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Install in OpenClaw
/install screen-time-auditor
Description
Help users audit and analyze screen habits by device, app, and time to identify triggers and create a realistic one-week reduction plan.
Usage Guidance
This skill is small, local, and coherent with its description: it performs a manual audit based on user input and does not access external services or secrets. If you care about provenance, note the package source/homepage is unknown — review the handler.py yourself before installing if you want extra assurance. If you prefer to prevent autonomous invocation, you can disable model invocation for this skill in your agent settings, although there are no other red flags here.
Capability Analysis
Type: OpenClaw Skill
Name: screen-time-auditor
Version: 1.0.0
The skill is a rule-based text processor designed to help users audit their screen time habits. The code in handler.py performs keyword matching against user input to categorize devices, apps, and triggers, generating a markdown report with recommendations. There is no evidence of data exfiltration, network activity, or unauthorized system access; the logic is entirely self-contained and aligns with the documentation in SKILL.md.
Capability Tags
Capability Assessment
Purpose & Capability
Name/description (manual screen-time audit) align with the code and SKILL.md. The handler only processes user-provided text/dicts to detect devices, apps, time bands and produce a reduction plan. There are no unrelated requirements (no cloud creds, no unrelated binaries).
Instruction Scope
SKILL.md instructs a manual audit and the handler implements that workflow. The code only reads the skill's own SKILL.md, the provided inputs, and local helper logic—there are no instructions to read arbitrary user files, shell history, or transmit data externally.
Install Mechanism
This is effectively instruction-first with small local Python files and no install spec. Nothing is downloaded from external URLs and no archives are extracted. Risk from installation is minimal.
Credentials
The skill declares no required environment variables, credentials, or config paths and the code does not access environment secrets. Requested privileges are proportionate (none).
Persistence & Privilege
always:false and user-invocable defaults are used. The skill does not modify other skills or system-wide settings and does not request permanent presence.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install screen-time-auditor - After installation, invoke the skill by name or use
/screen-time-auditor - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of Screen Time Auditor, a tool for manually auditing and reducing problematic screen habits.
- Helps estimate usage by device/app, identify triggers, and map out worst "leakage zones."
- Guides users to distinguish between functional use and unconscious or emotional screen time.
- Supports creating friction, replacement habits, and realistic phone-free periods.
- Includes a structured workflow and output format for actionable, non-judgmental audit results.
- Emphasizes practical, humane reduction strategies—one week at a time.
Metadata
Frequently Asked Questions
What is Screen Time Auditor?
Help users audit and analyze screen habits by device, app, and time to identify triggers and create a realistic one-week reduction plan. It is an AI Agent Skill for Claude Code / OpenClaw, with 83 downloads so far.
How do I install Screen Time Auditor?
Run "/install screen-time-auditor" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Screen Time Auditor free?
Yes, Screen Time Auditor is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Screen Time Auditor support?
Screen Time Auditor is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Screen Time Auditor?
It is built and maintained by haidong (@harrylabsj); the current version is v1.0.0.
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