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Creates comprehensive feature documentation for humans and AI to understand features, resolve bugs, and extend functionality. Use after complete feature implementation (may span multiple commits). Generates feature docs, updates godoc, and creates testable examples.

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SKILL.md

name documentation
description Creates comprehensive feature documentation for humans and AI to understand features, resolve bugs, and extend functionality. Use after complete feature implementation (may span multiple commits). Generates feature docs, updates godoc, and creates testable examples.

Feature Documentation

Creates comprehensive feature documentation for humans and AI to use for future bug resolution, feature extensions, and codebase understanding.

When to Use

  • After a complete feature is implemented (may span multiple commits)
  • When adding significant new functionality to the codebase
  • NOT for: individual commits, bug fixes, minor refactors

Purpose

Generate documentation that helps:

  • Humans: Understand what the feature does and how to use it
  • AI: Context for future bug fixes and feature extensions
  • Team: Onboarding and knowledge sharing

This is NOT a changelog - it's an introduction to the feature.

Workflow

1. Understand Feature Scope

  • Review all commits related to the feature
  • Identify all modified/new files
  • Understand the problem being solved
  • Map out integration points with existing system

2. Analyze Architecture

  • Identify core domain types
  • Map data/control flow
  • Document design decisions (WHY choices were made)
  • Note patterns used (vertical slice, self-validating types, etc.)

3. Generate Documentation Artifacts

Primary: Feature Documentation (docs/[feature-name].md)

  • Problem & solution: What problem does this solve?
  • Architecture: How does it work?
  • Usage examples: How do I use it?
  • Integration: How does it fit into the system?

Secondary: Code Comments

  • Update package godoc to reflect feature's role
  • Add godoc to key types explaining their purpose
  • Create testable examples (Example_* functions) when helpful

4. Validate Documentation

  • Can someone unfamiliar understand the feature?
  • Can AI use this for bug fixes without reading all code?
  • Are design decisions clearly explained?
  • Are integration points documented?

Documentation Template

# [Feature Name]

## Problem & Solution
**Problem**: [What user/system problem does this solve?]

**Solution**: [High-level approach taken]

## Architecture

### Core Types
- `TypeName` - [Purpose, why it exists, key responsibility]
- `AnotherType` - [Purpose, why it exists, key responsibility]

### Design Decisions
- **Why [Decision]**: [Rationale - connects to coding principles]
  - Example: "UserID is a custom type (not string) to avoid primitive obsession and ensure validation"
- **Why [Pattern]**: [Rationale]
  - Example: "Vertical slice structure groups all user logic together for easier maintenance"

### Data Flow

[Step-by-step flow diagram or description] Input → Validation → Processing → Storage → Output


### Integration Points
- **Consumed by**: [What uses this feature]
- **Depends on**: [What this feature uses]
- **Events/Hooks**: [If applicable]

## Usage

### Basic Usage
```go
// Common case example
package main

func example() {
    // Real, runnable code
}

Advanced Scenarios

// Complex case example
package main

func advancedExample() {
    // Real, runnable code showing edge cases
}

Testing Strategy

  • Unit Tests: [What's covered, approach]
  • Integration Tests: [What's covered, approach]
  • Coverage: [Percentage and rationale]

Future Considerations

  • [Known limitations]
  • [Potential extensions]
  • [Related features that might be built on this]

References

  • [Related packages]
  • [External documentation]
  • [Design patterns used]

## Code Comment Guidelines

**Package-Level Documentation:**
```go
// Package [name] provides [high-level purpose].
//
// [2-3 sentences about what problem this solves and how]
//
// Core types:
//   - Type1: [Purpose]
//   - Type2: [Purpose]
//
// Example usage:
//   [Simple example showing typical usage]
//
// Design notes:
//   - [Key design decision]
//   - [Why certain patterns were used]
package name

Type-Level Documentation:

// TypeName represents [domain concept].
//
// [Explain why this type exists - design decision]
// [Explain validation rules if self-validating]
// [Explain thread-safety if relevant]
//
// Example:
//   id, err := NewUserID("usr_123")
//   if err != nil {
//       // handle validation error
//   }
type TypeName struct {
    // ...
}

Testable Examples:

// Example_TypeName_Usage demonstrates typical usage of TypeName.
func Example_TypeName_Usage() {
    id, _ := NewUserID("usr_123")
    fmt.Println(id)
    // Output: usr_123
}

// Example_TypeName_Validation shows validation behavior.
func Example_TypeName_Validation() {
    _, err := NewUserID("")
    fmt.Println(err != nil)
    // Output: true
}

Output Format

After generating documentation:

📚 FEATURE DOCUMENTATION COMPLETE

Feature: [Feature Name]

Generated Artifacts:
✅ docs/[feature-name].md (created)
✅ Package godoc updated in [package]/[file].go
✅ Type documentation for:
   - TypeName1 ([file]:line)
   - TypeName2 ([file]:line)
✅ Testable examples:
   - Example_TypeName1_Usage
   - Example_TypeName2_Validation

Documentation covers:
- Problem & Solution overview
- Architecture with design decisions
- Core types: [list]
- Data flow diagram
- Integration points: [list]
- Usage examples (basic + advanced)
- Testing strategy
- Future considerations

📝 Next Steps:
1. Review docs/[feature-name].md for accuracy
2. Run `go test` to verify testable examples execute correctly
3. Consider: Does this help future you/AI understand the feature?

Would you like to:
1. Commit documentation as-is
2. Refine specific sections
3. Add more examples
4. Add testable examples to code

Key Principles

Documentation is NOT:

  • A changelog of commits
  • Implementation details without context
  • API reference without explanation
  • Generated automatically without understanding

Documentation IS:

  • Explaining WHY decisions were made
  • Providing context for future changes
  • Showing how pieces fit together
  • Helping both humans and AI understand intent

AI-Friendly Documentation: When AI tools read this documentation for bug fixes or extensions:

  • They should understand the problem domain
  • They should know which types are central
  • They should understand design constraints
  • They should see how it integrates with the system

See reference.md for complete documentation checklist and examples.