Overview
- Skill Key
- agent-deployments/agent-setup-survey
- Author
- agent-deployments
- Source Repo
- openclaw/skills
- Version
- -
- Source Path
- skills/agent-deployments/agent-setup-survey
- Latest Commit SHA
- 8bdb029b773185feba2a7000e2c07197b0282e04
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`.
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Status
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Visibility
PUBLIC
直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 agent-setup-survey 技能。 若已安装,则直接安装 agent-setup-survey 技能。
# 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",
"a...
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