ANOLISA is a server-side operating layer for AI agent workloads that provides terminal access, token-saving tool-output compression, runtime controls, security, observability, skills, memory, and sandbox management. It is for running and supervising agents from a Linux terminal while retaining an existing shell, agent framework, and sandbox. The catalogue add-ons are components of its agent operating environment and workflows.
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 alibaba/anolisa --skill storage-resizegit clone --depth 1 https://github.com/alibaba/anolisaWrote 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/alibaba/anolisa/storage-resize)<a href="https://agentmods.dev/skills/alibaba/anolisa/storage-resize"><img src="https://agentmods.dev/badge/skills/alibaba/anolisa/storage-resize/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/alibaba/anolisa/storage-resize"><img src="https://agentmods.dev/badge/skills/alibaba/anolisa/storage-resize.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Server-Side Request Forgery · line 111 Code accesses a cloud instance metadata endpoint (e.g. 169.254.169.254). A single request can return temporary IAM credentials, making this a high-value SSRF target for credential theft.Fix: Remove access to cloud metadata endpoints unless strictly required. If metadata is needed, restrict it (e.g. IMDSv2 with hop limit) and never expose returned credentials.
- high Server-Side Request Forgery · line 112 Code accesses a cloud instance metadata endpoint (e.g. 169.254.169.254). A single request can return temporary IAM credentials, making this a high-value SSRF target for credential theft.Fix: Remove access to cloud metadata endpoints unless strictly required. If metadata is needed, restrict it (e.g. IMDSv2 with hop limit) and never expose returned credentials.
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 | $0.00073 | $0.02505 |
| Opus 5.5 | $0.00029 | $0.01002 |
| Sonnet 5.5 | $0.00015 | $0.00501 |
| Haiku 4.5 | $0.00007 | $0.00250 |
Grade C, and why
storage-resize scanned grade C with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Cloud metadata endpointhighServer-side request forgery
One request to 169.254.169.254 can return temporary IAM credentials.
INSTANCE_ID=$(curl -s http://100.100.100.200/latest/meta-data/instance-id) Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
INSTANCE_ID=$(curl -s http://100.100.100.200/latest/meta-data/instance-id) How it starts
The opening of the file, as written. The whole thing — 322 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Storage resize - 磁盘扩容
核心定位
两阶段磁盘扩容流程:
- 云平台阶段:使用
aliyun-ecsskill 完成云盘扩容 - 操作系统阶段:执行分区调整和文件系统扩容
重要约束:
- ☁️ 阿里云云盘仅支持扩容,不支持缩容
- 📀 支持系统盘和数据盘两种场景
- ⚡ 在线扩容:云盘扩容后无需重启实例,通过 NVMe 重新扫描即可识别(NVMe 设备)
前置要求
1. 依赖技能
本技能依赖 aliyun-ecs skill 进行云平台操作:
- 查询磁盘信息 (
DescribeDisks) - 执行磁盘扩容 (
ResizeDisk) - 查询实例信息 (
DescribeInstances)
2. 工具安装
# 检查并安装必要工具
yum install -y cloud-utils-growpart xfsprogs e2fsprogs btrfs-progs
# 验证工具已安装
which growpart xfs_growfs resize2fs
3. 权限要求
- 阿里云 CLI 认证:需配置
aliyun configure(优先使用 EcsRamRole) - 系统权限:需要 root 权限执行分区和文件系统操作
快速开始
一键扩容流程
# 1. 确认设备名称和文件系统类型
lsblk -f /dev/nvme0n1
# 2. 云平台扩容(使用 aliyun-ecs skill)
# aliyun ecs ResizeDisk --DiskId <disk-id> --NewSize <new-size> --RegionId <region>
# 3. NVMe 设备重新扫描(让 OS 识别新容量)
echo 1 > /sys/block/nvme0n1/device/rescan_controller
# 4. 确认新容量已识别
lsblk /dev/nvme0n1
# 5. 扩容分区
growpart /dev/nvme0n1 3
# 6. 扩容文件系统(根据类型选择命令)
xfs_growfs / # XFS(使用挂载点)
resize2fs /dev/nvme0n1p3 # EXT4(使用设备路径)
# 7. 验证
df -h /
文件系统支持
| 文件系统 | 扩容命令 | 参数类型 | 备注 |
|---|---|---|---|
| XFS | xfs_growfs /mountpoint |
挂载点 | Alinux4 默认文件系统 |
| EXT4 | resize2fs /dev/vdb1 |
设备路径 | 支持在线扩容 |
| Btrfs | btrfs filesystem resize max /mountpoint |
挂载点 | 需要 btrfs-progs |
文件系统类型检测
# 方法 1: 使用 df
df -T /
# 方法 2: 使用 lsblk
lsblk -f /dev/nvme0n1p3
# 方法 3: 使用 mount
mount | grep "on / "
完整流程
步骤 1: 云平台扩容(使用 aliyun-ecs skill)
# 获取实例 ID 和地域(ECS 实例内)
INSTANCE_ID=$(curl -s http://100.100.100.200/latest/meta-data/instance-id)
REGION_ID=$(curl -s http://100.100.100.200/latest/meta-data/region-id)
# 查询系统盘信息
aliyun ecs DescribeDisks \
--RegionId $REGION_ID \
--InstanceId $INSTANCE_ID \
--DiskType system
# 执行扩容(例如:40GB → 90GB)
aliyun ecs ResizeDisk \
--DiskId d-bp1234567890abcdef \
--NewSize 90 \
--RegionId $REGION_ID
步骤 2: 操作系统内扩容
# 2.1 识别设备类型
lsblk
# 2.2 NVMe 设备重新扫描(关键步骤!)
# 云盘扩容后,NVMe 设备需要重新扫描控制器才能识别新容量
echo 1 > /sys/block/nvme0n1/device/rescan_controller
# 2.3 验证新容量已识别
lsblk /dev/nvme0n1
# 2.4 扩容分区
growpart /dev/nvme0n1 3
# 2.5 扩容文件系统
# 先确认文件系统类型
FS_TYPE=$(df -T / | tail -1 | awk '{print $2}')
if [ "$FS_TYPE" = "xfs" ]; then
xfs_growfs /
elif [ "$FS_TYPE" = "ext4" ]; then
resize2fs /dev/nvme0n1p3
elif [ "$FS_TYPE" = "btrfs" ]; then
btrfs filesystem resize max /
fi
# 2.6 验证结果
df -h /
lsblk /dev/nvme0n1
What ships with it
2 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.
- 1mo ago First seen · 322 lines · 73 tokens per session scan C 190e188b2406
storage-resize is a skill published in the GitHub repository alibaba/anolisa (603 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 73 tokens to every session and 2,505 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it C with 2 findings (cloud metadata endpoint, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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