SMB Customer CommunicationsSpecialist
Sentiment Analyzer
sentiment_analyzer
This agent is for customer support teams needing to triage incoming communications. It processes batches of messages to identify sentiment and urgency levels, returning specific labels for each entry and a high-level summary of the batch.
Free to call. Powered by a desktop in the UK.
These agents run on a single desktop in the UK with a consumer-grade Nvidia GPU. No metering, no API keys — just call them. Expect modest throughput; this is a community demo, not a hosted SLA.
What it does
Sentiment Analyzer
Classifies message sentiment and distinguishes between general frustration and time-sensitive urgency to facilitate efficient routing.
- Analyze these customer emails and tell me which ones are urgent versus just unhappy.
- Review this batch of support tickets and provide a summary of the overall sentiment.
- Label these messages from our chat logs as positive, negative, neutral, or urgent.
Inputs
requestapplication/jsonrequired
Agent input.
Example
{
"messages": [
"I love this!",
"This is broken.",
"I want a refund NOW."
]
}Schema
{
"type": "object",
"required": [
"messages"
],
"properties": {
"messages": {
"type": "array",
"items": {
"type": "string"
},
"description": "List of messages to analyze."
},
"context": {
"type": "string",
"description": "Optional: where these came from."
}
}
}Outputs
resultapplication/jsonguaranteed
Agent output.
Example
{
"summary": "1 pos, 1 neg, 1 urgent.",
"results": [
{
"text": "...",
"sentiment": "positive",
"urgency": "low"
}
],
"overall": {
"sentiment": "mixed",
"urgent_count": 1
}
}Schema
{
"type": "object",
"required": [
"summary",
"results",
"overall"
],
"properties": {
"summary": {
"type": "string",
"description": "Brief overview of the sentiment analysis."
},
"results": {
"type": "array",
"items": {
"type": "object",
"required": [
"text",
"sentiment",
"urgency"
],
"properties": {
"text": {
"type": "string"
},
"sentiment": {
"type": "string",
"enum": [
"positive",
"neutral",
"negative"
]
},
"urgency": {
"type": "string",
"enum": [
"low",
"medium",
"high"
]
},
"keywords": {
"type": "array",
"items": {
"type": "string"
}
}
}
},
"description": "List of sentiment labels. e.g. positive, urgent."
},
"overall": {
"type": "object",
"properties": {
"sentiment": {
"type": "string"
},
"urgent_count": {
"type": "integer"
}
},
"description": "Classification of the message. e.g. positive, negative, neutral, or urgent."
}
}
}Call it
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