Transform business rules into ExecDSL-compliant JSON DSL with validation.
npx skills add https://github.com/SukiEva/CheckEngine --skill generate-execdsl
Please help me install this Agent Skill. Skill: generate-execdsl Source: https://github.com/SukiEva/CheckEngine/tree/main/.codex/skills/generate-execdsl Command: npx skills add https://github.com/SukiEva/CheckEngine --skill generate-execdsl
This skill converts business rules into a JSON DSL that complies with the current ExecDSL implementation constraints, and uses the repository's built-in validation script to perform post-generation checks and repairs. It helps generate the variables, steps, and on_fail structure from natural language prompts, validation rules, and SQL check requirements, and to verify that candidate DSLs satisfy the repository's check_engine parsing, references, message templates, and SQL safety rules.
Provide your business requirements in natural language and run the generator to produce and validate the ExecDSL JSON until it passes project checks.
High-intent search queries and answers about installing and using this skill.
You provide natural language prompts, validation rules, and SQL check requirements to generate a JSON DSL. The system transforms these inputs into an ExecDSL-compliant structure containing variables, steps, and on_fail configurations.
To validate generated DSL against repository check_engine parsing, use the built-in validation script. It checks references, message templates, and SQL safety rules, automatically repairing issues through up to three iterative fix cycles.
Yes, you can use natural language prompts to generate variables and steps for ExecDSL. The system interprets your input to automatically build the top-level DSL structure and aligns it with required validation rules and safe SQL usage.
The validation process handles SQL safety rules and message templates by verifying candidate DSLs against the repository's built-in validator. It ensures proper outputs and consumes structures, applying iterative fixes when constraints are not met.
A key limitation of automated DSL generation is the maximum of three iterative validation cycles. If the candidate DSL still fails repository check_engine parsing, reference checks, or SQL safety rules after three repair attempts, manual intervention is required.
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