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ia-agent-native-architecture

设计智能体原生应用,让智能体取代UI用户成为主要参与者。适用于MCP工具、智能体循环架构、共享工作空间等设计场景。

person作者: iliaalhubclawhub

Agent-Native Architecture

Core Principles

Five principles govern agent-native design. For detailed explanations, examples, and test criteria, see core-principles.md.

| Principle | One-line test | |-----------|--------------| | Parity | Can the agent achieve every outcome the UI allows? | | Granularity | To change behavior, do you edit prose or refactor code? | | Composability | Can you add a feature by writing a new prompt, without new code? | | Emergent Capability | Can the agent handle open-ended requests you didn't design for? | | Improvement Over Time | Does the app work better after a month, even without code changes? |

Focus Area Selection

  1. Design architecture - Plan a new agent-native system from scratch
  2. Files & workspace - Use files as the universal interface, shared workspace patterns
  3. Tool design - Build primitive tools, dynamic capability discovery, CRUD completeness
  4. Domain tools - Know when to add domain tools vs stay with primitives
  5. Execution patterns - Completion signals, partial completion, context limits
  6. System prompts - Define agent behavior in prompts, judgment criteria
  7. Context injection - Inject runtime app state into agent prompts
  8. Action parity - Ensure agents can do everything users can do
  9. Self-modification - Enable agents to safely evolve themselves
  10. Product design - Progressive disclosure, latent demand, approval patterns
  11. Mobile patterns - iOS storage, background execution, checkpoint/resume
  12. Testing - Test agent-native apps for capability and parity
  13. Refactoring - Make existing code more agent-native
  14. Anti-patterns - Common mistakes and how to avoid them
  15. Success criteria - Verify your architecture is agent-native
  16. Hooks patterns - Hook events, decision control, MCP matchers, async hooks

Wait for response before proceeding.

Reference Routing

| Response | Action | |----------|--------| | 1, "design", "architecture", "plan" | Read architecture-patterns.md, then apply Architecture Checklist below | | 2, "files", "workspace", "filesystem" | Read files-universal-interface.md and shared-workspace-architecture.md | | 3, "tool", "mcp", "primitive", "crud" | Read mcp-tool-design.md | | 4, "domain tool", "when to add" | Read from-primitives-to-domain-tools.md | | 5, "execution", "completion", "loop" | Read agent-execution-patterns.md | | 6, "prompt", "system prompt", "behavior" | Read system-prompt-design.md | | 7, "context", "inject", "runtime", "dynamic" | Read dynamic-context-injection.md | | 8, "parity", "ui action", "capability map" | Read action-parity-discipline.md | | 9, "self-modify", "evolve", "git" | Read self-modification.md | | 10, "product", "progressive", "approval", "latent demand" | Read product-implications.md | | 11, "mobile", "ios", "android", "background", "checkpoint" | Read mobile-patterns.md | | 11a, "icloud", "storage", "documents", "file state", "entitlement" | Read mobile-storage.md | | 11b, "background task", "battery", "on-device", "cloud routing" | Read mobile-execution.md | | 11c, "model tier", "token budget", "cost-aware", "batch", "caching" | Read mobile-cost.md | | 12, "test", "testing", "verify", "validate" | Read agent-native-testing.md | | 13, "review", "refactor", "existing" | Read refactoring-to-prompt-native.md | | 14, "anti-pattern", "mistake", "wrong" | Read anti-patterns.md | | 15, "success", "criteria", "verify", "checklist" | Read success-criteria.md | | 16, "hook", "hooks", "PreToolUse", "decision control", "async hook" | Read hooks-patterns.md | | 0, "quick start", "getting started", "overview", "introduction" | Read quick-start.md |

After reading the reference, apply those patterns to the user's specific context.

Architecture Review Checklist

When designing an agent-native system, verify these before implementation:

Core Principles

  • [ ] Parity: Every UI action has a corresponding agent capability
  • [ ] Granularity: Tools are primitives; features are prompt-defined outcomes
  • [ ] Composability: New features can be added via prompts alone
  • [ ] Emergent Capability: Agent can handle open-ended requests in your domain

Tool Design

  • [ ] Dynamic vs Static: For external APIs where agent should have full access, use Dynamic Capability Discovery
  • [ ] CRUD Completeness: Every entity has create, read, update, AND delete
  • [ ] Primitives over Workflows: Tools expose atomic capabilities; compose workflows in prompts
  • [ ] API as Validator: Use z.string() inputs when the API validates, not z.enum()
  • [ ] Eval Gate: 10 Q/A pairs in CI (read-only, multi-hop, closed-data), 9/10 pass threshold. See mcp-tool-design.md Evaluation section.

Files & Workspace

  • [ ] Shared Workspace: Agent and user work in same data space
  • [ ] context.md Pattern: Agent reads/updates context file for accumulated knowledge
  • [ ] File Organization: Entity-scoped directories with consistent naming
  • [ ] Context Durability: Incremental progress writes (WAL pattern) so interrupted tasks resume from last checkpoint

Agent Execution

  • [ ] Completion Signals: Agent has explicit complete_task tool (not heuristic detection)
  • [ ] Partial Completion: Multi-step tasks track progress for resume
  • [ ] Context Limits: Designed for bounded context from the start
  • [ ] Validate-Before-Run: Agent previews planned actions before executing destructive operations

Context Injection

  • [ ] Available Resources: System prompt includes what exists (files, data, types)
  • [ ] Available Capabilities: System prompt documents tools with user vocabulary
  • [ ] Dynamic Context: Context refreshes for long sessions (or provide refresh_context tool)
  • [ ] Trust levels for loaded content: System prompt distinguishes trusted (developer-authored) from untrusted (user input, retrieved docs, tool outputs); untrusted text is data, never instructions. See dynamic-context-injection.md Trust Levels section for the prompt-injection defense details.

UI Integration

  • [ ] Agent -> UI: Agent changes reflect in UI (shared service, file watching, or event bus)
  • [ ] No Silent Actions: Agent writes trigger UI updates immediately
  • [ ] Capability Discovery: Users can learn what agent can do

Governance

  • [ ] Approval Gates: Destructive or irreversible actions require user confirmation
  • [ ] Audit Trail: Agent actions logged with timestamp, tool, and outcome
  • [ ] Scope Boundaries: Agent cannot access resources outside its designated workspace

Hooks & Governance Automation

  • [ ] Event Coverage: Only 6 hook events fire in agent context (PreToolUse, PostToolUse, PermissionRequest, PostToolUseFailure, Stop/SubagentStop); session lifecycle logic lives in the orchestrator
  • [ ] Decision Gates: PreToolUse hooks enforce tool-level policy (allow/deny/ask/defer) instead of hardcoded checks
  • [ ] Completion Gating: SubagentStop hooks block premature completion when verification steps remain
  • [ ] MCP Matchers: Regex patterns target tools by server and operation for capability-based security
  • [ ] Two-Tier Config: Shared policy committed, personal overrides git-ignored, per-hook disable toggles

Mobile (if applicable)

  • [ ] Checkpoint/Resume: Handle iOS app suspension gracefully
  • [ ] iCloud Storage: iCloud-first with local fallback for multi-device sync
  • [ ] Cost Awareness: Model tier selection (Haiku/Sonnet/Opus)

When designing architecture, explicitly address each checkbox in your plan.