Agent Skills Hub

research-pipeline

End-to-end autonomous research agent: from idea generation and literature review to experiment execution, adversarial review loops, and paper writing.

box-least-squares

BLS periodogram tool for detecting transiting exoplanets and eclipsing binaries in photometric light curves. An astropy-based implementation for period, duration, and depth analysis.

prompt-writing

Create, refine, and optimize high-quality YAML prompts for AI assistants using structure guidelines, template patterns, and quality standards.

performance-analysis

Systematic performance engineering: baseline measurement, profiling, bottleneck diagnosis, and evidence-based optimization guidance for high-performance applications.

cn-daily-tools

An all-in-one Chinese daily utility toolkit: weather, currency exchange, news, and package tracking. Zero configuration, no API keys required.

skill-reinforcement

An automated meta-learning skill that improves agent workflows by capturing patterns, failures, and shortcuts after each task execution.

feature-dev

Guided, systematic feature development agent that orchestrates codebase exploration, architectural design, implementation, and automated testing.

massgen-config-creator

Guide for creating properly structured YAML configuration files for MassGen. Use this when creating new configs for examples, case studies, testing, or feature demonstrations.

semgrep-rule-variant-creator

Port Semgrep rules to new languages using a strict, test-driven methodology. Includes applicability analysis, AST-based translation, and automated validation for each target language.

alphaear-deepear-lite

Fetch real-time financial signals, transmission-chain reasoning, and market confidence metrics directly from the DeepEar Lite platform.

ai-llm-patterns

Anthropic Claude integration patterns: streaming, RAG with pgvector, tool use, model selection (Haiku/Sonnet/Opus), prompt caching, and cost management for AI-powered engineering.

data-cleaning-pipeline-generator

Generates data cleaning pipelines for pandas/polars/PySpark, handling missing values, duplicates, outliers, type conversions, and validation.