agent-native-audit
Skill1 starsChanged 5 months agoMITView on GitHub
Run a comprehensive scored audit of agent-native architecture principles
1 other project uses a version of this.
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- psw7205/skillstheir own version, first seen May 26, 2026
Other versions1 project uses a version of this.
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Wrote their own version · 1
- psw7205/skills★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository30 other files it gives its agents.
- .codex/AGENTS.mdAGENTS.md
- compound-engineeringSkill
- compound-engineeringSkill
- agent-browserSkill
- agent-native-architectureSkill
- brainstormingSkill
- cavemanSkill
- compound-docsSkill
- compound-engineeringSkill
- compounding-operating-systemSkill
- compound-refreshSkill
- create-agent-skillsSkill
- document-reviewSkill
- file-todosSkill
- finishing-branchSkill
- frontend-designSkill
- gemini-imagegenSkill
- git-worktreeSkill
- grill-meSkill
- ideateSkill
- i-have-adhdSkill
- laravel-conventionsSkill
- orchestrating-swarmsSkill
- rcloneSkill
- resolve-pr-parallelSkill
- setupSkill
- skill-creatorSkill
- systematic-debuggingSkill
- ubiquitous-languageSkill
- xml-tag-structureSkill
The file
Show its rules and text
We split this skill into the rules it gives an agent
18 rules. About 0 are common, 16 are distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈16
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 16
Run a comprehensive review of a codebase against agent-native architecture principles, split the work into scored principle-specific audit …
- Distinctive: line 22
After adding agent tools, prompts, commands, or shared-workspace behavior
- Distinctive: line 23
Before shipping major agent-facing product changes
- Distinctive: line 24
When you need a numeric baseline for how agent-native a system really is
- Distinctive: line 25
When you want prioritized recommendations instead of a vague architectural opinion
- Distinctive: line 55
Use the local skill name directly.
- Very specific: line 59
If $ARGUMENTS names a single principle, audit only that principle.
- Distinctive: line 63
When auditing a plugin, CLI, or developer-tooling codebase, map "user actions" and "UI" broadly:
- Distinctive: line 80
Prefer discovery-oriented agents for evidence gathering and stronger review agents for synthesis when available.
- Distinctive: line 85
Check compliance against the principle
- Distinctive: line 105
Check which actions have corresponding agent tools, commands, or capabilities
- Distinctive: line 185
Check whether agents and users operate on the same state or separate shadow state
- Distinctive: line 232
Check how agent actions propagate to user-visible surfaces
- Distinctive: line 260
Check for these discovery mechanisms:
- Distinctive: line 288
Read prompts, agents, skills, commands, and orchestration code
- Distinctive: line 292
Check whether changing behavior usually requires prompt edits or code edits
- Distinctive: line 308
After all audit tracks finish, compile a single report:
- Very specific: line 353
If $ARGUMENTS specifies a single principle, run only that audit track and provide detailed findings for that principle.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Agent-Native Audit
Run a comprehensive review of a codebase against agent-native architecture principles, split the work into scored principle-specific audit tracks, and produce a prioritized summary report.
Announce at start: "I'm using the agent-native-audit skill to run a scored agent-native architecture review."
When to Use
- After adding agent tools, prompts, commands, or shared-workspace behavior
- Before shipping major agent-facing product changes
- When you need a numeric baseline for how agent-native a system really is
- When you want prioritized recommendations instead of a vague architectural opinion
Core Principles to Audit
- Action Parity - "Whatever the user can do, the agent can do"
- Tools as Primitives - "Tools provide capability, not behavior"
- Context Injection - "System prompt includes dynamic context about app state"
- Shared Workspace - "Agent and user work in the same data space"
- CRUD Completeness - "Every important entity has full CRUD (Create, Read, Update, Delete)"
- UI Integration - "Agent actions are reflected in the product experience"
- Capability Discovery - "Users can discover what the agent can do"
- Prompt-Native Features - "Features are prompts defining outcomes, not rigid workflow code"
Workflow
Step 1: Load the Local Reference Skill
First, invoke agent-native-architecture to refresh the local vocabulary, principles, checklist, and anti-patterns used in this plugin.
Focus especially on:
- Core principles
- Architecture Review Checklist
- Tool Design
- Files & Workspace
- Context Injection
- UI Integration
- Capability Discovery
- Anti-Patterns
Use the local skill name directly. Do not rely on Every-specific namespaced invocations.
Step 2: Decide Audit Scope
If $ARGUMENTS names a single principle, audit only that principle.
Otherwise, audit all 8 principles.
When auditing a plugin, CLI, or developer-tooling codebase, map "user actions" and "UI" broadly:
- Slash commands
- Prompts
- Agents
- Skills
- CLI entrypoints
- Generated artifacts
- Shared files, docs, and workspace state
Step 3: Launch Parallel Audit Tracks
Launch up to 8 parallel audit tracks using the platform's task/subagent tool.
- On Claude-style platforms, this is typically
Taskwithsubagent_type - On Copilot-style platforms, this is typically
taskwithagent_type
Prefer discovery-oriented agents for evidence gathering and stronger review agents for synthesis when available. In this plugin, agent-native-reviewer, architecture-strategist, explore, and general-purpose are all reasonable choices depending on platform and available agents.
Each audit track should:
- Enumerate all relevant instances in the codebase
- Check compliance against the principle
- Produce a specific numeric score in
X/Yformat - List concrete gaps
- Recommend the highest-impact fixes first
Audit Track Prompts
Track 1: Action Parity
Audit for ACTION PARITY - "Whatever the user can do, the agent can do."
Tasks:
- Enumerate all meaningful user actions across product surfaces:
- UI actions
- Slash commands
- CLI actions
- Form submissions
- API endpoints
- File and workspace operations
- Check which actions have corresponding agent tools, commands, or capabilities
- Score: "Agent can do X out of Y user actions"
Format:
## Action Parity Audit
### User Actions Found
| Action | Location | Agent Equivalent | Status |
|--------|----------|------------------|--------|
### Score: X/Y (percentage%)
### Missing Agent Capabilities
### RecommendationsTrack 2: Tools as Primitives
Audit for TOOLS AS PRIMITIVES - "Tools provide capability, not behavior."
Tasks:
- Find and read all agent tools, commands, or callable integration surfaces
- Classify each as:
- PRIMITIVE (good) - Exposes a capability without embedding decision-making
- WORKFLOW (risky) - Encodes business logic, orchestration, or branching that should live in prompts
- Score: "X out of Y tools are proper primitives"
Format:
## Tools as Primitives Audit
### Tool Analysis
| Surface | File | Type | Reasoning |
|---------|------|------|-----------|
### Score: X/Y (percentage%)
### Workflow-Heavy Surfaces
### RecommendationsTrack 3: Context Injection
Audit for CONTEXT INJECTION - "System prompt includes dynamic context about app state."
Tasks:
- Find context injection code, system prompts, and agent setup logic
- Enumerate what is injected versus what should be injected:
- Available resources
- User preferences
- Recent activity
- Workspace or session state
- Available capabilities
- Relevant history
- Score: "X out of Y important context categories are injected"
Format:
## Context Injection Audit
### Context Types Analysis
| Context Type | Injected? | Location | Notes |
|--------------|-----------|----------|-------|
### Score: X/Y (percentage%)
### Missing Context
### RecommendationsTrack 4: Shared Workspace
Audit for SHARED WORKSPACE - "Agent and user work in the same data space."
Tasks:
- Identify all important data stores and shared artifacts:
- Files
- Databases
- Documents
- Session stores
- Queues
- Generated outputs
- Check whether agents and users operate on the same state or separate shadow state
- Score: "X out of Y important data spaces are truly shared"
Format:
## Shared Workspace Audit
### Data Space Analysis
| Data Space | User Access | Agent Access | Shared? |
|------------|-------------|--------------|---------|
### Score: X/Y (percentage%)
### Isolated State (anti-pattern)
### RecommendationsTrack 5: CRUD Completeness
Audit for CRUD COMPLETENESS - "Every important entity has full CRUD."
Tasks:
- Identify all important entities, resources, or managed objects
- For each, check whether the agent can:
- Create
- Read
- Update
- Delete
- 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
### RecommendationsTrack 6: UI Integration
Audit for UI INTEGRATION - "Agent actions are reflected in the product experience."
Tasks:
- Check how agent actions propagate to user-visible surfaces
- Look for:
- Immediate UI refresh
- Shared state updates
- Eventing or streaming
- File watching
- Regeneration steps
- Clear feedback in CLI or docs
- Identify silent-action anti-patterns where the agent changes something but the user cannot see it promptly
Format:
## UI Integration Audit
### Agent Action -> User Visibility Analysis
| Agent Action | Surface Update Mechanism | Immediate? | Notes |
|--------------|--------------------------|------------|-------|
### Score: X/Y (percentage%)
### Silent Actions
### RecommendationsTrack 7: Capability Discovery
Audit for CAPABILITY DISCOVERY - "Users can discover what the agent can do."
Tasks:
- Check for these discovery mechanisms:
- Onboarding or getting-started guidance
- Help documentation
- Capability hints in UI or command descriptions
- Agent self-description
- Suggested prompts or workflows
- Empty-state guidance
- Slash commands or discoverable command lists
- Score against the mechanisms that are relevant to the product
Format:
## Capability Discovery Audit
### Discovery Mechanism Analysis
| Mechanism | Exists? | Location | Quality |
|-----------|---------|----------|---------|
### Score: X/Y (percentage%)
### Missing Discovery Paths
### RecommendationsTrack 8: Prompt-Native Features
Audit for PROMPT-NATIVE FEATURES - "Features are prompts defining outcomes, not code."
Tasks:
- Read prompts, agents, skills, commands, and orchestration code
- Classify each important behavior as defined primarily in:
- PROMPT (good) - Outcome described in natural language
- CODE (risky) - Business logic hardcoded in conditionals or rigid orchestration
- Check whether changing behavior usually requires prompt edits or code edits
Format:
## Prompt-Native Features Audit
### Feature Definition Analysis
| Feature | Defined In | Type | Notes |
|---------|------------|------|-------|
### Score: X/Y (percentage%)
### Code-Defined Behaviors
### RecommendationsStep 4: Compile the Summary Report
After all audit tracks finish, compile a single report:
## 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 requested audit tracks complete
- Each principle has a specific numeric score in
X/Yformat - Summary table includes all audited principles and status indicators
- Recommendations are prioritized by impact
- Report identifies both strengths and gaps
Optional: Single Principle Audit
If $ARGUMENTS specifies a single principle, run only that audit track and provide detailed findings for that principle.
Valid arguments:
action parityor1toolsorprimitivesor2contextorinjectionor3sharedorworkspaceor4crudor5uiorintegrationor6discoveryor7promptorfeaturesor8
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