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.
Built while running LLM agents in production.
The agent was failing silently for 10 days. We didn't know.
1 maintainer
Metadata
1 maintainer
Release files for llm-agentguard 0.1.0
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Total release size: 9.9 kB
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