A platform-neutral analytical skill that profiles messy data, selects adaptive methods, and produces source-backed visual reports for high-stakes decisions.

A plugin for Claude Code that adds a router, specialist agents, skills, and workflows to engineer the loop and persist artifacts across runs.

When the user needs to generate, iterate, or scale ad creative for paid advertising. Use when they say 'write ad copy,' 'generate headlines,' 'create ad variations,' 'bulk creative,' 'iterate on ads,' 'ad copy validation,' 'RSA headlines,' 'Meta ad copy,' 'LinkedIn ad,' or 'creative testing.' This is pure creative production — distinct from paid-ads (campaign strategy). Use ad-creative when you need the copy, not the campaign plan.

OpenSPG is a Knowledge Graph Engine developed by Ant Group in collaboration with OpenKG, based on the SPG (Semantic-enhanced Programmable Graph) framework. Core Capabilities: 1) domain model constrained knowledge modeling, 2) facts and logic fused representation, 3) natively support KAG...

Practical Claude Code runbooks for clean, resource-efficient open-source development - from planning and implementation to debugging, review, release, and deployment

Pycopy - a minimalist and memory-efficient Python dialect. Good for desktop, cloud, constrained systems, microcontrollers, and just everything.

Generates, optimizes, and validates Cypher 25 queries for Neo4j 2025.x and 2026.x.

Place one consent-first CALL-E callback after a local safety gate has already blocked an extreme-risk developer action, so a known project owner can say stop or request normal review without granting the agent destructive permission.

Scraping + AI-provider standards — the Scraper trait & SCRAPERS registry, selector resilience, rate-limiting/cancellation, and the provider-abstraction (zero-change) rule for embeddings/streaming/prompts. Load for changes under scraping/, ai_provider/, packages/prompts, documents/embed.

Robotics tools in C++11. Implements soft real time arm drivers for Kuka LBR iiwa plus V-REP, ROS, Constrained Optimization based planning, Hand Eye Calibration and Inverse Kinematics integration.

Use when the user wants to deeply learn a new topic from scratch. Runs a pre-interview (current knowledge, end-goal proficiency, depth, practice load, background, scope), researches online (articles, niche-influencer blogs, canonical docs, subtopic landscape), then produces a structured markdown course with mandatory visual diagrams, evidence-based learning-science features (retrieval practice, spaced callbacks, worked-example fading, concept ledger, jargon gate, analogy hygiene), and a self-contained interactive HTML mini-course. Triggers on /teach-me, "teach me about X", "I want to learn X", "deep dive on X", "create a course on X", "study X with me".

Constrained and Unconstrained Risk Budgeting / Risk Parity Allocation in Python