agent-native-audit
Comprehensive agent-native architecture audit with scored principles and multi-slice review. Use for system-wide health checks or periodic audits.
Best use case
agent-native-audit is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Comprehensive agent-native architecture audit with scored principles and multi-slice review. Use for system-wide health checks or periodic audits.
Teams using agent-native-audit should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/agent-native-audit/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How agent-native-audit Compares
| Feature / Agent | agent-native-audit | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Comprehensive agent-native architecture audit with scored principles and multi-slice review. Use for system-wide health checks or periodic audits.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Agent-Native Architecture Audit Conduct a comprehensive review of the codebase against agent-native architecture principles, running multi-agent slices (parallel or serial) and producing a scored report. ## When to Use - System-wide health checks - Periodic audits - Major refactors or architecture resets ## Output Location - Write results under `docs/05-reviews-audits/` as `agent-native-audit_YYYY_MM_DD.md`. ## Core Principles to Audit 1. **Action Parity** - "Whatever the user can do, the agent can do" 2. **Tools as Primitives** - "Tools provide capability, not behavior" 3. **Context Injection** - "System prompt includes dynamic context about app state" 4. **Shared Workspace** - "Agent and user work in the same data space" 5. **CRUD Completeness** - "Every entity has full CRUD (Create, Read, Update, Delete)" 6. **UI Integration** - "Agent actions immediately reflected in UI" 7. **Capability Discovery** - "Users can discover what the agent can do" 8. **Prompt-Native Features** - "Features are prompts defining outcomes, not code" ## Workflow ### Step 1: Load Skills 1. Invoke the agent-native-architecture skill to understand all principles: ``` /compound-engineering:agent-native-architecture ``` Select option 7 (action parity) to load the full reference material. 2. Run skill `multi-agent-routing` to decide sub-agents vs parallel/serial sessions. ### Step 2: Run Agent Slices Run 8 agent slices, one per principle. - If sub-agents are supported, launch them with the Task tool using `subagent_type: Explore` (parallel or serial per routing). - Otherwise open parallel sessions or run serially (one block per slice). Each agent should: 1. Enumerate ALL instances in the codebase (user actions, tools, contexts, data stores, etc.) 2. Check compliance against the principle 3. Provide a SPECIFIC SCORE like "X out of Y (percentage%)" 4. List specific gaps and recommendations <agent-slices> **Agent 1: Action Parity** ``` Audit for ACTION PARITY - "Whatever the user can do, the agent can do." Tasks: 1. Enumerate ALL user actions in frontend (API calls, button clicks, form submissions) - Search for API service files, fetch calls, form handlers - Check routes and components for user interactions 2. Check which have corresponding agent tools - Search for agent tool definitions - Map user actions to agent capabilities 3. Score: "Agent can do X out of Y user actions" Format: ## Action Parity Audit ### User Actions Found | Action | Location | Agent Tool | Status | ### Score: X/Y (percentage%) ### Missing Agent Tools ### Recommendations ``` **Agent 2: Tools as Primitives** ``` Audit for TOOLS AS PRIMITIVES - "Tools provide capability, not behavior." Tasks: 1. Find and read ALL agent tool files 2. Classify each as: - PRIMITIVE (good): read, write, store, list - enables capability without business logic - WORKFLOW (bad): encodes business logic, makes decisions, orchestrates steps 3. Score: "X out of Y tools are proper primitives" Format: ## Tools as Primitives Audit ### Tool Analysis | Tool | File | Type | Reasoning | ### Score: X/Y (percentage%) ### Problematic Tools (workflows that should be primitives) ### Recommendations ``` **Agent 3: Context Injection** ``` Audit for CONTEXT INJECTION - "System prompt includes dynamic context about app state" Tasks: 1. Find context injection code (search for "context", "system prompt", "inject") 2. Read agent prompts and system messages 3. Enumerate what IS injected vs what SHOULD be: - Available resources (files, drafts, documents) - User preferences/settings - Recent activity - Available capabilities listed - Session history - Workspace state Format: ## Context Injection Audit ### Context Types Analysis | Context Type | Injected? | Location | Notes | ### Score: X/Y (percentage%) ### Missing Context ### Recommendations ``` **Agent 4: Shared Workspace** ``` Audit for SHARED WORKSPACE - "Agent and user work in the same data space" Tasks: 1. Identify all data stores/tables/models 2. Check if agents read/write to SAME tables or separate ones 3. Look for sandbox isolation anti-pattern (agent has separate data space) Format: ## Shared Workspace Audit ### Data Store Analysis | Data Store | User Access | Agent Access | Shared? | ### Score: X/Y (percentage%) ### Isolated Data (anti-pattern) ### Recommendations ``` **Agent 5: CRUD Completeness** ``` Audit for CRUD COMPLETENESS - "Every entity has full CRUD" Tasks: 1. Identify all entities/models in the codebase 2. For each entity, check if agent tools exist for: - Create - Read - Update - Delete 3. Score per entity and overall Format: ## CRUD Completeness Audit ### Entity CRUD Analysis | Entity | Create | Read | Update | Delete | Score | ### Overall Score: X/Y entities with full CRUD (percentage%) ### Incomplete Entities (list missing operations) ### Recommendations ``` **Agent 6: UI Integration** ``` Audit for UI INTEGRATION - "Agent actions immediately reflected in UI" Tasks: 1. Check how agent writes/changes propagate to frontend 2. Look for: - Streaming updates (SSE, WebSocket) - Polling mechanisms - Shared state/services - Event buses - File watching 3. Identify "silent actions" anti-pattern (agent changes state but UI doesn't update) Format: ## UI Integration Audit ### Agent Action → UI Update Analysis | Agent Action | UI Mechanism | Immediate? | Notes | ### Score: X/Y (percentage%) ### Silent Actions (anti-pattern) ### Recommendations ``` **Agent 7: Capability Discovery** ``` Audit for CAPABILITY DISCOVERY - "Users can discover what the agent can do" Tasks: 1. Check for these 7 discovery mechanisms: - Onboarding flow showing agent capabilities - Help documentation - Capability hints in UI - Agent self-describes in responses - Suggested prompts/actions - Empty state guidance - Slash commands (/help, /tools) 2. Score against 7 mechanisms Format: ## Capability Discovery Audit ### Discovery Mechanism Analysis | Mechanism | Exists? | Location | Quality | ### Score: X/7 (percentage%) ### Missing Discovery ### Recommendations ``` **Agent 8: Prompt-Native Features** ``` Audit for PROMPT-NATIVE FEATURES - "Features are prompts defining outcomes, not code" Tasks: 1. Read all agent prompts 2. Classify each feature/behavior as defined in: - PROMPT (good): outcomes defined in natural language - CODE (bad): business logic hardcoded 3. Check if behavior changes require prompt edit vs code change Format: ## Prompt-Native Features Audit ### Feature Definition Analysis | Feature | Defined In | Type | Notes | ### Score: X/Y (percentage%) ### Code-Defined Features (anti-pattern) ### Recommendations ``` </agent-slices> ### Step 3: Compile Summary Report After all agents complete, compile a summary with: ```markdown ## Agent-Native Architecture Review: [Project Name] ### Overall Score Summary | Core Principle | Score | Percentage | Status | |----------------|-------|------------|--------| | Action Parity | X/Y | Z% | ✅/⚠️/❌ | | Tools as Primitives | X/Y | Z% | ✅/⚠️/❌ | | Context Injection | X/Y | Z% | ✅/⚠️/❌ | | Shared Workspace | X/Y | Z% | ✅/⚠️/❌ | | CRUD Completeness | X/Y | Z% | ✅/⚠️/❌ | | UI Integration | X/Y | Z% | ✅/⚠️/❌ | | Capability Discovery | X/Y | Z% | ✅/⚠️/❌ | | Prompt-Native Features | X/Y | Z% | ✅/⚠️/❌ | **Overall Agent-Native Score: X%** ### Status Legend - ✅ Excellent (80%+) - ⚠️ Partial (50-79%) - ❌ Needs Work (<50%) ### Top 10 Recommendations by Impact | Priority | Action | Principle | Effort | |----------|--------|-----------|--------| ### What's Working Excellently [List top 5 strengths] ``` ## Success Criteria - [ ] All 8 slices complete their audits - [ ] Each principle has a specific numeric score (X/Y format) - [ ] Summary table shows all scores and status indicators - [ ] Top 10 recommendations are prioritized by impact - [ ] Report identifies both strengths and gaps ## Optional: Single Principle Audit If $ARGUMENTS specifies a single principle (e.g., "action parity"), only run that agent and provide detailed findings for that principle alone. Valid arguments: - `action parity` or `1` - `tools` or `primitives` or `2` - `context` or `injection` or `3` - `shared` or `workspace` or `4` - `crud` or `5` - `ui` or `integration` or `6` - `discovery` or `7` - `prompt` or `features` or `8`
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