feature-parser

# Feature Parser

Extract structured information from markdown feature proposals.

## Purpose

Transform free-form or template-based markdown proposals into structured data that can be consumed by judges and analyzers.

## Input

Markdown proposal text (either user-written or generated by proposal-builder).

Expected format (from template):
```markdown
# Feature: [Title]

## Overview
[Description]

## Goals
- Goal 1
- Goal 2

## Requirements

### Must Have
- [ ] Requirement 1
- [ ] Requirement 2

### Nice to Have
- [ ] Optional 1

## Constraints
- Constraint 1
- Constraint 2

## Success Criteria
- [ ] Criterion 1
- [ ] Criterion 2

## Related Context
(Optional)
```

## Processing Steps

### Step 1: Extract Feature Title

```markdown
Priority order:
1. H1 heading starting with "Feature:" → extract text after "Feature:"
2. First H1 heading → use as-is
3. First sentence of document → use first 50 chars
4. Fallback → "Unnamed Feature"

Examples:
"# Feature: User Notification System" → "User Notification System"
"# Real-time Notifications" → "Real-time Notifications"
"Add notifications to the app..." → "Add notifications to the app..."
```

### Step 2: Extract Overview/Description

```markdown
Find "## Overview" section:
- Extract all text until next ## heading
- Trim whitespace
- If not found: use first paragraph of document
- If empty: "No description provided"
```

### Step 3: Extract Goals

```markdown
Find "## Goals" section:
- Extract all bullet points (lines starting with -, *, +, or numbered)
- Clean formatting (remove bullet markers, trim whitespace)
- Return as array of strings

Example input:
## Goals
- Notify users of important events
- Support multiple channels
- Easy user configuration

Output: ["Notify users of important events", "Support multiple channels", "Easy user configuration"]

If section not found: []
```

### Step 4: Extract Requirements

```markdown
Find "## Requirements" section, then sub-sections:

**Must Have:**
- Find "### Must Have" subsect