Learning Optimizer
v1.0.1Learning optimizer - analyze study patterns, identify inefficiencies, suggest optimizations for better learning outcomes
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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
Name/description (learning optimizer) align with the included code and SKILL.md: analyze, optimize, and allocate commands. No unrelated credentials, binaries, or installs are requested.
Instruction Scope
SKILL.md instructs running the bundled Python script which performs analysis and suggestions. The script only reads CLI inputs and writes local JSON logs (analysis_log.json, optimization_log.json, allocation_log.json). This is consistent with the stated 'No external data collection' constraint, but it does persist user-provided inputs to files on disk — reviewers should be aware of local data retention.
Install Mechanism
No install spec or external downloads; the skill is instruction-only with a bundled Python script. No packages are fetched or executed from remote URLs.
Credentials
The skill requires no environment variables, credentials, or config paths. However, it does persist user-supplied inputs into local log files, which may contain sensitive schedule or performance data—this is expected for the feature but worth noting.
Persistence & Privilege
always is false and the skill does not modify other skills or system settings. It only creates/append local log files in the working directory.
Assessment
This skill appears coherent with its stated purpose and has low risk: it runs a local Python script that analyzes inputs and writes local JSON logs. Before installing or running: (1) inspect scripts/main.py (already provided) to confirm behavior (no network calls or secrets usage); (2) be aware that any personal inputs (schedules, problems, performance data) will be saved to files in the current directory—store/run it in a directory you control and set appropriate filesystem permissions; (3) run as a non-privileged user (not root) to limit impact; (4) if you need to avoid local persistence, modify the script to disable or encrypt logging. If you want additional assurance, run the script in an isolated environment (container or VM) and review or remove the logging lines.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.