planghq/plang/skill
Claude Code and agent skill by planghq/plang
- community
Checking that the SKILL.md file is still in the repository.
Expert guidance for Plang programming language (plang.is). Use when the user asks about Plang syntax, wants to generate Plang code, needs help debugging Plang goals, wants to understand Plang patterns, or is working on Plang projects. Plang is a natural language pseudo-code language with goal-based architecture using SQLite databases.
Install
npx vskill@latest install planghq/plang/skillSKILL.md
Plang Programming Language
Overview
Plang is a natural language programming language that uses pseudo-code syntax and goal-based architecture. Each file represents a "goal" containing steps written in natural language. Use this skill when working with Plang code generation, debugging, or architectural guidance.
Quick Start
For comprehensive syntax and examples, read the appropriate reference files:
- Basic syntax: Read syntax.md for variable handling, database operations, HTTP requests, control flow
- Common patterns: Read patterns.md for proven implementation patterns
- Database schemas: Read database.md for table creation and data modeling
Core Concepts
Goal Structure
Goals are Plang's fundamental unit. Each goal is a file containing steps:
Natural Language Steps
Steps are written in natural language with specific patterns Plang recognizes:
Key Design Principles
- SQLite-first: Presume SQLite for all database operations unless specified
- Goal-based: Break functionality into discrete goals (files)
- Natural language: Write steps as readable instructions
- Variable passing: Use
%variableName%syntax throughout - Error handling: Use
on errorclauses and validation
When to Generate Plang Code
Generate Plang goals when the user:
- Asks to "create a Plang goal for..."
- Requests database operations (Plang excels at CRUD)
- Needs API integration code
- Wants to build web applications with UI
- Requires LLM integration
- Needs file processing workflows
- Wants event-driven architectures
Code Generation Guidelines
1. Start with Clear Goal Names
2. Use Proper Variable Syntax
3. Follow Database Conventions
4. Structure Complex Goals Properly
For complex operations, break into sub-goals with option of parameters:
5. Use Transactions Appropriately
Common Task Patterns
Database CRUD
API Integration
Form Processing
File Processing
Debugging Plang Code
Common Issues
Variable not found:
- Ensure variables are written to before reading:
write to %varName% - Check variable scope (variables from sub-goals need to be returned)
Database errors:
- Verify table exists and columns match
- Check data types match column definitions
- Ensure foreign key relationships are valid
Goal not found:
- Check file path is correct (relative paths supported)
- Verify goal name matches filename (case-sensitive)
HTTP errors:
- Add error handlers:
on error status code = 404, call HandleNotFound - Check API authentication headers
- Verify URL and request body format
Debug Output
Architecture Patterns
Microservice-Style Goals
Organize by feature domain:
Event-Driven Pattern
Multi-Datasource Pattern
Note: For sqlite, attaching two datasource, the first datasource uses main. prefix
Reference Files
This skill includes comprehensive reference documentation:
references/syntax.md
Complete syntax reference covering:
- Variable handling and operations
- Database operations (SELECT, INSERT, UPDATE, DELETE)
- HTTP operations (GET, POST with error handling)
- File operations (read, write, CSV, Excel, JSON)
- Control flow (if/then, loops, foreach)
- UI operations (rendering, DOM manipulation)
- LLM integration
- Events and goal control
references/patterns.md
Proven implementation patterns:
- Database patterns (transactions, upsert, pagination)
- API integration patterns (auth, retry, pagination)
- Error handling patterns
- Payment processing patterns
- UI patterns (forms, modals, progressive enhancement)
- LLM processing patterns
- File processing patterns
- Authentication patterns
- Email patterns
- Testing patterns
references/database.md
Database schema patterns:
- Table creation syntax
- Index patterns
- Column modifications
- Common schemas (users, orders, transactions, analytics)
- Data integrity patterns
- Multi-database queries
Best Practices
- Read references first: Before generating code, read the relevant reference file
- Use transactions: For multi-step database operations, wrap in transactions
- Validate inputs: Always validate user input and required parameters
- Handle errors: Add error handlers for external calls (APIs, file operations)
- Use meaningful names: Goal names and variables should be self-documenting
- Break down complexity: Split complex logic into multiple goals
- Leverage caching: Use cache for expensive operations (set cache, get cache)
- Test incrementally: Build and test goals one at a time
Example: Complete Feature Implementation
Here's a complete example showing best practices:
This example demonstrates:
- Input validation
- Transaction management
- Error handling
- Goal composition
- Database operations
- UI rendering
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingSkill/SKILL.md
Popularity
- Repository stars
- 62
- Repository forks
- 9
- 7-day trend score
- 21
Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 19 Mar 2026, 7 months ago.
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