guidance Skill
Constrain LLM output with grammars; guarantee valid JSON. Published by NousResearch in hermes-agent.
Decision snapshot
Is this a fit?
Research, Includes SKILL.md, Reusable instructions
Compatibility not yet detected.
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Copy skill directory
21 days ago · MIT license
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What is guidance Skill?
Constrain LLM output with grammars; guarantee valid JSON. Published by NousResearch in hermes-agent. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement. See how SkillIndex evaluates profiles.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Research
- Research use cases
Declared skill metadata
- Declared author: Orchestra Research
- Declared license: MIT
- Source file: optional-skills/mlops/guidance/SKILL.md
These fields retain source and confidence evidence from the indexed SKILL.md.
Compatibility and setup
- Install or run with Copy skill directory
When to use guidance Skill
- Use it for research.
Built with
Editorial notes
Source
- Creator: NousResearch
- Repository: NousResearch/hermes-agent
- Skill file: optional-skills/mlops/guidance/SKILL.md
What it does
Constrain LLM output with grammars; guarantee valid JSON.
Skill instructions
Guidance: Constrained LLM Generation When to Use This Skill Use Guidance when you need to: - Control LLM output syntax with regex or grammars - Guarantee valid JSON/XML/code generation - Reduce latency vs traditional prompting approaches - Enforce structured formats (dates, emails, IDs, etc.) - Build multi-step workflows with Pythonic control flow - Prevent invalid outputs through grammatical constraints GitHub Stars: 18,000+ | From: Microsoft Research Installation bash Base installation pip install guidance With specific backends pip install guidance[transformers] Hugging Face models pip install guidance[llamacpp] llama.cpp models Quick Start Basic Example: Structured Generation python from guidance import models, gen Load model (supports OpenAI, Transformers, llama.cpp) lm = models.OpenAI("gpt-4") Generate with constraints result = lm + "The capital of France is " + gen("capital", maxtokens=5) print(result["capital"]) "Paris" Chat format with a local model Constraint support requires
Verified compatibility and discovery
Frequently asked questions
What is guidance?
guidance is a open-source AI agent skill with Copy skill directory. Constrain LLM output with grammars; guarantee valid JSON.
Who is guidance best for?
guidance is best for reusing agent instructions, scripts, and references, research workflows.
How do I install guidance?
Install or run guidance using Copy skill directory. Check guidance for the latest setup command.
Is guidance actively maintained?
guidance may need a closer maintenance check before production use.
Project health auto-fetched from the source repository.
Maintain this resource?
Review this source-backed profile, send a correction with evidence, or link to it from your documentation. Claims verify your relationship to the project; profile facts still require source evidence and editorial review.
