Loading...
Loading...
Found 168 Skills
[Hyper] Create and refactor AI-readable docs, instruction bases, runbooks, specs, and harness-ready rule packs for context, prompt, tool, eval, sourcing, safety, and validation workflows.
Prompt engineering standards and context engineering principles for AI agents based on Anthropic best practices. Covers clarity, structure, progressive discovery, and optimization for signal-to-noise ratio.
AI Agent Harness Design Patterns - Memory, Permission, Context Engineering, Delegation, Skill, Hook, Bootstrap. Chinese Version.
Comprehensive guide to understanding and implementing AI agent systems using Claude Code architecture patterns
Generate a test suite of natural-language → SQL pairs that becomes the quality benchmark for a nao agent, then run it via `nao test`. Use when the user wants to start measuring agent reliability, extend an existing test suite, or add tests for new metrics. Tests are the only honest answer to "is the context working?". Do not use for writing rules (write-context-rules) or diagnosing failures (audit-context).
Best practices for prompt engineering and context engineering for Coding Agent prompts
This skill should be used when the user asks to "optimize CLAUDE.md", "create a new skill", "write a custom agent", "configure hooks", "manage context window", "set up MCP servers", "scaffold a skill package", "analyze token budget", "create subagents", "configure permissions", "set up worktrees", or "integrate Claude Code with editors". Use for Claude Code CLI mastery, skill authoring, context engineering, hooks automation, subagent creation, and development workflow optimization.
Optimize and structure context for agents and LLMs by reducing noise, prioritizing relevance, organizing memory, defining constraints, and managing token budgets.
Recognize, diagnose, and mitigate patterns of context degradation in agent systems. Use when context grows large, agent performance degrades unexpectedly, or debugging agent failures.
Senior AI Product Manager. Expert in Probabilistic Strategy, Rapid Agentic Prototyping, and Hypothesis Generation for 2026.
Elite AI context engineering specialist mastering dynamic context management, vector databases, knowledge graphs, and intelligent memory systems. Orchestrates context across multi-agent workflows, enterprise AI systems, and long-running projects with 2024/2025 best practices. Use PROACTIVELY for complex AI orchestration.
Manus-style context engineering for Agent Teams. Coordinate multiple Claude Code instances with shared planning files. Use when complex tasks need parallel work (code review, debugging, feature development). Requires CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1.