Parfait Charts
v1.0.0Stacked bar charts showing composition and performance. Use for analyzing structure and trends.
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by@linuszz
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
Name and description describe creating stacked composition/performance charts and the SKILL.md contains templates and examples for exactly that. There are no unrelated required binaries, environment variables, or config paths.
Instruction Scope
Instructions are narrowly scoped to producing chart analyses and include an explicit template and output format. They do use a generic placeholder ($ARGUMENTS) and don't specify how data is supplied or validated, so callers should confirm what input the agent will be provided (avoid giving it private files or credentials). No instructions read files, access env vars, or transmit data to external endpoints.
Install Mechanism
No install spec and no code files — this is an instruction-only skill. That is the lowest-risk install profile (nothing is written to disk).
Credentials
The skill declares no environment variables, credentials, or config paths. There is no disproportionate request for secrets or system access relative to the stated purpose.
Persistence & Privilege
always:false (default) and user-invocable. It does not request permanent presence or any modifications to other skills or system-wide settings. Note: the platform default allows autonomous invocation; that normal capability is not by itself a problem here.
Assessment
This skill is a simple, coherent template for producing stacked-bar (parfait) chart analyses and appears safe to install. Before using it, decide how the agent will receive data: avoid supplying sensitive files or credentials as the SKILL.md does not define data sources or validation. Test the skill with non-sensitive sample data to confirm output shape and ensure the agent does not attempt to fetch external resources or access unrelated system files. If you need the agent to work with private datasets, prefer explicitly-scoped data-provision steps and review any future updates that add install scripts or environment requirements.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.