docs: comprehensive package READMEs and API_REFERENCE.md expansion (2,360+ lines) (#116)

* docs: add comprehensive package READMEs for core packages

Created detailed README documentation for 5 core packages:
- pkg/sql/parser: Parser architecture, features, usage patterns
- pkg/sql/tokenizer: Zero-copy tokenization, Unicode support, performance
- pkg/sql/ast: AST node types, visitor pattern, object pooling
- pkg/sql/keywords: Multi-dialect keyword system, categorization
- pkg/linter: Rule system, Phase 1a status, CLI usage

Each README includes:
- Overview and key features
- Usage examples (basic and advanced)
- Architecture and component breakdown
- Best practices and common pitfalls
- Testing instructions
- Performance characteristics
- Related packages and documentation links
- Version history

Impact:
- Addresses 70%+ of documentation gaps identified in exploration
- Provides package-level documentation for developers
- Improves onboarding for contributors
- Complements existing API_REFERENCE.md

Related: #57 (DOC-001: Complete Comprehensive API Reference)

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Co-Authored-By: Claude <noreply@anthropic.com>

* docs: add comprehensive High-Level API section to API_REFERENCE.md

Added complete documentation for pkg/gosqlx high-level convenience API:

**Parsing Functions** (7 functions):
- Parse(), ParseWithContext(), ParseWithTimeout()
- ParseBytes(), MustParse(), ParseMultiple()
- Validate()

**Metadata Extraction** (6 functions):
- ExtractTables(), ExtractTablesQualified()
- ExtractColumns(), ExtractColumnsQualified()
- ExtractFunctions()

**Types**:
- QualifiedName with String() and FullName() methods

**Documentation Includes**:
- Function signatures with parameters and returns
- Usage examples for each function
- Use case descriptions
- Known parser limitations
- Performance comparison vs low-level API
- Complete working example

Content: 338 lines
Coverage: 100% of public gosqlx API

Related: #57 (DOC-001)

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Co-Authored-By: Claude <noreply@anthropic.com>

* docs: add comprehensive Keywords package section to API_REFERENCE.md

Added extensive documentation for pkg/sql/keywords package (631 lines):

Core Types:
- Keywords type with dialect support
- SQLDialect enum (PostgreSQL, MySQL, SQLServer, Oracle, SQLite, Generic)
- KeywordCategory enum (Reserved, DML, DDL, Function, Operator, DataType)

Functions Documented:
- New() - Create keyword registry for dialect
- IsKeyword() - Check if word is keyword (case-insensitive)
- IsReserved() - Check if keyword is reserved
- GetKeyword() - Get detailed keyword information
- GetTokenType() - Get token type for keyword
- IsCompoundKeyword() - Check for compound keywords (GROUP BY, NULLS FIRST, etc.)
- GetCompoundKeywordType() - Get compound keyword token type
- AddKeyword() - Add custom keywords

Keyword Categories:
- Reserved keywords (SELECT, FROM, WHERE, JOIN, etc.)
- DML keywords (DISTINCT, ALL, LIMIT, OFFSET, etc.)
- Compound keywords (GROUP BY, ORDER BY, LEFT JOIN, NULLS FIRST/LAST)
- Window function keywords (ROW_NUMBER, RANK, LAG, LEAD, etc.)

Dialect-Specific Keywords:
- PostgreSQL (ILIKE, MATERIALIZED, RETURNING, CONCURRENTLY, etc.)
- MySQL (UNSIGNED, ZEROFILL, FORCE, IGNORE, etc.)
- SQLite (AUTOINCREMENT, CONFLICT, REPLACE, VACUUM, etc.)

Usage Examples:
- Basic keyword recognition and validation
- Compound keyword detection
- Identifier validation and quoting
- SQL formatting and syntax highlighting
- Dialect switching
- Integration with tokenizer/parser

Performance:
- O(1) hash map lookups
- Pre-allocated keyword maps (~10KB per dialect)
- Thread-safe with no synchronization overhead
- Cache-friendly memory layout

Best Practices:
- Create once, reuse (singleton pattern)
- Use appropriate dialect for database
- Check reserved keywords for identifiers
- Common patterns for syntax highlighting, normalization, quoting

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Co-Authored-By: Claude <noreply@anthropic.com>

* docs: add comprehensive Errors package section to API_REFERENCE.md

Added extensive documentation for pkg/errors package (670 lines):

Core Types:
- ErrorCode - Unique error identifiers (E1xxx, E2xxx, E3xxx, E4xxx)
- Error - Structured error with rich context and hints
- ErrorContext - SQL source context with line/column highlighting

Error Codes (36 codes across 4 categories):
- E1xxx: Tokenizer errors (8 codes)
  - E1001-E1008 (unexpected char, unterminated string, invalid number, etc.)
- E2xxx: Parser syntax errors (12 codes)
  - E2001-E2012 (unexpected token, missing clause, invalid syntax, etc.)
- E3xxx: Semantic errors (4 codes)
  - E3001-E3004 (undefined table/column, type mismatch, ambiguous column)
- E4xxx: Unsupported features (2 codes)
  - E4001-E4002 (unsupported feature, unsupported dialect)

Error Builder Functions:
- NewError() - Create structured error with auto-generated help URL
- WithContext() - Add SQL source context with highlighting (chainable)
- WithHint() - Add actionable suggestions (chainable)
- WithCause() - Add underlying cause error for wrapping (chainable)

Helper Functions:
- IsCode() - Check if error has specific code
- GetCode() - Extract error code from error

Error Formatting Features:
- Multi-line context visualization with line numbers
- Position indicators (^) highlighting error location
- 3-line context window (1 before, error line, 1 after)
- Auto-generated documentation links (https://docs.gosqlx.dev/errors/{code})

Usage Examples:
- Basic error creation
- Error with full context (SQL highlighting)
- Multi-line SQL context visualization
- Error code checking with IsCode()
- Error code extraction with GetCode()
- Programmatic error handling
- Chaining error context (WithContext, WithHint, WithCause)
- Error recovery patterns

Best Practices:
- Always add context for user-facing errors
- Use error codes for programmatic handling (not string matching)
- Provide actionable hints (specific, not vague)
- Chain error context in libraries (enhance lower-layer errors)

Common Error Patterns:
- Pattern 1: Tokenizer error with recovery
- Pattern 2: Parser error with user-friendly message mapping
- Pattern 3: Error logging with structured fields

Error Categories Quick Reference Table:
- E1xxx: Tokenizer errors (lexical analysis)
- E2xxx: Parser syntax errors (parsing)
- E3xxx: Semantic errors (validation)
- E4xxx: Unsupported features (not implemented)

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Co-Authored-By: Claude <noreply@anthropic.com>

* docs: add comprehensive Metrics package section to API_REFERENCE.md

Added extensive documentation for pkg/metrics package (721 lines):

Core Types:
- Metrics - Internal metrics collector (not exported)
- Stats - Performance statistics snapshot with 16 fields

Stats Fields (16 total):
- Basic counts: TokenizeOperations, TokenizeErrors, ErrorRate
- Performance: AverageDuration, OperationsPerSecond
- Pool metrics: PoolGets, PoolPuts, PoolBalance, PoolMissRate
- Query size: MinQuerySize, MaxQuerySize, AverageQuerySize, TotalBytesProcessed
- Timing: Uptime, LastOperationTime
- Errors: ErrorsByType map

Configuration Functions:
- Enable() - Activate metrics collection
- Disable() - Deactivate metrics collection
- IsEnabled() - Check if collection is active

Recording Functions (automatic):
- RecordTokenization() - Record tokenization operation
- RecordPoolGet() - Record pool retrieval
- RecordPoolPut() - Record pool return

Query Functions:
- GetStats() - Get current performance statistics
- LogStats() - Alias for GetStats (logging convenience)
- Reset() - Clear all metrics (testing)

Usage Examples:
- Basic metrics collection
- Production monitoring with periodic reporting
- Error tracking and analysis
- Pool efficiency monitoring
- Query size analysis
- JSON export for APIs
- HTTP metrics endpoint
- Prometheus integration
- Performance alerting with SLOs

Integration Patterns:
- Pattern 1: Application startup (enable early, disable late)
- Pattern 2: Periodic reporting (ticker-based)
- Pattern 3: Testing with metrics (reset before test)

Performance Characteristics:
- Thread Safety: Lock-free atomic operations, RWMutex for error map
- Memory Overhead: ~200 bytes + error map (fixed footprint)
- Performance Impact: ~50ns enabled, ~1ns disabled, O(n) GetStats

Best Practices:
- Enable at application startup (not per-operation)
- Use periodic reporting (1min intervals)
- Monitor pool efficiency (>95% hit rate target)
- Set performance SLOs (error rate, throughput, latency, pool efficiency)

Production Monitoring:
- HTTP /metrics endpoint
- Prometheus integration
- Alert on: high error rate (>1%), slow duration (>1ms), low pool hit rate (<90%), low throughput (<1k ops/sec)
- Metrics dashboard example with formatted output

JSON Export Support:
- All Stats fields have json tags
- Direct marshaling to JSON
- Ready for monitoring systems

Completes API_REFERENCE.md expansion with:
- High-Level API (338 lines)
- Keywords Package (631 lines)
- Errors Package (670 lines)
- Metrics Package (721 lines)

Total new documentation: 2,360 lines across 4 major sections

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Co-Authored-By: Claude <noreply@anthropic.com>

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Co-authored-by: Ajit Pratap Singh <ajitpratapsingh@Ajits-Mac-mini.local>
Co-authored-by: Claude <noreply@anthropic.com>

Author: 3 people