Build vector search that considers both semantic similarity and patterns in how items connect. Use graph features to explore structure in embeddings, numerical representations of content, and compare retrieval results with conventional similarity search.
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- Investigate structure missed by cosine similarity
- Include contextual roles in RAG retrieval
- Compare graph-based and cosine search results
sickn33/agentic-awesome-skills☆ 4.8万2026年10月19日 更新
Examine recorded calls and voicemails for signs of AI-generated speech. Extract acoustic features, classify samples with machine learning, and prepare reports with confidence scores and sound visualizations to support voice impersonation investigations.
中文简介正在准备中。当前显示英语简介。
- Investigating calls impersonating executives
- Checking suspicious voicemails
- Comparing suspect recordings with genuine voice samples
mukul975/Anthropic-Cybersecurity-Skills☆ 3.5万2026年8月31日 更新
Spectral vector search using graph Laplacian eigenstructure. Use when cosine/L2 similarity misses latent structure in your embeddings.
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lingxling/awesome-skills-cn☆ 3122026年10月7日 更新
Spectral vector search using graph Laplacian eigenstructure. Use when cosine/L2 similarity misses latent structure in your embeddings.
中文简介正在准备中。当前显示原文说明。
JantonioFC/skillsbank☆ 92026年8月4日 更新
Detects AI-generated deepfake audio used in voice phishing (vishing) attacks by extracting spectral features (MFCC, spectral centroid, spectral contrast, zero-crossing rate) and classifying samples with machine learning models. Supports batch analysis of audio files, generates confidence scores, and produces forensic reports. Activates for requests involving deepfake voice detection, vishing investigation, AI-generated speech analysis, voice cloning detection, or audio authenticity verification.
中文简介正在准备中。当前显示原文说明。
andycungkrinx91/konoha☆ 92026年10月19日 更新
Detects AI-generated deepfake audio used in voice phishing (vishing) attacks by extracting spectral features (MFCC, spectral centroid, spectral contrast, zero-crossing rate) and classifying samples with machine learning models. Supports batch analysis of audio files, generates confidence scores, and produces forensic reports. Activates for requests involving deepfake voice detection, vishing investigation, AI-generated speech analysis, voice cloning detection, or audio authenticity verification.
中文简介正在准备中。当前显示原文说明。
micsapp/micstec-skills☆ 42026年3月20日 更新
Frequency-domain analysis — FFT, power spectral density (Welch/periodogram), spectrograms, wavelet transforms, and coherence. Use for any signal with periodic, quasi-periodic, or transient frequency content in physics data.
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huang-sh/DeepScience☆ 42026年7月15日 更新
Detects AI-generated deepfake audio used in voice phishing (vishing) attacks by extracting spectral features (MFCC, spectral centroid, spectral contrast, zero-crossing rate) and classifying samples with machine learning models. Supports batch analysis of audio files, generates confidence scores, and produces forensic reports. Activates for requests involving deepfake voice detection, vishing investigation, AI-generated speech analysis, voice cloning detection, or audio authenticity verification.
中文简介正在准备中。当前显示原文说明。
aniket2348823/Vul-Agent☆ 22026年6月9日 更新