Loading...
Loading...
Found 1,953 Skills
Guidelines for creating high-quality datasets for LLM post-training (SFT/DPO/RLHF). Use when preparing data for fine-tuning, evaluating data quality, or designing data collection strategies.
Document chunking implementations and benchmarking tools for RAG pipelines including fixed-size, semantic, recursive, and sentence-based strategies. Use when implementing document processing, optimizing chunk sizes, comparing chunking approaches, benchmarking retrieval performance, or when user mentions chunking, text splitting, document segmentation, RAG optimization, or chunk evaluation.
Iteratively write academic documents (paper sections, research proposals, technical documents) with quality improvement loop. Uses academic-planner for structure design and academic-reviewer for quality evaluation. Ensures no hallucinations through fact verification.
Guides technical evaluation of code review feedback before implementation. Use when receiving PR comments, review suggestions, GitHub feedback, or when asked to address reviewer feedback. Emphasizes verification and reasoned pushback over blind agreement.
MixSeek Agent Skills collection for AI coding assistants. Provides workspace management, team configuration, evaluation setup, and debugging tools for MixSeek-Core.
Run SEO and GEO audits on URLs covering technical SEO, content quality, E-E-A-T signals, and AI citation readiness. Use when evaluating search performance or diagnosing ranking issues.
Software design principles and patterns. This skill should be used when making architectural decisions, designing classes or modules, or evaluating code structure. Use proactively when discussing SOLID principles, coupling, cohesion, connascence, refactoring structure, class design, module boundaries, dependency injection, or the Four Rules of Simple Design. (user)
4-stage funnel that screens all 500+ Hyperliquid perps down to the top trading opportunities. Scores setups 0-400 across smart money, market structure, technicals, and funding. BTC macro filter, hourly trend gate (counter-trend = hard skip), cross-scan momentum tracking. Near-zero LLM tokens — all computation in Python. Use when scanning for new trading opportunities on Hyperliquid, evaluating setups, or checking market conditions.
Analyze and correct previous responses when questioned or when contradictions are detected. Use this skill when the user challenges your reasoning, points out inconsistencies, or asks 'what makes you think that?' to help you review your logic, identify errors in your previous statements, and provide accurate corrections. Useful for maintaining consistency, admitting mistakes, and rebuilding trust through transparent self-evaluation.
Conduct Failure Mode and Effects Analysis (FMEA) for systematic identification and risk assessment of potential failures in designs, processes, or systems. Supports DFMEA (Design), PFMEA (Process), and FMEA-MSR (Monitoring & System Response). Uses AIAG-VDA 7-step methodology with Action Priority (AP) risk assessment replacing traditional RPN. Use when analyzing product designs for potential failures, evaluating manufacturing process risks, conducting proactive risk assessment, preparing for APQP/PPAP submissions, investigating field failures, or when user mentions "FMEA", "failure mode", "DFMEA", "PFMEA", "severity occurrence detection", "RPN", "Action Priority", "design risk analysis", or needs to identify and prioritize potential failure modes with their causes and effects.
Use when evaluating individual Xiaohongshu post performance, identifying what makes content succeed or fail, extracting viral content patterns, recognizing underperforming content that needs optimization, or comparing performance across different content types and formats
Use when calculating marketing ROI on Xiaohongshu, measuring campaign return on investment, analyzing cost per acquisition, evaluating marketing spend efficiency, or proving marketing value to stakeholders