Agent Skills

Build production-ready LLM applications, advanced RAG systems, and

When the user wants backlink analysis, link gap analysis, competitor link profiles, referring domain data, or link building research. Trigger on "backlinks," "who links to," "link profile," "referring domains," "link gap," "Ahrefs," "link building research," or "why do they outrank me" (often a link authority issue).

Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations (for example: Codex, Responses API, Chat Completions, Apps SDK, Agents SDK, Realtime, model capabilities or limits); prioritize OpenAI docs MCP tools and restrict any fallback browsing to official OpenAI domains.

Archive session learnings, debugging solutions, and deployment logs to .archive/yyyy-mm-dd/ as indexed markdown with searchable tags. Use when completing a significant task, resolving a tricky bug, deploying, or when the user says \"archive this\". Maintains .archive/MEMORY.md index for cross-session knowledge reuse.

Implement secure API design patterns including authentication, authorization, input validation, rate limiting, and protection against common API vulnerabilities

Your agent has zero users. This fixes that. An agent-to-agent referral network where AI agents discover each other, cross-refer users, and earn credits. Available as an MCP server and HTTP API. Built by an AI agent that couldn't find its own customers. Published as io.github.oxgeneral/agentnet v1.0.0 You built an agent. It works. Nobody uses it. - 3M+ GPTs on OpenAI — most have zero users - 17,000

🚀 MCP Server Available: Install the Model Context Protocol server for AI Distiller from NPM: @janreges/ai-distiller-mcp - seamlessly integrate with Claude, Cursor, and other MCP-compatible AI tools! /.aid/ regardless of where you run aid - Cache management: MCP cache stored in .aid/cache/ for better organization - Easy cleanup: Add .aid/ to .gitignore to keep outputs out of version control Detect

Research a topic from the last 30 days on Reddit + X + Web, become an expert, and write copy-paste-ready prompts for the user's target tool.

Lint any URL for LLM readiness. Get a 0-100 score for token efficiency, RAG readiness, agent compatibility, and LLM extraction quality. Context CLI is an LLM Readiness Linter that checks how well a URL is structured for AI consumption. As LLM-powered search engines, RAG pipelines, and AI agents become primary consumers of web content, your pages need to be optimized for token efficiency, structure

Multi-agent AI consultation framework for Claude Code via MCP. Get a second (and third) opinion from other LLMs when Claude Code alone isn't enough. Claude Code is powerful, but one brain can miss bugs, overlook edge cases, or get stuck in a local optimum. Critical decisions benefit from diverse perspectives. Concilium runs parallel consultations with multiple LLMs through standard MCP protocol. E

Seamlessly integrate Anki with AI assistants through the Model Context Protocol Beta - This project is in active development. APIs and features may change. A Model Context Protocol (MCP) server that enables AI assistants to interact with Anki, the spaced repetition flashcard application. Transform your Anki experience with natural language interaction - like having a private tutor. The AI assistan

All servers: 100 vendors, US region, individual plans, stateless, no auth, 100 req/min. Start local dev server: In a separate terminal: Use workflow endpoints when you want one request to return: - decision classification (yes | no | tie) from /api/decide - policy result from the relevant notary endpoint - recommended Zendesk action + tags + private note with requestid - POST https://refund.decide

Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector stores), and the cognitive architectures that organize them. Key insight: Memory isn't just storage - it's retrieval. A million stored facts mean nothing if you can't find the right one. Chunking, embedding, and retrieval strategies determine whether your agent remembers or forgets. The field is fragm

Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability.

Automate Airtable tasks via Rube MCP (Composio): records, bases, tables, fields, views. Always search tools first for current schemas.

English | 简体中文 🧠 The data layer for AI systems. Skill Seekers turns any documentation, GitHub repo, or PDF into structured knowledge assets—ready to power AI Skills (Claude, Gemini, OpenAI), RAG pipelines (LangChain, LlamaIndex, Pinecone), and AI coding assistants (Cursor, Windsurf, Cline) in minutes, not hours. Skill Seekers is the universal preprocessing layer that sits between raw documentatio

GitHub patterns using gh CLI for pull requests, stacked PRs, code review, branching strategies, and repository automation. Use when working with GitHub PRs, merging strategies, or repository management tasks.

Curated collection of high-quality prompts for various use cases. Includes role-based prompts, task-specific templates, and prompt refinement techniques. Use when user needs prompt templates, role-play prompts, or ready-to-use prompt examples for coding, writing, analysis, or creative tasks.

Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use when architecting complex backend systems or refactoring existing applications for better maintainability.

AI Engine Optimization - semantic triples, page templates, content clusters for AI citations

You are an accessibility expert specializing in WCAG compliance, inclusive design, and assistive technology compatibility. Conduct audits, identify barriers, and provide remediation guidance.

This skill should be used when the user asks to "attack Active Directory", "exploit AD", "Kerberoasting", "DCSync", "pass-the-hash", "BloodHound enumeration", "Golden Ticket", "Silver Ticket", "AS-REP roasting", "NTLM relay", or needs guidance on Windows domain penetration testing.

Optimize end-to-end application performance with profiling, observability, and backend/frontend tuning. Use when coordinating performance optimization across the stack.

Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks Use when: agent testing, agent evaluation, benchmark agents, agent reliability, test agent.