llm-agentguard 0.1.0

Detect silent failures in LLM agents

AgentGuard

Detect silent failures in LLM agents.

Your agent can fail silently.
It returns something that looks correct… but is wrong.
No error. No warning. Just bad output.

AgentGuard detects it automatically.

Install

pip install agentguard

Use

from agentguard import watch
from pydantic import BaseModel

class AgentOutput(BaseModel):
    answer: str
    confidence: float

@watch(schema=AgentOutput)
def my_agent(input):
    return llm_call(input)

If the output is empty, crashes, or doesn't match the schema → you get an alert.

Alerts

Set in your .env:

AGENTGUARD_TELEGRAM_TOKEN=your_bot_token
AGENTGUARD_TELEGRAM_CHAT_ID=your_chat_id

What it detects

• Empty or null output
• Schema violation (wrong structure, missing fields)
• Agent crash (exception swallowed)

No dashboard. No setup. One line.

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Built while running LLM agents in production.
The agent was failing silently for 10 days. We didn't know.