design-agent-native
Build applications where agents are first-class citizens. Use this skill when designing autonomous agents, creating MCP tools, implementing self-modifying systems, or building apps where features are outcomes achieved by agents operating in a loop.
npx skills add majiayu000/claude-skill-registry --skill design-agent-native --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
What it does
The skill instructs building applications where agents are first-class, enabling autonomous agents to achieve outcomes through a loop using atomic tools. It emphasizes parity between UI actions and agent capabilities, granular tool primitives, and prompt-based feature definition that the agent implements by operating in loops until outcomes are reached. It also covers open-ended capability emergence and incremental improvement without code changes, including self-modification concepts and a focus on domain tools and execution patterns.
How it works
The skill lays out core principles: parity (UI actions must be achievable by tools), granularity (tools are atomic primitives; features are outcomes described in prompts), and composability (new features via prompts without code). It promotes designing with atomic tools (read_file, write_file, list_files, etc.), writing a system prompt that directs the agent to perform steps toward an outcome, and allowing the agent to operate in a loop until complete_task is invoked. It discusses context maintenance, prompt refinement, and emergent capabilities where the agent can fulfill open-ended domain requests by using available tools in sequence and iteration.
When to use it
Use when designing autonomous agents, MCP tools, self-modifying systems, or apps where features are outcomes achieved by agents in a loop. Intended for environments where you want the agent to pursue outcomes via tool use and iterative reasoning rather than a fixed script.
What it can touch
Tools are described as atomic primitives (e.g., read_file, write_file, list_files, complete_task). The agent operates with a loop using these tools to accomplish outcomes, guided by the system prompt and prompts describing desired features.
Caveats
The material discusses self-modification and safety rails as advanced concepts. It emphasizes designing with atomic tools and a parity-driven approach, but does not guarantee outcomes beyond the stated loop behavior (complete_task signaling). License is MIT as per the skill metadata.
<why_now> ## Why Now Software agents work reliably now. Claude Code demonstrated that an LLM with access to bash and file tools, operating in a loop until an objective is achieved, can accomplish complex multi-step tasks autonomously. The surprising discovery: **a really good coding agent is actually a really good general-purpose agent.** The same architecture that lets Claude Code refactor a codebase can let an agent organize your files, manage your reading list, or automate your workflows. The Claude Code SDK makes this accessible. You can build applications where features aren't code you write—they're outcomes you describe, achieved by an agent with tools, operating in a loop until the outcome is reached. This opens up a new field: software that works the way Claude Code works, applied to categories far beyond coding. </why_now> <core_principles> ## Core Principles ### 1. Parity **Whatever the user can do through the UI, the agent should be able to achieve through tools.** This is the foundational principle. Without it, nothing else matters. Imagine you build a notes app with a beautiful interface for creating, organizing, and tagging notes. A user asks the agent: "Create a note
- Why Now
- Core Principles
- 1. Parity
- 2. Granularity
- 3. Composability
- 4. Emergent Capability
- 5. Improvement Over Time
- What aspect of agent-native architecture do you need help with?
- Architecture Review Checklist
- Tool Design
- Files & Workspace
- Agent Execution
- Context Injection
- UI Integration
What does the design-agent-native skill do?
Build applications where agents are first-class citizens. Use this skill when designing autonomous agents, creating MCP tools, implementing self-modifying systems, or building apps where features are outcomes achieved by agents operating in a loop.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill design-agent-native --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.