parser-generator

name	Parser Generator
description	Expert skill for parser generation and implementation using LL, LR, LALR, PEG, and Pratt parsing techniques
category	Compiler Frontend
allowed-tools	["Read","Write","Edit","Glob","Grep","Bash"]
graph	{"domains":["domain:software-engineering"],"specializations":["specialization:programming-languages"],"skillAreas":["skill-area:compiler-implementation","skill-area:parsing-data-formats"],"roles":["role:backend-engineer"]}

Parser Generator Skill

Overview

Expert skill for parser generation and implementation using LL, LR, LALR, PEG, and Pratt parsing techniques.

Capabilities

• Generate parsers from grammar specifications (ANTLR, Bison, tree-sitter)
• Implement recursive descent parsers with predictive parsing
• Implement Pratt parsers for expression handling
• Generate LALR/GLR parse tables
• Implement PEG parsers with packrat memoization
• Handle grammar conflicts (shift-reduce, reduce-reduce)
• Generate concrete syntax trees (CST) and AST transformations
• Implement operator precedence parsing

Target Processes

• parser-development.js
• language-grammar-design.js
• ast-design.js
• lsp-server-implementation.js

Dependencies

• ANTLR4
• tree-sitter
• Bison/Yacc

Usage Guidelines

1. Grammar Analysis: Analyze grammar class requirements (LL(k), LALR, etc.) before selecting parser type
2. Conflict Resolution: Document and resolve all shift-reduce/reduce-reduce conflicts explicitly
3. Error Recovery: Implement synchronization points for robust error recovery
4. AST Construction: Design AST node types before implementing production actions
5. Expression Parsing: Use Pratt parsing for complex expression precedence handling

Output Schema

{
  "type": "object",
  "properties": {
    "parserType": {
      "type": "string",
      "enum": ["recursive-descent", "pratt", "lalr", "glr", "peg", "ll"]
    },
    "grammarClass": { "type": "string" },
    "conflicts": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "type":