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Found 779 Skills
Pre-landing PR review. Analyzes diff against the base branch for SQL safety, LLM trust boundary violations, conditional side effects, and other structural issues.
Terminal tool that detects your hardware and recommends which LLM models will actually run well on your system
Ultra-lightweight AI assistant in Go that runs on $10 hardware with <10MB RAM, supporting multiple LLM providers, tools, and single-binary deployment across RISC-V, ARM, MIPS, and x86.
Personal intelligence agent that aggregates 27 OSINT data sources into a self-hosted Jarvis-style dashboard with Telegram/Discord bots, LLM analysis, and real-time alerts.
Guides LLM agents through large-scale coding tasks using a spec-driven, phase-by-phase methodology covering requirement definition, planning, algorithm design, and implementation with OOP principles and language-specific coding standards. Use when starting a new software project, implementing a complex feature, refactoring existing code, or when you need a disciplined step-by-step approach to any non-trivial coding task.
Run 397B parameter Mixture-of-Experts LLMs on a MacBook using pure C/Metal with SSD streaming
Behavioral compliance testing for any CLAUDE.md or agent definition file. Auto-generates test scenarios from your rules, runs them via LLM-as-judge scoring, and reports compliance. Optionally improves failing rules via automated mutation loop.
Official Reference Guide for the PPIO Platform, covering LLM API (OpenAI-compatible), Agent Sandbox, GPU (Instances and Serverless), integration, authentication, pricing, rate limiting, and troubleshooting. Suitable for common questions such as 'How to integrate PPIO in specific application scenarios?' and PPIO request failures.
Reduce LLM API and infrastructure costs through model selection, prompt caching, batching, caching, quantization, and self-hosting strategies. Track spend by team and model, set budgets, and implement cost-aware routing.
How to access SuprSend documentation and get support. Includes docs site, LLM-friendly doc endpoints, in-app chat, AI copilot, Slack community, and email support.
Fetch and compile arXiv papers on LLMs, autonomous agents, and AI infrastructure into scored, grouped research digests. Stores digests at ~/.aibtc/arxiv-research/digests/. No API key required.
Creates a reusable use case specification file that defines the business problem, stakeholders, and measurable success criteria for model customization, as recommended by the AWS Responsible AI Lens. Use as the default first step in any model customization plan. Skip only if the user explicitly declines or already has a use case specification to reuse. Captures problem statement, primary users, and LLM-as-a-Judge success tenets.