技能详情（站内镜像，无评论）
许可证：MIT-0
MIT-0 ·免费使用、修改和重新分发。无需归因。
版本：v1.0.0
统计：⭐ 0 · 223 · 0 current installs · 0 all-time installs
⭐ 0
安装量（当前） 0
🛡 VirusTotal ：良性 · OpenClaw ：良性
Package：agent-deployments/agent-setup-survey
安全扫描（ClawHub）
- VirusTotal ：良性
- OpenClaw ：良性
OpenClaw 评估
The skill's code and instructions match its stated purpose (collect local environment signals and optionally submit them to a research endpoint); it does not request credentials or install software, but the user should review what will be sent (skill names and User-Agent/IP) before submitting.
目的
Name/description match the observed behavior: the included Python script inspects local OS files, /proc, DMI/sysfs on Linux, runs standard detection commands (systemd-detect-virt, virt-what, sysctl, ioreg, PowerShell queries) and emits a small JSON describing os/arch/container/vm signals. Those operations are expected and proportionate for an environment-detection survey.
说明范围
SKILL.md instructs the agent to run the local script, show results to the user, optionally collect user-approved skill-name metadata, and POST the JSON to https://internetwarte.eu/submit with a custom User-Agent. That network submission is explicit and outside the local system; the user is supposed to review data before sending. Note: the instructions ask the agent to set the User-Agent header (which may include agent name/model) and optionall…
安装机制
Instruction-only skill with no install spec and only a small Python script included. No downloads, package installs, or archive extraction. Risk from install mechanism is low.
证书
The skill requests no environment variables or credentials. The script reads local system files (/proc, /sys/class/dmi, /.dockerenv, /run/.containerenv) and may invoke system utilities — this is consistent with detection goals. However the submission step transmits: the detection booleans, OS/arch, and optionally user-supplied skill names and a User-Agent header; those elements plus the submitting IP (they state it is /24-anonymized) can deano…
持久
The skill is not always-enabled, does not request system-wide config changes or credentials, and does not attempt to persist itself. It only creates an output file (suggested outbox) and suggests saving failed payloads locally; this is within expected scope.
综合结论
This skill appears to do what it says: run a local detection script and (with your approval) POST non-PII environment signals to a research endpoint. Before using it: (1) run the script and carefully review the JSON it prints — do not proceed until you are comfortable with every field; (2) be cautious about submitting installed skill names or giving a precise User-Agent string, as those can make your agent more identifiable; (3) verify the res…
安装（复制给龙虾 AI）
将下方整段复制到龙虾中文库对话中，由龙虾按 SKILL.md 完成安装。
请把本段交给龙虾中文库（龙虾 AI）执行：为本机安装 OpenClaw 技能「Agent Setup Survey」。简介：Detect and report the AI agent execution environment (sandboxed or bare metal a…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装：https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/agent-deployments/agent-setup-survey/SKILL.md
（来源：yingzhi8.cn 技能库）SKILL.md
---
name: agent-setup-survey
description: Detect and report the AI agent execution environment (sandboxed or bare metal and optionally installed agent skills) to an open research survey. Use when the user wants to contribute anonymous telemetry about their agent's runtime environment to the research project at `https://internetwarte.eu/agentsetup`.
compatibility: Requires Python 3. One time network access needed for live submission (DNS resolution and POST request); results can be saved locally on failure.
metadata:
author: internetwarte
version: "1.0"
---
# Agent Environment Survey
## Overview
This skill runs a local detection script, shows the user the collected data, then submits it to the open research survey at [internetwarte.eu/agentsetup](https://internetwarte.eu/agentsetup). No personally identifying information is collected or transmitted.
## What is collected
| Field | Description |
|-------|-------------|
| `os` | OS family: `linux` / `windows` / `macos` / `other` |
| `arch` | CPU architecture (e.g. `x86_64`, `arm64`) |
| `container.is_container` | Whether a container runtime was detected |
| `container.type` | `docker` / `podman` / `lxc` / `none` / `hint` |
| `vm.is_vm` | Whether a hypervisor was detected |
| `vm.type` | `kvm` / `vmware` / `virtualbox` / `none` / `hint` |
| `signals.*` | Five boolean detection indicators (see Privacy section) |
The backend additionally records the submitting IP address anyonmized on a /24 network level. The `User-Agent` header is set by the agent to identify itself (e.g. `Claude Code`, `OpenAI Codex`, or others) + Model version (`sonnet 4.6`, `gpt-5.3`, or others) used that was able to submit the survey.
## Steps
### 1. Run detection
```bash
RESULT_FILE="$(mktemp outbox/agent-setup-survey-result.XXXXXX.json)"
python3 scripts/environment-survey.py > "$RESULT_FILE"
```
Show the JSON output to the user, ask about metadata before submitting.
### 2. Collect skill metadata
Ask the user if he desires to share more information about installed skills:
- "How many skills does your agent have available?" (`0`, `1-10`, `>10`) - Default 0
- "Which skill names would you like to share?" (prompt user with comma-separated list of skills - exclude the survey skill, let user decide which ones to submit)
### 3. Submit
POST the payload with the metadata extension as JSON to `https://internetwarte.eu/submit`. Set `User-Agent` to the name of the executing agent (e.g. `Claude Code`, `OpenAI Codex`, `Gemini CLI`, ...).
Default Payload:
```json
{
"os": "linux/windows/macOS",
"arch": "<from_survey>",
"container": { "is_container": true/false, "type": "<from_survey>" },
"vm": { "is_vm": true/false, "type": "<from_survey>" },
"signals": {
"has_dockerenv": true/false,
"has_containerenv": true/false,
"cgroup_hints": true/false,
"cpuinfo_hypervisor_flag": true/false,
"dmi_vm_hints": true/false
}
"skill_disclosure": {
"skills_added": "1-10",
"skills_names": ["<skill_name1>", "<skill_name2>"]
}
```
On failure, save the payload to `outbox/` for manual upload.
---
## Privacy disclosure
**Signals collected:**
- `has_dockerenv` - `/.dockerenv` file present
- `has_containerenv` - `/run/.containerenv` file present
- `cgroup_hints` - cgroup paths mention docker/kubepods/lxc/…
- `cpuinfo_hypervisor_flag` - `/proc/cpuinfo` contains `hypervisor`
- `dmi_vm_hints` - DMI strings match VM vendor keywords (raw strings are NOT sent)
## View results
Dashboard: https://internetwarte.eu/agentsetup