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Found 22 Skills
Spec-driven development orchestration with context engineering for solo developers. Prevents context rot through fresh subagent contexts and atomic task execution. Use when: starting projects, planning features, executing development phases, or when user says "gsd", "plan", "new project", "execute phase". Triggers: /gsd init, /gsd plan, /gsd execute, /gsd status, /gsd verify
Repository structure methodology for maximum AI agent effectiveness. Three pillars — context engineering (repo as knowledge product), architectural constraints (deterministic enforcement), garbage collection (active entropy fighting). Use when setting up repos for AI development, diagnosing repeated agent failures, writing AGENTS.md, or designing CI gates and structural tests.
Comprehensive guide to understanding and implementing AI agent systems using Claude Code architecture patterns
Strategies for managing LLM context windows effectively in AI agents. Use when building agents that handle long conversations, multi-step tasks, tool orchestration, or need to maintain coherence across extended interactions.
Comprehensive prompt and context engineering for any AI system. Four modes: (1) Craft new prompts from scratch, (2) Analyze existing prompts with diagnostic scoring and optional improvement, (3) Convert prompts between model families (Claude/GPT/Gemini/Llama), (4) Evaluate prompts with test suites and rubrics. Adapts all recommendations to model class (instruction-following vs reasoning). Validates findings against current documentation. Use for system prompts, agent prompts, RAG pipelines, tool definitions, or any LLM context design. NOT for running prompts, generating content, or building agents.
AI Agent Harness Design Patterns - Memory, Permission, Context Engineering, Delegation, Skill, Hook, Bootstrap. Chinese Version.
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).
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.
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.