context-engineering
Active context curation to fight context rot. Curates what goes into limited context window from constantly evolving information universe. 39% improvement, 84% token reduction.
Active context curation to fight context rot. Curates what goes into limited context window from constantly evolving information universe. 39% improvement, 84% token reduction.
Use when creating or formatting tables in markdown. Covers table syntax, alignment, escaping, and best practices.
Create interactive chart visualizations (bar, line, pie) from data.
Google web search with integrated image results
Use when Java Streams API for functional-style data processing. Use when processing collections with streams.
Use when validating and casting data with Ecto changesets including field validation, constraints, nested changesets, and data transformation. Use for ensuring data integrity before database operations.
Use when optimizing GraphQL API performance with query complexity analysis, batching, caching strategies, depth limiting, monitoring, and database optimization.
Use when scala collections including immutable/mutable variants, List, Vector, Set, Map operations, collection transformations, lazy evaluation with views, parallel collections, and custom collection builders for efficient data processing.
Create efficient data pipelines with tf.data
Use when Python data modeling with dataclasses, attrs, and Pydantic. Use when creating data structures and models.
Migrate AI image generation from Google Gemini 2.5 Flash to BytePlus SeeDream v4.5. Use when: (1) User wants to switch from Gemini to SeeDream/BytePlus for image generation, (2) User asks about migrating image generation APIs or replacing Gemini with BytePlus, (3) User needs cost optimization or better image quality for AI-generated images, (4) User mentions SeeDream, BytePlus, or wants SDK-to-REST API migration for image generation
Data journalism workflows for analysis, visualization, and storytelling. Use when analyzing datasets, creating charts and maps, cleaning messy data, calculating statistics or building data-driven stories. Essential for reporters, newsrooms and researchers working with quantitative information.
Python data processing pipelines with modular architecture. Use when building content processing workflows, implementing dispatcher patterns, integrating Google Sheets/Drive APIs, or creating batch processing systems. Covers patterns from rosen-scraper, image-analyzer, and social-scraper projects.
Guides VibeCoder (non-technical users) through natural language development. Use when user asks what to do next, how to use the system, needs help, or is stuck. Do NOT load for: technical-user work, direct implementation requests, or reviews.
Calculate sound speed in seawater from practical salinity, temperature, and pressure using the Gibbs Seawater Oceanographic Toolbox.
Query EBI GWAS Catalog for GWAS statistical associations (p-value, effect size, risk allele) between a variant and traits/diseases.
Calculate the freezing point temperature of seawater from absolute salinity and pressure using GSW thermodynamic equations.
Calculate buoyancy forces and acceleration for fluid mechanics and hydrodynamics analysis.
Molecular Docking Pipeline - Complete docking workflow: retrieve protein structure, predict binding pockets, prepare receptor, and dock ligand. Use this skill for structural biology tasks involving retrieve protein data by pdbcode run fpocket convert pdb to pdbqt dock quick molecule docking. Combines 4 tools from 2 SCP server(s).
Run Cadence Spectre simulations remotely via virtuoso-bridge: upload netlists, execute, parse PSF results. TRIGGER when the user wants to run a SPICE/Spectre simulation from a netlist file, do transient/AC/PSS/pnoise analysis outside Virtuoso GUI, parse PSF waveform data, run multiple simulations in parallel across one or more servers, check simulation job status, or mentions Spectre APS/AXS modes. Also triggers for sim-jobs, sim-cancel, or parallel/concurrent simulation requests. Use this for standalone netlist-driven simulation — for GUI-based ADE Maestro simulation, use the virtuoso skill instead.
The olm:v5 migration script, UpdateTagsService, batch processing, migrated_at, ClassifyTagsService deprecated mappings, and data migration from v4 category tables.
深度调研主题并自动生成知识关系图谱PDF。接收研究主题后自动进行网络调研、信息收集、知识整理,最终生成专业的可视化关系图谱。适用于"研究...并做图"、"深度分析...并可视化"、"生成知识图谱"等场景。
Guidance for creating effective prompts, chains, and gates using CAGEERF methodology
Best practices for integrating TanStack Query with TanStack Router and TanStack Start. Patterns for full-stack data flow, SSR, and caching coordination.