Constrain LLM generation to produce valid JSON, XML, and code outputs.
npx skills add https://github.com/JKhyro/HERMES-AGENT --skill guidance-jkhyro
Please help me install this Agent Skill. Skill: guidance Source: https://github.com/JKhyro/HERMES-AGENT/tree/main/skills/mlops/inference/guidance Command: npx skills add https://github.com/JKhyro/HERMES-AGENT --skill guidance-jkhyro
Guidance removes the guesswork from LLM output generation by enforcing syntax, structure, and field-level constraints so models produce valid results instead of messy retries and post-processing.
Ask Guidance to generate a valid JSON object with constrained fields for a person profile.
High-intent search queries and answers about installing and using this skill.
Constrained generation forces an LLM to produce valid JSON by applying grammar enforcement and field-level constraints during inference, eliminating the need for post-processing. This guarantees structured outputs match your exact schema.
Yes, regex validation enforces token-level pattern constraints on specific LLM output fields like emails, dates, and IDs. This guarantees generated text matches exact format requirements during generation, preventing invalid data.
Token healing repairs boundary artifacts at prompt endings to ensure smooth transitions into structured outputs. You need it when enforcing grammar or syntax constraints to prevent malformed tokens and maintain generation continuity.
Constrained generation works with local runtimes like Transformers and llama.cpp and API models. This backend flexibility ensures deterministic format control and grammar enforcement across different deployment environments without changing your workflow.
Build multi-step agent workflows by applying selection and control flow constraints to drive branching logic and tool use. This ensures models follow deterministic paths and execute ReAct-style loops reliably within enforced grammatical structures.
The best way to guarantee valid XML and code generation is by applying grammar enforcement constraints during inference. This directly controls output structure and ensures syntax compliance for complex formats without relying on fragile validation passes.
superfhpGenerate valid JSON, XML, and code using regex and grammatical constraints.
zhnnky329Classify parsed subquestions into standard mathematical modeling problem types.
AlvaroBianoConstrain LLM outputs with regex and grammars for valid JSON, XML, or code.
ovachieverConstrain LLM outputs to valid JSON, XML, and code using regex and grammar constraints.
