Parser Generator
Expert skill for parser generation and implementation using LL, LR, LALR, PEG, and Pratt parsing techniques
Best use case
Parser Generator is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Expert skill for parser generation and implementation using LL, LR, LALR, PEG, and Pratt parsing techniques
Teams using Parser Generator should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/parser-generator/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Parser Generator Compares
| Feature / Agent | Parser Generator | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Expert skill for parser generation and implementation using LL, LR, LALR, PEG, and Pratt parsing techniques
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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
```json
{
"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": { "type": "string" },
"resolution": { "type": "string" }
}
}
},
"generatedFiles": {
"type": "array",
"items": { "type": "string" }
}
}
}
```Related Skills
color-palette-generator
Generate accessible color palettes with WCAG compliance
tracing-schema-generator
Generate distributed tracing schemas for OpenTelemetry with Jaeger/Zipkin integration
metrics-schema-generator
Generate metrics schemas for Prometheus, OpenTelemetry, and Grafana dashboards
log-schema-generator
Generate structured logging schemas with correlation ID patterns and ELK/Splunk integration
load-test-generator
Generate load test scripts for k6, Locust, and Gatling from OpenAPI specs
graphql-schema-generator
Generate GraphQL schemas from data models with resolver stubs and federation support
docs-site-generator
Generate documentation sites using Docusaurus, MkDocs, or VuePress
dependency-graph-generator
Generate module dependency graphs with circular dependency detection and coupling metrics
dashboard-generator
Generate monitoring dashboards for Grafana and DataDog with alert integration
c4-diagram-generator
Specialized skill for generating C4 model architecture diagrams. Supports Structurizr DSL, PlantUML, and Mermaid formats with multi-level abstraction (Context, Container, Component, Code).
adr-generator
Specialized skill for generating and managing Architecture Decision Records (ADRs). Supports Nygard, MADR, and custom templates with auto-numbering, linking, and status management.
typespec-sdk-generator
Microsoft TypeSpec-based API and SDK generation