Generate localized cover images and reusable image prompts from the shared Punk style library for articles, Xiaohongshu notes, WeChat…
AI-assisted safety layer for git push operations with quality gates and collaboration guardrails.
Push to remote and monitor CI. Validates branch safety, executes git push WITH explicit user approval, then monitors CI run status via gh…
When to activate: push notifications, UserNotifications framework, APNs, notification content extensions, rich notifications, notification…
This skill should be used when the user wants to create a pull request, or submit code for review.
Automate Pushover tasks via Rube MCP (Composio).
Guides the structured engineering workflow for binary vulnerability analysis, debugging, and proof-of-concept stabilization.
Generate synthetic evaluation datasets for the PXI eval harness (evals/pxi/).
When to activate: Pydantic v2, data validation, serialization, settings management, pydantic-settings, field validators
Python library for working with DICOM (Digital Imaging and Communications in Medicine) files.
Fast high-dimensional fixed effects: OLS, Poisson, IV with multi-way FE; DiD (TWFE, did2s, Sun-Abraham); clustered SEs…
Comprehensive healthcare AI toolkit for developing, testing, and deploying machine learning models with clinical data.
Guides the agent on how to run clean python styling, Black/Ruff compliance checks, and pytest execution on changed python scripts.
Pythia event generation skill for proton-proton and lepton collisions at high energies
When to activate: httpx, API clients, retry logic, auth headers, rate limiting client-side, OpenAPI client generation
Best practices, common mistakes, decision guidance, and checklists for async Python, asyncio, and FastAPI — covering single-instance code…
Curated bundle of essential Python backend development skills.
When to activate: ARQ, RQ, background workers, Redis-based queues, async task workers
When to activate: Redis, caching strategies, cache-aside, TTL, cache invalidation, aiocache, cache decorators
Guidance for writing, reviewing, and refactoring Python code with clear style, naming, design principles, and testing discipline.
Reviews Python code for type safety, async patterns, error handling, and common mistakes.