Motor Parameter Calculator

v1.2.0

电机设计参数计算助手 | 根据基本参数计算极槽配合、匝数、磁密、反电动势等核心设计数据

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MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
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high confidence
Purpose & Capability
The name/description, SKILL.md examples, and the included Python script all implement motor design calculations (pole/slot, winding factor, flux, Ke/Kt, slot-sweep). The presence of an additional Node script (calculator.js) is a minor mismatch with SKILL.md (which only documents the Python script) but is explainable as an alternative implementation rather than malicious or unrelated functionality.
Instruction Scope
SKILL.md instructs running the local Python script (scripts/param_calculator.py) and using its interactive or sweep modes. The instructions only read user-provided parameters (command-line args or interactive input) and do not direct the agent to read unrelated files, environment variables, or to transmit data externally.
Install Mechanism
There is no install spec (instruction-only). Code files are bundled with the skill and run locally. The Python script optionally imports numpy/matplotlib for plotting if available — these are standard scientific libraries. No external downloads, URLs, or archive extraction are used.
Credentials
The skill declares no required environment variables, no credentials, and no config paths. The runtime code does not read environment secrets or system config. Optional third-party libraries (numpy/matplotlib) are the only external dependencies and are appropriate for numeric/plotting tasks.
Persistence & Privilege
always is false and the skill does not request persistent or elevated agent/system privileges. The code prints results and, aside from optional plotting, does not modify system-wide configuration or other skills.
Assessment
This package appears to be a straightforward local motor-parameter calculator. Before running it: (1) Inspect the bundled files (scripts/param_calculator.py and calculator.js) yourself — calculator.js is present but not mentioned in SKILL.md; confirm you trust its contents. (2) Run the Python script in a virtual environment (pip install numpy matplotlib if you want plotting) to avoid polluting your system. (3) Because the skill runs locally and prompts for inputs, provide only non-sensitive example values when testing. (4) The package metadata shows minor version/metadata mismatches (_meta.json version 1.0.0 vs registry 1.2.0); this is likely harmless but worth noting. If you need remote/automated execution in an environment with sensitive data, consider sandboxing or code review first.

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.

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