Restaurant Operations
v1.0.0Provide precise, data-driven restaurant operations advice based on concept, location, and challenges using industry benchmarks and key performance metrics.
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by@1kalin
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
The name and description (restaurant operations advice using benchmarks and KPIs) match the SKILL.md and README content. All tables and frameworks are directly relevant to providing operational guidance; there are no unrelated requirements (no cloud creds, no system binaries).
Instruction Scope
The SKILL.md tells the agent to analyze user-provided restaurant information using the included frameworks and to provide numeric, data-driven guidance. It does not instruct the agent to read local files, environment variables, or other system state, nor to transmit data to external endpoints from within the skill. The README contains links to external AfrexAI resources, but the skill itself is instruction-only and does not include automation steps that would access those services.
Install Mechanism
No install specification and no code files are present. Being instruction-only means nothing is written to disk and no external packages are pulled in by the skill itself.
Credentials
The skill requires no environment variables, credentials, or config paths. There are no requests for SECRET/TOKEN/PASSWORD variables, which is proportionate to a guidance-only skill.
Persistence & Privilege
always is false and there is no install logic that modifies agent configuration or other skills. The skill can be invoked by the agent (default behavior) — this is normal for skills and not a concern here because the skill has no external hooks or elevated privileges.
Assessment
This skill is structurally coherent and low-risk as shipped: it only provides frameworks and benchmarks. Before installing, consider: (1) provenance — the package source and homepage are missing (verify the author or test on non-sensitive data); (2) data accuracy — cross-check critical benchmarks against trusted industry sources and local regulations (health code fines and labor rules vary by jurisdiction); (3) privacy — do not feed personally identifying or financial credentials (employee SSNs, payroll account numbers, bank details) into the skill output or prompts; (4) scope — the README links to external AfrexAI automation resources, but this package does not perform automation itself — if you later integrate with automation/context packs, review those components for installs, credentials, and network endpoints. If you need higher assurance, ask the publisher for source provenance or a changelog before deploying in production.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.
