Results for “hn”

11 skills

Qdrant Search Quality Diagnosis

Diagnoses Qdrant search quality issues by isolating causes like HNSW approximation, quantization, embedding model, or search pipeline problems.

Browse Hacker News feeds and stories from the command line, including top, new, best, ask, show, jobs, story details with comments, and search.

Qdrant Indexing Performance Optimization

Diagnoses and resolves slow Qdrant indexing and data ingestion by optimizing batching, sharding, HNSW parameters, and payload indexing strategies.

Qdrant Search Quality

Diagnoses and improves Qdrant search relevance by isolating embedding model, configuration, or query strategy issues.

More results

Qdrant Minimize Latency

Guides optimization of Qdrant query latency by tuning segments, memory, quantization, and search parameters.

Qdrant Search Speed Optimization

Diagnoses and resolves slow Qdrant search performance issues including high latency, low throughput, and slow filtered searches.

Performs HLA allele genotyping from WGS/WES VCF data, producing a structured markdown report and machine-readable JSON results.

Aicoin Hyperliquid

This skill should be used when the user asks about Hyperliquid whale positions, Hyperliquid liquidations, Hyperliquid open interest, Hyperliquid trader analytics, Hyperliquid taker data, smart money on Hyperliquid, or any Hyperliquid-specific query. Use when user says: 'Hyperliquid whales', 'HL whale positions', 'HL liquidations', 'HL open interest', 'HL trader', 'smart money', 'Hyperliquid大户', 'HL鲸鱼', 'HL持仓', 'HL清算', 'HL持仓量', 'HL交易员'. For general crypto prices/news, use aicoin-market. For exchange trading, use aicoin-trading. For Freqtrade, use aicoin-freqtrade.

Qdrant Memory Usage Optimization

Diagnoses and reduces Qdrant memory usage by analyzing resident memory, page cache, and providing optimization techniques like quantization, on-disk storage, and async_scorer.

jrennie99-glitch

Vector embeddings with HNSW indexing, sql.js persistence, and hyperbolic support. 75x faster with agentic-flow integration. Use when: semantic search, pattern matching, similarity queries, knowledge retrieval. Skip when: exact text matching, simple lookups, no semantic understanding needed.

Qdrant Vertical Scaling

Guides vertical scaling decisions for Qdrant vector databases, covering when to scale up, how to resize nodes in Qdrant Cloud or self-hosted deployments, RAM sizing formulas, and when to switch to horizontal scaling.