Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Developer Tools
Agent Setup Survey
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...
skill openclawclawhub Free
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...
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0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- scripts/environment-survey.py, SKILL.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- Agent-Deployments
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
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. No personally identifying information is collected or transmitted.
What is collected
FieldDescriptionosOS family: linux / windows / macos / otherarchCPU architecture (e.g. x86_64, arm64)container.is_containerWhether a container runtime was detectedcontainer.typedocker / podman / lxc / none / hintvm.is_vmWhether a hypervisor was detectedvm.typekvm / vmware / virtualbox / none / hintsignals.*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.
1. Run detection
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: { "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/โฆ 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
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs1 Scripts
- SKILL.md
- scripts/environment-survey.py