---
title: "AgentGuard vs guidance"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/dipampaul17-agentguard-vs-guidance-ai-guidance"
tools: ["dipampaul17-agentguard", "guidance-ai-guidance"]
---

# AgentGuard vs guidance

*GraphCanon updated Aug 9, 2026*

## Verdict

Pick AgentGuard if agentGuard is a budget-conscious observer for real-time token spending by AI agents and LLMs, integrating with major providers like OpenAI and Anthropic; pick guidance if guidance is a specialized tool written in Jupyter Notebooks that provides a unique language to control large language models (LLMs) across multiple backends such as Transformers, llama.cpp, and OpenAI. It's open-source,轻.

[AgentGuard](https://github.com/dipampaul17/AgentGuard) reports 171 GitHub stars, 10 forks, and 1 open issues, last pushed Jul 31, 2025. [guidance](https://github.com/guidance-ai/guidance) has 22k stars, 1.2k forks, and 316 open issues, last pushed May 21, 2026. Figures are from public GitHub metadata via [AgentGuard's repository](https://github.com/dipampaul17/AgentGuard) and [guidance's repository](https://github.com/guidance-ai/guidance).

| | [AgentGuard](/tools/dipampaul17-agentguard.md) | [guidance](/tools/guidance-ai-guidance.md) |
| --- | --- | --- |
| Tagline | Real-time guardrail that monitors token spend and manages LLM/agent loops in real time | A guidance language for controlling large language models. |
| Stars | 171 | 21,706 |
| Forks | 10 | 1,198 |
| Open issues | 1 | 316 |
| Language | JavaScript | Jupyter Notebook |
| Adopt for | AgentGuard is a budget-conscious observer for real-time token spending by AI agents and LLMs, integrating with major providers like OpenAI and Anthropic. | Guidance is a specialized tool written in Jupyter Notebooks that provides a unique language to control large language models (LLMs) across multiple backends such as Transformers, llama.cpp, and OpenAI. It's open-source,轻 |
| Persona | - | - |
| Runtime | - | - |
| License | MIT | MIT |
| Categories | Evaluation & Observability, Inference & Serving | Inference & Serving, LLM Frameworks |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [AgentGuard](/tools/dipampaul17-agentguard.md) | [guidance](/tools/guidance-ai-guidance.md) |
| --- | --- | --- |
| Maintenance | Dormant (18%) | Steady (60%) |
| Days since push | 373d | 78d |
| Open issues (now) | 1 | 316 |
| Owner type | User | Organization |
| Full report | [trust report](/tools/dipampaul17-agentguard/trust.md) | [trust report](/tools/guidance-ai-guidance/trust.md) |

## Decision facts: AgentGuard

- **Adopt for:** AgentGuard is a budget-conscious observer for real-time token spending by AI agents and LLMs, integrating with major providers like OpenAI and Anthropic.

## Decision facts: guidance

- **Adopt for:** Guidance is a specialized tool written in Jupyter Notebooks that provides a unique language to control large language models (LLMs) across multiple backends such as Transformers, llama.cpp, and OpenAI. It's open-source,轻

## Choose when

### Choose AgentGuard if…

- AgentGuard is primarily JavaScript; guidance is Jupyter Notebook.
- Tags unique to AgentGuard: ai-agents, anthropic, cost-monitoring, observability.
- Also covers Evaluation & Observability.
- When you need precise control over spend and want live updates on token prices

### Choose guidance if…

- guidance is primarily Jupyter Notebook; AgentGuard is JavaScript.
- Tags unique to guidance: backend support, control language, language-models, pip-installable.
- Also covers LLM Frameworks.
- When you need a specific language to finely control various LLM backends including Transformers, llama.cpp, and OpenAI

## When NOT to use AgentGuard

- If you prioritize a different language for your project and cannot use JavaScript
- In cases requiring more elaborate fallback mechanisms than what AgentGuard offers

## When NOT to use guidance

- When your project is strictly confined to using only one type of backend which you can manage without a specialized control language
- If your development environment does not support or prefer Jupyter Notebooks, Guidance may not be the best choice

## Common questions

### What is the difference between AgentGuard and guidance?

AgentGuard: Real-time guardrail that monitors token spend and manages LLM/agent loops in real time. guidance: A guidance language for controlling large language models.. See the comparison table for live GitHub stats and shared categories.

### When should I choose AgentGuard over guidance?

Choose AgentGuard over guidance when AgentGuard is primarily JavaScript; guidance is Jupyter Notebook; Tags unique to AgentGuard: ai-agents, anthropic, cost-monitoring, observability; Also covers Evaluation & Observability; When you need precise control over spend and want live updates on token prices.

### When should I choose guidance over AgentGuard?

Choose guidance over AgentGuard when guidance is primarily Jupyter Notebook; AgentGuard is JavaScript; Tags unique to guidance: backend support, control language, language-models, pip-installable; Also covers LLM Frameworks; When you need a specific language to finely control various LLM backends including Transformers, llama.cpp, and OpenAI.

### When should I avoid AgentGuard?

If you prioritize a different language for your project and cannot use JavaScript In cases requiring more elaborate fallback mechanisms than what AgentGuard offers

### When should I avoid guidance?

When your project is strictly confined to using only one type of backend which you can manage without a specialized control language If your development environment does not support or prefer Jupyter Notebooks, Guidance may not be the best choice

### Is AgentGuard or guidance more popular on GitHub?

guidance has more GitHub stars (21,706 vs 171). Stars measure visibility, not whether either tool fits your constraints.

### Are AgentGuard and guidance open source?

Yes - both are open-source projects on GitHub (AgentGuard: MIT, guidance: MIT).

### Where can I find alternatives to AgentGuard or guidance?

GraphCanon lists graph-backed alternatives at [AgentGuard alternatives](/tools/dipampaul17-agentguard/alternatives) and [guidance alternatives](/tools/guidance-ai-guidance/alternatives) ([AgentGuard markdown twin](/tools/dipampaul17-agentguard/alternatives.md), [guidance markdown twin](/tools/guidance-ai-guidance/alternatives.md)), ranked by typed relationship edges rather than popularity votes.

### Is there a machine-readable version of this comparison?

Yes. The markdown twin at [this comparison](/compare/dipampaul17-agentguard-vs-guidance-ai-guidance.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, AgentGuard or guidance?

AgentGuard: Dormant. guidance: Steady. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.

### Where are the full trust reports for AgentGuard and guidance?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [AgentGuard trust report](/tools/dipampaul17-agentguard/trust); [guidance trust report](/tools/guidance-ai-guidance/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=dipampaul17-agentguard`](/api/graphcanon/graph?tool=dipampaul17-agentguard)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_