Habit Stack Designer
v1.0.0Design a habit stack by choosing a reliable existing anchor, shrinking the new habit into a tiny first action, and adding friction reduction, reward, and a r...
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byhaidong@harrylabsj
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
Capability signals
These labels describe what authority the skill may exercise. They are separate from suspicious or malicious moderation verdicts.
OpenClaw
Benign
high confidencePurpose & Capability
The name/description, SKILL.md, and handler.py all align: the skill analyzes a user-provided habit description and returns a habit-stack design. It doesn't request unrelated credentials, binaries, or config paths. The included rule lists and templates are appropriate for generating the described outputs.
Instruction Scope
SKILL.md explicitly states the skill is descriptive only and does not create reminders or external automation. The runtime code only normalizes input, extracts keywords, and renders a markdown output. It reads its bundled SKILL.md (local file) for metadata but does not read other system files, environment variables, or transmit data externally.
Install Mechanism
There is no install spec; the skill is instruction/code-only and does not download or install third-party packages or binaries. No extract/download URLs or package registry installs are present.
Credentials
The skill requires no environment variables, credentials, or config paths. All data is derived from the provided input string and internal templates, so requested privileges are proportional to the functionality.
Persistence & Privilege
always is false and the skill does not request persistent system presence or modify other skills. disable-model-invocation is false (normal), but that is not combined with other risky behaviors here.
Assessment
This skill appears coherent and low-risk: it only analyzes text and emits a markdown habit-stack design, and it does not request credentials or access external endpoints. If you plan to enable autonomous invocation for agents generally, be aware the platform could call the skill without each explicit prompt (the skill itself is harmless). If you have strong operational security requirements, you can review the small handler.py (it only uses local templates and keyword matching) or run it in a sandbox before enabling it for production agents. Avoid sending highly sensitive personal data in free-form inputs (unnecessary for a habit design).Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.