ringexploring-codebase

name	ring:exploring-codebase
description	Autonomous two-phase codebase exploration - first discovers natural perspectives (layers, components, boundaries), then dispatches adaptive deep-dive explorers based on what was discovered. Synthesizes findings into actionable insights.
license	MIT
compatibility	opencode
metadata	{"trigger":"Need to understand how feature/system works, starting on unfamiliar codebase, planning multi-layer changes","skip_when":"Pure reference lookup, checking if file exists, reading known error location"}

Autonomous Two-Phase Codebase Exploration

Overview

Traditional exploration assumes structure upfront or explores sequentially. This skill takes an autonomous two-phase approach: discover the natural perspectives of the codebase first, then deep dive into each discovered perspective with targeted explorers.

Core principle: Let the codebase reveal its own structure, then explore each structure element thoroughly with adaptive parallel agents.

MANDATORY ANNOUNCEMENT at start:

"I'm using the ring:exploring-codebase skill to autonomously discover and explore the codebase structure.

Before proceeding, I've checked the Red Flags table and confirmed:

• Production pressure makes me WANT to skip discovery → Using skill anyway
• I think I 'already know' the structure → Discovery will validate assumptions
• This seems like a simple question → Location without context is incomplete
• Colleague gave me high-level info → Discovery finds what they forgot

The skill's core principle: When pressure is highest, systematic approach matters most."

🚨 Red Flags: When You're About to Make a Mistake

STOP and use this skill if you catch yourself thinking:

Red Flag Thought	What It Means	Do This Instead
"I already know this architecture"	⚠️ Dunning-Kruger	Run discovery to validate assumptions
"Grep is faster for this simple question"	⚠️ Optimizing for feeling productive	One exploration > multiple follow-ups
"Production is down, no time for process"	⚠️ Panic mode	High stakes demand MORE rigor
"Colleague told me the structure"	⚠️ Trusting abstractions	Discovery finds what they forgot
"Being pragmatic means skipping this"	⚠️ Conflating speed with value	Real pragmatism = doing it right
"This is overkill for..."	⚠️ Underestimating complexity	Incomplete understanding compounds
"I'll explore progressively if I get stuck"	⚠️ Reactive vs proactive	Discovery prevents getting stuck
"Let me just quickly check..."	⚠️ Ad-hoc investigation trap	Systematic > ad-hoc

If 2+ red flags triggered: YOU NEED THIS SKILL.

💥 Violation Consequences: Real Costs of Skipping

"What's the worst that could happen if I skip discovery?"

Consequence 1: The Cascade Effect

Scenario: Skip discovery → Fix in wrong component → Break integration → New production issue

Example:

• Bug: "Account creation failing"
• Assumption: "It's in onboarding component"
• Reality: Transaction component has new validation that breaks onboarding
• Your fix: Modify onboarding (wrong component)
• Result: Original bug persists, NEW bug in onboarding, 2 issues instead of 1

Discovery would have revealed: Transaction component owns the validation now.

Consequence 2: The Multiple Round-Trip Effect

Scenario: Grep for location → Answer question → User asks follow-up → Grep again → Another follow-up

Example:

• Q1: "Where is validation?" → Grep → Answer: validation.go:45
• Q2: "How does it integrate?" → Read files → Answer: "Called from use case"
• Q3: "What else validates?" → Grep again → Answer: "Assert package + HTTP layer"
• Total: 3 round trips, 15 minutes, incomplete mental model

Exploration would have provided: All answers in one comprehensive document, 10 minutes total.

Consequence 3: The Stale Knowledge Effect

Scenario: "I already know" → Work based on old mental model → Code has changed → Wrong implementation

Example:

• Your knowledge: "3 components (onboarding, transaction, crm)"
• Reality: New audit component added last month for compliance
• Your fix: Modify account creation in onboarding
• Missing: Audit component now logs all account operations
• Result: Account created but not audited, compliance violation

Discovery would have revealed: 4 components now, audit is mandatory.

Consequence 4: The Hidden Dependencies Effect

Scenario: Skip discovery → Miss shared libraries → Duplicate code → Technical debt

Example:

• Task: Add account validation rule
• Grep finds: create-account.go has validation
• You add: New validation in same file
• Discovery would reveal: pkg/validator/account.go has shared validation library
• Result: Duplicate logic, inconsistent validation across codebase

Discovery would have revealed: Centralized validation library for reuse.

Cost Summary Table

Skip Reason	Time "Saved"	Actual Cost	Net Loss
"I already know"	6-10 min	2+ hours debugging stale knowledge	-110 to -114 min
"Simple question"	6-10 min	3 round trips × 5 min each = 15 min	-5 to -9 min
"Production emergency"	6-10 min	Wrong fix + cascade = 2+ hours	-110 to -114 min
"Colleague told me"	6-10 min	Missing component/library = 1+ hour rework	-50 to -54 min

Pattern: Every "time-saving" skip costs more time than it saves.**

The Two-Phase Flow

Phase 1: Discovery Pass (Meta-Exploration)

Goal: Understand "What IS this codebase?"

Launch 3-4 discovery agents to identify:

• Architecture pattern (hexagonal, layered, microservices, etc.)
• Major components/modules
• Natural boundaries and layers
• Organization principles
• Key technologies and frameworks

Output: Structural map of the codebase

Phase 2: Deep Dive Pass (Adaptive Exploration)

Goal: Understand "How does [target] work in each discovered area?"

Based on Phase 1 discoveries, launch N targeted explorers (where N adapts):

• One explorer per discovered perspective/component/layer
• Each explorer focuses on the target within their scope
• Number and type of explorers match codebase structure

Output: Comprehensive understanding of target across all perspectives

When to Use

Decision flow:

• Need codebase understanding? → Is it trivial (single file/function)? → Yes = Use Read/Grep directly
• No → Is it unfamiliar territory or spans multiple areas? → Yes = Two-phase exploration
• Are you about to make changes spanning multiple components? → Yes = Two-phase exploration

Use when:

• Understanding how a feature works in an unfamiliar codebase
• Starting work on new component/service
• Planning architectural changes
• Need to find where to implement new functionality
• User asks "how does X work?" for complex X in unknown codebase

Don't use when:

• Pure reference lookup: "What's the signature of function X?"
• File existence check: "Does utils.go exist?"
• Reading known error location: "Show me line 45 of errors.go"

COMMON TRAPS - These SEEM like valid skip reasons but are NOT:

❌ Trap 1: "Simple Question About Location"

Rationalization: "User just asked 'where is X?' - grep is faster"

Reality: Location questions lead to "how does X work?" next

• Question: "Where is validation logic?"
• Grep answer: validation.go:45
• Follow-up: "How does it integrate with the system?"
• Follow-up: "What else validates this?"
• Result: 3 questions, incomplete picture, wasted time

Counter: Run exploration once, answer current + future questions.

❌ Trap 2: "I Already Know the Architecture"

Rationalization: "I worked here before, discovery is redundant"

Reality: Prior knowledge is dangerously incomplete

• You know high-level (components exist)
• You don't know details (how they're wired, what changed)
• Assumptions about "known" code cause most bugs

Counter: Discovery validates assumptions and reveals what changed.

❌ Trap 3: "Production Emergency, No Time"

Rationalization: "Production is down, skip the process"

Reality: High stakes demand MORE rigor, not less

• 6-10 min discovery prevents hours of wrong assumptions
• Production bugs from incomplete context cost >> discovery time
• "I know where to look" under stress = peak Dunning-Kruger

Counter: See "When Pressure is Highest" section below.

❌ Trap 4: "Colleague Told Me Structure"

Rationalization: "They said '3 microservices', why rediscover?"

Reality: High-level descriptions miss critical details

• "3 microservices" doesn't mention shared libraries, background jobs, API gateways
• Mental models are abstractions, not complete maps
• People forget to mention "obvious" infrastructure

Counter: Use colleague info as validation context, not replacement for discovery.

When Pressure is Highest, Use Skill Most

CRITICAL INSIGHT: Production emergencies DEMAND systematic understanding.

The Emergency Trap

False logic: "Production down → Skip process → Fix faster" True logic: "Production down → Need accuracy → Use systematic approach"

Why Discovery Matters MORE Under Pressure

Shortcut Path	Systematic Path
Grep "CreateAccount" (30 sec)	Run two-phase exploration (6-10 min)
Read 2-3 files (2 min)	Get complete architecture + target impl
Make assumption-based fix (10 min)	Fix with full context (5 min)
Fix breaks something else (2 hours)	Fix correct first time
Total: 2+ hours + new bugs	Total: 15-20 minutes, done right

The "Surgeon Textbook" Analogy is Wrong

Bad analogy: "Surgeon doesn't read textbook while patient bleeds" Correct analogy: "Surgeon checks vitals before operating"

Discovery is NOT reading theory - it's gathering critical context:

• ✅ Discovery = Checking patient vitals (essential context)
• ❌ Reading textbooks = Reading unnecessary theory

You wouldn't skip vitals because "emergency" - same principle applies here.

Production Emergency Protocol

When production is down:

1. Acknowledge the pressure - "This is urgent, I feel pressure to skip discovery"
2. Recognize the trap - "That pressure is EXACTLY when I need systematic approach"
3. Invest 6-10 minutes - Run two-phase exploration
4. Fix with confidence - Full context prevents cascading failures

Reality check: If you don't have 6-10 minutes for discovery, you don't have 2+ hours to undo wrong fixes.

Real vs False Pragmatism

False Pragmatism (Shortcuts that Backfire)

Shortcut	Seems Pragmatic	Actual Result
"Skip discovery, I already know"	Saves 6-10 min	Hours debugging wrong assumptions
"Grep for simple questions"	Faster than exploration	Multiple follow-up questions, incomplete picture
"Production emergency, no process"	Fixes faster	Wrong fix, breaks more things
"Colleague told me structure"	Use existing knowledge	Miss shared libs, background jobs, actual impl

Real Pragmatism (Invest to Save)

Systematic Approach	Costs	Saves
6-10 min two-phase exploration	6-10 minutes	Hours of debugging wrong assumptions
Complete understanding first	Discovery time	Multiple follow-up questions
Systematic under pressure	Feeling "slow"	Fixing wrong thing, cascading failures
Validate colleague's mental model	Discovery vs assumption	Missing critical infrastructure

Real pragmatism = Doing it right when stakes are high.

False pragmatism = Taking shortcuts that create bigger problems.

When Pragmatism Tells You to Skip...

If you think "being pragmatic means skipping this," ask:

1. Am I conflating "fast" with "good"? Speed without accuracy is just fast failure.
2. Am I optimizing for feeling productive? Grep gives quick dopamine, but incomplete understanding.
3. Am I making excuses under pressure? High stakes demand MORE rigor, not less.
4. Am I assuming I know more than I do? Dunning-Kruger peaks under stress.

If you answered yes to any: Use the skill anyway.

Rationalization Table

When you're tempted to skip the skill, check this table:

Rationalization	Why It Feels Right	Why It's Wrong	Counter
"I already know the architecture"	You worked here before	Prior knowledge is high-level abstractions	Discovery reveals what you don't know to ask
"Simple question, grep is faster"	Just need a file location	Leads to follow-ups, incomplete picture	One exploration answers current + future questions
"Production emergency, no time"	Every second counts	Wrong fix wastes hours, creates new bugs	6-10 min discovery prevents hours of wrong assumptions
"Colleague told me the structure"	They work here, they'd know	Mental models miss details (shared libs, jobs)	Use as validation context, not replacement
"Being pragmatic not dogmatic"	Process shouldn't be rigid	Shortcuts under pressure cause bigger problems	Real pragmatism = right approach when stakes high
"Match tool to scope"	Simple task = simple tool	Context-free answer requires follow-ups	Comprehensive once > multiple partial searches
"Skip discovery to save time"	3-5 min vs 6-10 min	Saving 5 min, losing hours on wrong assumptions	False economy - incomplete understanding compounds
"Progressive investigation works"	Start narrow, expand if stuck	Ad-hoc misses systematic patterns	Discovery first prevents getting stuck

Process

Copy this checklist to track progress:

Two-Phase Exploration Progress:
- [ ] Phase 0: Scope Definition (exploration target identified)
- [ ] Phase 1: Discovery Pass (structure discovered - 3-4 agents)
- [ ] Phase 2: Deep Dive Pass (N adaptive explorers launched)
- [ ] Phase 3: Result Collection (all agents completed)
- [ ] Phase 4: Synthesis (discovery + deep dive integrated)
- [ ] Phase 5: Action Recommendations (next steps identified)

Phase 0: Scope Definition

Step 0.1: Identify Exploration Target

From user request, extract:

• Core subject: What feature/system/component to explore?
• Context clue: Why are they asking? (planning change, debugging, learning)
• Depth needed: Surface understanding or comprehensive dive?

Step 0.2: Set Exploration Boundaries

Define scope to keep agents focused:

• Include: Directories/components relevant to target
• Exclude: Build config, vendor code, generated files (unless specifically needed)
• Target specificity: "account creation" vs "entire onboarding service"

Phase 1: Discovery Pass (Meta-Exploration)

Goal: Discover the natural structure of THIS codebase

Step 1.1: Launch Discovery Agents in Parallel

CRITICAL: Single message with 3-4 Task tool calls

Dispatch discovery agents simultaneously:

Task(subagent_type="Explore", description="Architecture discovery",
     prompt="[Architecture Discovery prompt]")

Task(subagent_type="Explore", description="Component discovery",
     prompt="[Component Discovery prompt]")

Task(subagent_type="Explore", description="Layer discovery",
     prompt="[Layer Discovery prompt]")

Task(subagent_type="Explore", description="Organization discovery",
     prompt="[Organization Discovery prompt]")

See Discovery Agent Prompts section below for templates.

Step 1.2: Collect Discovery Results

Wait for all discovery agents to complete. Extract from results:

Structural Elements:

• Architecture pattern(s) used
• List of major components/services
• Layers within components (if applicable)
• Directory organization principle
• Technology stack per component

Perspective Matrix: Create a matrix of discovered perspectives:

Components: [A, B, C]
Layers (per component): [HTTP, UseCase, Repository, Domain]
Boundaries: [Component boundaries, Layer boundaries]
Organization: [By feature, By layer, By domain]

Step 1.3: Determine Deep Dive Strategy

Based on discoveries, decide exploration approach:

Discovery Result	Deep Dive Strategy
3 components × 4 layers	Launch 3 explorers (one per component)
Single component, clear layers	Launch 4 explorers (one per layer)
Microservices architecture	Launch N explorers (one per service)
Monolith by feature	Launch explorers per major feature
Mix of patterns	Adaptive: explore each unique area

Step 1.4: Validate Discovery Quality

✅ Quality checks:

• Architecture pattern clearly identified
• Major components/modules enumerated
• Boundaries and layers documented
• File paths provided as evidence
• No major "unknown" areas remaining

If quality insufficient: Re-run specific discovery agents with refined prompts.

Phase 2: Deep Dive Pass (Adaptive Exploration)

Goal: Explore target within each discovered perspective

Step 2.1: Generate Adaptive Prompts

For each discovered perspective, create a targeted prompt:

Template structure:

Explore [TARGET] in [DISCOVERED_COMPONENT/LAYER].

Context from discovery:
- This is the [COMPONENT_NAME] which handles [RESPONSIBILITY]
- Architecture: [PATTERN]
- Location: [DIRECTORY_PATHS]
- Related components: [DEPENDENCIES]

Task:
1. Find how [TARGET] is implemented in this area
2. Trace execution flow within this scope
3. Identify key files and functions (with file:line references)
4. Document patterns and conventions used
5. Note integration points with other areas

Boundaries:
- Stay within [DIRECTORY_SCOPE]
- Maximum depth: [BASED_ON_LAYER]
- Focus on [TARGET] specifically

Output format: [Structured report with file:line references]

Step 2.2: Dispatch Adaptive Explorers in Parallel

CRITICAL: Single message with N Task tool calls (N = number of discovered perspectives)

Example for 3-component system:

Task(subagent_type="Explore", description="Explore target in Component A",
     prompt="[Adaptive prompt for Component A]")

Task(subagent_type="Explore", description="Explore target in Component B",
     prompt="[Adaptive prompt for Component B]")

Task(subagent_type="Explore", description="Explore target in Component C",
     prompt="[Adaptive prompt for Component C]")

Agent Configuration:

• subagent_type: Explore (fast agent specialized for codebase exploration)
• model: haiku (fast, cost-effective)
• run_in_background: No (await results for synthesis)

Step 2.3: Await All Deep Dive Agents

Block until all N agents complete. Do not proceed with partial results.

Phase 3: Result Collection

Step 3.1: Organize Findings

Separate results into two buckets:

Discovery Results (from Phase 1):

• Architecture map
• Component catalog
• Layer definitions
• Organization principles

Deep Dive Results (from Phase 2):

• Per-perspective exploration reports
• File:line references for target
• Patterns observed in each area
• Integration points discovered

Step 3.2: Quality Check Deep Dives

For each deep dive agent result:

• ✅ Check completeness (did it find the target?)
• ✅ Verify file:line references provided
• ✅ Confirm it stayed within scope
• ⚠️ Note gaps ("target not found in this area" is valid)
• ⚠️ Identify conflicts between areas

Step 3.3: Cross-Reference Discovery vs Deep Dive

Validate that deep dives align with discovered structure:

• Do findings match the architecture pattern?
• Are all discovered components covered?
• Are there surprises (things not in discovery)?

If major misalignment: Investigation needed (discovery was incomplete or incorrect).

Phase 4: Synthesis

Step 4.1: Integrate Discovery + Deep Dive

Create unified understanding by layering deep dives onto discovery:

Integration process:

1. Start with structural map (from Phase 1)
2. Overlay target implementation (from Phase 2 per area)
3. Identify how target flows across discovered boundaries
4. Document patterns consistent across areas
5. Highlight variations between areas

Step 4.2: Create Synthesis Document

Output format:

# Autonomous Codebase Exploration: [Target]

## Executive Summary
[2-3 sentences: architecture + how target works]

---

## Phase 1: Discovery Findings

### Architecture Pattern
[Pattern name with evidence]

### Component Structure
[Components discovered with responsibilities]

### Layer Organization
[Layers identified with boundaries]

### Technology Stack
[Key technologies per area]

### Structural Diagram
[ASCII/markdown diagram of discovered structure]

---

## Phase 2: Deep Dive Findings

### [Discovered Area 1 - e.g., "Onboarding Component"]
**Scope:** `components/onboarding/`
**Target Implementation:**
- Entry point: `path/to/file.ext:line`
- Flow: [step-by-step with file:line references]
- Patterns: [patterns observed]
- Integration: [how it connects to other areas]

### [Discovered Area 2 - e.g., "Transaction Component"]
**Scope:** `components/transaction/`
**Target Implementation:**
- Entry point: `path/to/file.ext:line`
- Flow: [step-by-step with file:line references]
- Patterns: [patterns observed]
- Integration: [how it connects to other areas]

[... repeat for each discovered area ...]

---

## Cross-Cutting Insights

### Pattern Consistency
[Where patterns are consistent across areas]

### Pattern Variations
[Where implementation differs and why]

### Integration Points
[How discovered areas interact for target]

### Data Flow
[How data flows across boundaries]

### Key Design Decisions
[Architectural choices evident from exploration]

---

## Implementation Guidance

### For Adding New Functionality
**Where to add code:**
- In [Component]: `path/to/directory/`
- In [Layer]: Follow pattern from `example/file.ext:line`

**Patterns to follow:**
- [Pattern 1] as seen in `file.ext:line`
- [Pattern 2] as seen in `file.ext:line`

**Integration requirements:**
- Connect to [Component A] via [interface]
- Update [Component B] to handle [scenario]

### For Modifying Existing Functionality
**Files to change:**
- Primary: `path/file.ext:line`
- Secondary impacts: `path/file2.ext:line`

**Ripple effects:**
- Changes in [Component A] require updates in [Component B]

### For Debugging
**Start investigation in:**
- [Component/Layer]: `path/file.ext:line`

**Data inspection points:**
- [Layer 1]: `file.ext:line` - [what to check]
- [Layer 2]: `file.ext:line` - [what to check]

**Common failure points:**
- [Area identified from cross-cutting analysis]

---

## Appendix: Discovery Evidence

[File:line references supporting structural discoveries]

Step 4.3: Validate Synthesis

✅ Completeness check:

• Both Phase 1 and Phase 2 integrated
• All discovered areas covered in deep dive
• Cross-cutting insights identified
• Implementation guidance specific and actionable

Phase 5: Action Recommendations

Based on synthesis, provide context-aware next steps:

If user's goal is implementation:

Based on autonomous exploration:

**Codebase Structure:**
- Architecture: [Discovered pattern]
- Components: [List with responsibilities]

**To implement [TARGET]:**
1. Add new code in: [Component/Layer] at `path/`
2. Follow pattern: [Pattern name] from `file.ext:line`
3. Integrate with: [Other components] via [mechanism]
4. Test using: [Test pattern discovered]

**Critical files to understand:**
- `file1.ext:line` - [why important]
- `file2.ext:line` - [why important]

Ready to create implementation plan? (Use /ring:write-plan)

If user's goal is debugging:

Based on autonomous exploration:

**Investigation starting points:**
- [Component A]: `file.ext:line` - [what to check]
- [Component B]: `file.ext:line` - [what to check]

**Data flow for [TARGET]:**
[Origin] → [Transform 1] → [Validation] → [Destination]

**Common failure modes:**
- [Pattern from cross-cutting analysis]

Ready to investigate systematically? (Use systematic-debugging)

If user's goal is learning:

Based on autonomous exploration:

**Codebase organization:**
- [Discovered architecture pattern]
- [N components] with [responsibilities]

**Reading path for [TARGET]:**
1. Start: `file1.ext:line` - [entry point]
2. Then: `file2.ext:line` - [core logic]
3. Finally: `file3.ext:line` - [persistence/output]

**Key patterns to understand:**
- [Pattern 1]: Explained in `file.ext:line`
- [Pattern 2]: Explained in `file.ext:line`

**Related areas to explore next:**
- [Connection found during exploration]

Discovery Agent Prompts

Template: Architecture Discovery Agent

**Goal:** Discover the architecture pattern(s) used in this codebase.

**Scope:** Entire codebase (focus on [TARGET_AREA if specified])

**Task:**
1. Examine directory structure at top level
2. Identify architectural pattern(s):
   - Hexagonal (Ports & Adapters)?
   - Layered (N-tier)?
   - Microservices?
   - Monolith (modular or big ball)?
   - Clean Architecture?
   - MVC/MVVM?
   - Event-driven?
   - Other or mixed?
3. Document evidence for pattern identification:
   - Directory names suggesting layers/boundaries
   - Presence of "adapters", "ports", "domain", "infrastructure"
   - Service separation or monolithic structure
4. Note if multiple patterns coexist (e.g., hexagonal within each microservice)

**Evidence to collect:**
- Directory structure (top 2-3 levels)
- Key directory names that indicate architecture
- Example file paths showing layer separation
- README or docs mentioning architecture

**Output format:**

Architecture Discovery

Primary Pattern: [Pattern Name]

Evidence:

• Directory structure shows: [what indicates this pattern]
• Example paths:
  • path/to/adapter/ - [adapter layer]
  • path/to/domain/ - [domain layer]
  • path/to/infrastructure/ - [infrastructure layer]

Confidence: [High/Medium/Low]

[Explain confidence level]

Secondary Patterns: [If any]

[Any mixed or nested patterns]

Architectural Diagram:

[ASCII diagram of discovered architecture]

Key Insights:

• [Any notable architectural decisions or trade-offs visible]

Template: Component Discovery Agent

**Goal:** Identify all major components/modules/services in the codebase.

**Scope:** Entire codebase (focus on [TARGET_AREA if specified])

**Task:**
1. Identify major components:
   - By directory (e.g., `services/`, `components/`, `modules/`)
   - By responsibility (what each component does)
   - By deployment unit (if microservices)
2. For each component, document:
   - Name and location (directory path)
   - Primary responsibility (one sentence)
   - Key technologies used (language, framework)
   - Size/scope (small, medium, large)
3. Map dependencies between components:
   - Which components depend on which?
   - Are dependencies clean or tangled?
4. Identify shared libraries or common code

**Evidence to collect:**
- List of top-level directories
- README files describing components
- Import/dependency patterns
- Package.json, go.mod, or similar dependency files

**Output format:**

Component Discovery

Components Identified: [N]

Component 1: [Name]

• Location: path/to/component/
• Responsibility: [One sentence]
• Technology: [Language + framework]
• Size: [Lines of code or file count]
• Key entry points:
  • file1.ext - [purpose]
  • file2.ext - [purpose]

Component 2: [Name]

[... same structure ...]

Dependency Map:

[Component A] ──→ [Component B]
              ──→ [Shared Lib]
[Component B] ──→ [Shared Lib]
[Component C] ──→ [Component A]
              ──→ [Shared Lib]

Shared Libraries:

• lib/common/ - [what it provides]
• pkg/utils/ - [what it provides]

Dependency Health:

✅ Clean: [Examples] ⚠️ Tangled: [Examples of circular or unclear dependencies]

Template: Layer Discovery Agent

**Goal:** Discover layers/boundaries within components.

**Scope:** [Specific component if multi-component, else entire codebase]

**Task:**
1. Within each component, identify layers:
   - Presentation/API layer (HTTP handlers, controllers, etc.)
   - Business logic layer (use cases, services, domain)
   - Data access layer (repositories, database)
   - Infrastructure layer (external integrations)
2. Document how layers are separated:
   - By directory?
   - By naming convention?
   - By file organization?
3. Check for layer violations:
   - Does presentation layer directly access database?
   - Does business logic depend on infrastructure?
4. Identify patterns used for layer communication:
   - Dependency injection?
   - Interfaces/abstractions?
   - Direct coupling?

**Evidence to collect:**
- Directory structure showing layer separation
- File naming conventions indicating layer
- Import patterns (what imports what)
- Interface/abstraction usage

**Output format:**

Layer Discovery

Component: [Name]

Layers Identified:

Layer 1: [Name - e.g., "HTTP/API Layer"]

• Location: path/to/layer/
• Responsibility: [What it does]
• Key files:
  • file1.ext - [purpose]
  • file2.ext - [purpose]
• Dependencies: [What it depends on]

Layer 2: [Name - e.g., "Business Logic"]

[... same structure ...]

Layer 3: [Name - e.g., "Data Access"]

[... same structure ...]

Layer Communication Pattern:

[How layers interact - interfaces, DI, direct calls, etc.]

Layer Diagram:

┌─────────────────────┐
│   HTTP/API Layer    │
└─────────┬───────────┘
          │
┌─────────▼───────────┐
│   Business Logic    │
└─────────┬───────────┘
          │
┌─────────▼───────────┐
│   Data Access       │
└─────────────────────┘

Layer Health:

✅ Clean separation: [Evidence] ⚠️ Violations found: [Examples with file:line]

Repeat for other components if multi-component system

Template: Organization Discovery Agent

**Goal:** Understand the organizing principle of this codebase.

**Scope:** Entire codebase

**Task:**
1. Identify primary organization principle:
   - By layer (all controllers together, all models together)
   - By feature (each feature has its own directory with all layers)
   - By domain (organized around business domains)
   - By component type (frontend, backend, shared)
   - Mixed or unclear
2. Document file naming conventions:
   - kebab-case, snake_case, camelCase?
   - Suffixes or prefixes? (e.g., `UserController`, `user.controller.ts`)
3. Identify test organization:
   - Co-located with source?
   - Separate test directory?
   - Naming convention for tests?
4. Note configuration and build setup:
   - Where are config files?
   - Build tool used?
   - Environment-specific configs?

**Evidence to collect:**
- Directory structure examples
- File naming examples
- Test file locations
- Config file locations

**Output format:**

Organization Discovery

Primary Organization: [Principle Name]

Evidence:

• Feature X has all its files in: path/to/feature/
• OR: Controllers are all in: path/controllers/, Models in: path/models/

Example structure:

[Show representative directory tree]

File Naming Convention:

• Style: [kebab-case, snake_case, camelCase, etc.]
• Pattern: [Describe pattern]
• Examples:
  • example-file-1.ext
  • example-file-2.ext

Test Organization:

• Location: [Co-located or separate]
• Pattern: *.test.ext, *_test.ext, test/*, etc.
• Examples:
  • Source: src/service.ts
  • Test: src/service.test.ts

Configuration:

• Location: path/to/configs/
• Environment handling: [How envs are managed]
• Build tool: [Make, npm, cargo, etc.]

Key Insights:

• [Notable organizational choices]
• [Any inconsistencies or legacy patterns]

Deep Dive Agent Prompts

Template: Adaptive Deep Dive Agent

**Goal:** Explore [TARGET] within [DISCOVERED_PERSPECTIVE].

**Context from Discovery Phase:**
- **Architecture:** [Discovered pattern]
- **This area is:** [Component/Layer/Module name]
- **Responsibility:** [What this area handles]
- **Location:** [Directory paths]
- **Technologies:** [Stack for this area]
- **Related areas:** [Dependencies/connections]

**Task:**
1. **Find [TARGET] in this area:**
   - Search for relevant files containing [TARGET] implementation
   - Identify entry points (APIs, handlers, functions)
   - Document with file:line references

2. **Trace execution flow:**
   - Follow [TARGET] through this area's layers/components
   - Document each step with file:line
   - Note data transformations
   - Identify validation/error handling

3. **Document patterns:**
   - What patterns are used in this area for [TARGET]?
   - Error handling approach
   - Testing approach
   - Integration approach with other areas

4. **Identify integration points:**
   - How does this area connect to others for [TARGET]?
   - What interfaces/APIs are used?
   - What data is passed between areas?

**Boundaries:**
- **Stay within:** [Directory scope for this perspective]
- **Maximum depth:** [Based on layer - don't trace into frameworks]
- **Focus:** [TARGET] specifically (don't document unrelated code)

**Output Format:**

Deep Dive: [TARGET] in [PERSPECTIVE_NAME]

Overview

[2-3 sentences about how [TARGET] works in this area]

Entry Points

File: path/to/file.ext:line Function/Handler: functionName Triggered by: [API call, event, function call, etc.]

Execution Flow

Step 1: [Layer/Stage Name]

• File: path/to/file.ext:line
• What happens: [Description]
• Key code:

  [Relevant snippet if helpful]
  

Step 2: [Next Layer/Stage]

[... same structure ...]

[... repeat for all steps ...]

Data Transformations

• Input format: [Describe]
• Transform 1: At file.ext:line - [what changes]
• Transform 2: At file.ext:line - [what changes]
• Output format: [Describe]

Patterns Observed

• Error handling: [Approach with example]
• Validation: [Where and how]
• Testing: [Test patterns if visible]
• Integration: [How it connects to other areas]

Integration Points

Outbound: Calls to Other Areas

• To [Area X]: Via interface/api at file.ext:line
  • Purpose: [Why]
  • Data passed: [What]

Inbound: Called by Other Areas

• From [Area Y]: Via interface/api at file.ext:line
  • Purpose: [Why]
  • Data received: [What]

Key Files for [TARGET]

1. path/file1.ext:line - [Primary implementation]
2. path/file2.ext:line - [Secondary/helper]
3. path/file3.ext:line - [Integration point]

Notes

• [Any discoveries not fitting above categories]
• [Gaps: "Could not find X in this area"]
• [Surprises: "Unexpected implementation choice"]

Common Mistakes

❌ Bad	✅ Good
Skip discovery, assume structure	Always run Phase 1 discovery first
Use same deep dive agents for all codebases	Adapt Phase 2 agents based on Phase 1
Accept vague discoveries	Require file:line evidence
Run explorers sequentially	Dispatch all in parallel (per phase)
Skip synthesis step	Always integrate discovery + deep dive
Provide raw dumps	Synthesize into actionable guidance
Use for single file lookup	Use Read/Grep instead

Integration with Other Skills

Skill	When to use together
ring:brainstorming	Use ring:exploring-codebase in Phase 1 (Understanding) to gather context
ring:writing-plans	Use ring:exploring-codebase before creating implementation plans
ring:executing-plans	Use ring:exploring-codebase if plan execution reveals gaps
ring:systematic-debugging	Use ring:exploring-codebase to understand system before debugging
ring:dispatching-parallel-agents	This skill is built on that pattern (twice!)

Output Format

When skill completes, provide:

1. Synthesis Document

[As defined in Phase 4.2 - includes both discovery and deep dive]

2. Structural Insights

**Discovered Architecture:**
- Pattern: [Name]
- Components: [List]
- Layers: [List]
- Organization: [Principle]

**[TARGET] Implementation:**
- Present in: [N components/layers]
- Entry points: [List with file:line]
- Integration: [How areas connect]
- Patterns: [Consistent patterns observed]

3. Next Step Recommendations

[As defined in Phase 5 - context-aware based on user goal]

Verification

After completing exploration:

✅ Phase 1 (Discovery) completeness:

• Architecture pattern identified with evidence
• All major components/modules enumerated
• Layers/boundaries documented
• Organization principle clear
• File:line references for structural elements

✅ Phase 2 (Deep Dive) completeness:

• All discovered perspectives explored
• [TARGET] found and documented in each area
• Execution flows traced with file:line
• Integration points identified
• Patterns documented per area

✅ Synthesis quality:

• Discovery and deep dive integrated
• Cross-cutting insights identified
• Inconsistencies explained
• Implementation guidance specific
• Next steps clear and actionable

Adaptive Examples

Example 1: Microservices Architecture

Phase 1 Discovery finds:

• 5 microservices (Auth, User, Order, Payment, Notification)
• Each service is independent
• Event-driven communication via message bus

Phase 2 adapts:

• Launch 5 deep dive agents (one per service)
• Each explores target within their service
• Focus on event publishing/subscribing for integration

Example 2: Monolithic Hexagonal Architecture

Phase 1 Discovery finds:

• Single application
• Hexagonal architecture (adapters + domain)
• 4 layers: HTTP → Application → Domain → Infrastructure

Phase 2 adapts:

• Launch 4 deep dive agents (one per layer)
• Each explores target within their layer
• Focus on dependency inversion at boundaries

Example 3: Feature-Organized Monolith

Phase 1 Discovery finds:

• Features organized in separate directories
• Each feature has its own layers
• 6 major features identified

Phase 2 adapts:

• Launch 6 deep dive agents (one per feature)
• Each explores target within their feature
• Focus on shared code and cross-feature integration

Key Principles

Principle	Application
Discover, then dive	Phase 1 discovery informs Phase 2 exploration
Adaptive parallelization	Number and type of agents matches structure
Evidence-based	All discoveries backed by file:line references
Autonomous	Codebase reveals its own structure
Synthesis required	Raw outputs must be integrated
Action-oriented	Always end with next steps
Quality gates	Verify each phase before proceeding

Required Patterns

This skill uses these universal patterns:

• State Tracking: See skills/shared-patterns/state-tracking.md
• Failure Recovery: See skills/shared-patterns/failure-recovery.md
• TodoWrite: See skills/shared-patterns/todowrite-integration.md

Apply ALL patterns when using this skill.

Notes

• Performance: Two phases complete faster than naive sequential exploration
• Cost: Uses haiku model (cost-effective for exploration)
• Adaptability: Works for any architecture (hexagonal, microservices, MVC, etc.)
• Scalability: Handles codebases from small (2-3 components) to large (10+ services)
• Reusability: Synthesis documents serve as permanent reference