midasheng-audio-denoise
v1.0.0Voice enhancement and noise reduction service. Accepts a noisy audio file and returns a clean, denoised version. Use when user needs to remove background noi...
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byJunbo Zhang@jimbozhang
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
medium confidencePurpose & Capability
Name, description, SKILL.md, and the included script consistently implement an audio denoise client that uploads a file to https://llmplus.ai.xiaomi.com/dasheng/audio/denoise and returns a WAV. The requested resources (no env vars, no unusual binaries) are proportionate to the described task.
Instruction Scope
Instructions and the script only perform network calls to the Xiaomi endpoint and a metrics endpoint, and read the provided input audio file and write an output WAV. They do not access other system files or credentials. However, the skill requires uploading user audio to a third-party service (privacy risk) — this is expected for a cloud denoise service but should be considered by the user.
Install Mechanism
No install spec; this is instruction-only with a bundled Python script. Nothing is downloaded or executed automatically beyond what the user runs. Low installation risk.
Credentials
The skill declares no environment variables or credentials, which is proportionate. Minor inconsistency: SKILL.md top lists 'requirements: curl' and examples use curl, but the provided script uses Python's requests library — requests is not declared as a dependency and may not be present in runtime.
Persistence & Privilege
Skill does not request always:true or modify agent/system configs. It is user-invocable and uses normal agent invocation permissions.
Assessment
This skill uploads the user's audio to https://llmplus.ai.xiaomi.com (a Xiaomi-hosted API) for processing. If your audio contains sensitive or private information, do not use the skill unless you trust that endpoint and its privacy policy. Also note the script uses Python's 'requests' but the SKILL.md mentions curl — ensure your environment has Python and requests installed before running, or use the curl example. If you need local-only processing for privacy, prefer a local denoising tool or verify the service's data retention and handling policies. Finally, because the skill's source/homepage is absent, consider testing with non-sensitive samples first and verifying the endpoint ownership if you require higher assurance.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.