predictive-scaler
v1.0.0Analyze resource usage patterns and predict future scaling needs using trend analysis and forecasting methods for capacity planning and auto-scaling decisions.
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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/description (predictive scaling, capacity planning) align with the included SKILL.md and index.js implementation: moving averages, linear regression, exponential smoothing, multi-resource prediction, and recommendation logic. The code implements the documented APIs and outputs.
Instruction Scope
SKILL.md instructs loading the local module and calling prediction functions with historical data. The instructions and code operate entirely on input arrays and return recommendations; there are no steps that read unrelated files, environment variables, or send data to external endpoints.
Install Mechanism
There is no install spec and package.json has no dependencies. The skill is instruction-only with an included index.js; nothing is downloaded or executed from remote URLs and no archive extraction is present.
Credentials
The skill does not declare or use environment variables, credentials, or config paths. The code does not reference process.env or other secret sources, so requested access is minimal and proportionate.
Persistence & Privilege
Flags indicate normal invocation (not always: true). The skill does not modify agent/system configuration, does not persist credentials, and requires explicit invocation; no elevated persistence or privileges are requested.
Assessment
This skill appears to be a straightforward local forecasting module. Before installing or using it in production: (1) review and test predictions with your real workloads in a staging environment to tune thresholds and horizons, (2) validate input sanitization if you pass non-normalized values (the code clamps values to 0-1 but you should confirm behavior for your metrics), and (3) if you plan to integrate it into automation that performs scaling actions, ensure you add safeguards (rate limits, cooldowns, manual approvals) because recommendations are based on statistical heuristics and can be wrong during bursty/volatile periods. If you require external integrations or cloud credentials later, ensure those are provided only to modules that clearly need them.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.