Cloud ECS Linux OS. Use when a user needs to diagnose a specified ECS Linux instance, such as instance stuck in Starting, boot stuck, SSH/VNC/Workbench login failure, network issues, disk/FS issues, performance anomalies, suspected mining or hidden processes, crash/hang, clock drift, or…
gke-ai-troubleshooting-jobset-interruption
Diagnoses GKE JobSet interruptions, restarts, and preemptions for AI/ML training workloads autonomously. Use when troubleshooting JobSet restart loops, spot VM preemptions, node readiness failures, host VM issues, or coordinator worker crashes. Don't use for general GKE cluster creation, basic workload deployment, or…
gke-node-notready
Diagnoses GKE nodes reporting NotReady or Unknown status by inspecting node conditions, events, kubelet/containerd logs, and node metrics, then proposing safe remediations. Use when nodes show NotReady, when the kubelet stops posting node status, or when workloads are evicted or stuck Pending due to node health. Don't…
agentcore-investigation
Investigate Bedrock AgentCore runtime sessions via CloudWatch Logs Insights — resolve session/trace IDs, query OTEL spans, filter noise, build timelines. Use when debugging AgentCore agent sessions, tracing tool calls, or analyzing latency.
network-rca
Kubernetes network root cause analysis skill powered by Kubeshark MCP. Use this skill whenever the user wants to investigate past incidents, perform retrospective traffic analysis, take or manage traffic snapshots, extract PCAPs, dissect L7 API calls from historical captures, compare traffic patterns over time, detect…