neural-learning-engine
v1.0.0Simulates a neural network learning loop by detecting input patterns, storing them in memory, and generating improved, adaptive responses over time.
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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 and description match the SKILL.md content: a conceptual pipeline (Input → Processing → Memory → Output) for simulating pattern detection and adaptive responses. Nothing in the metadata or SKILL.md asks for unrelated resources or permissions.
Instruction Scope
Instructions are high-level and purely conceptual; they do not include commands, file I/O, network calls, or explicit persistence mechanics. The SKILL.md repeatedly references storing patterns in 'memory' but does not specify how or where memory is persisted (agent memory, external DB, file), leaving implementation details to the host agent.
Install Mechanism
No install spec and no code files (instruction-only). This minimizes disk writes and supply-chain risk; there are no third-party downloads or package installs to evaluate.
Credentials
The skill declares no required environment variables, credentials, or config paths. That matches the instruction-only nature and the absence of external integrations in the runtime instructions.
Persistence & Privilege
always:false and default autonomous invocation are set (normal). The skill does not request permanent presence or attempt to modify system or other skills' configurations. Note: because it references 'memory', any persistence will depend on the agent's own memory storage policy, not the skill itself.
Assessment
This skill is a conceptual recipe rather than runnable code. It does not request permissions or install anything, so the direct security risk is low. Before relying on it in production, decide how you want 'memory' implemented (ephemeral agent memory vs. a persistent database), and if you add external integrations (APIs, storage), require explicit environment variables and review those additions. Also be mindful of privacy: if the agent persists user inputs/patterns, make sure you have retention and data-protection policies in place.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.