Split text into retrieval-friendly chunks with a token budget and sentence-aware
Split text into retrieval-friendly chunks with a token budget and sentence-aware boundaries. Overlap between consecutive chunks preserves context across splits — the standard preparation step before embedding. Use this when an agent needs to rAG-ready chunks with token budgets and overlap.
Answeringour last check, 2026-10-02
1 of 1checks answered this week
267 msmedian answer time
$0.002listed price per call
$0.002price it asked us
Paid test badge: not yet. The checks above are free: we call the tool without paying and read the payment request it sends back. The Verified badge needs paid calls whose answers match the promised output, and nobody can buy a badge.
Endpoint
GET https://agenttools-hub.vercel.app/api/v1/dev/text-chunker
| Category | Market data |
|---|---|
| Provider host | agenttools-hub.vercel.app |
| Networks | eip155:8453 |
| Payment schemes | exact |
| Self-reported calls, 30 days | 3 from 1 payers (the provider's figure, not ours) |
Our checks, last 30 days
| Day | Result | HTTP | Asked | Time |
|---|---|---|---|---|
| 2026-10-02 | valid payment request | 402 | $0.002 | 267 ms |
Example input (from the provider)
{
"method": "GET",
"queryParams": {
"overlapTokens": 15,
"targetTokens": 60,
"text": "Retrieval-augmented generation improves factuality. First, documents are split into chunks. Second, chunks are embedded into vectors. Third, the agent retrieves the top matches for a query. Overlap keeps ideas that straddle boundaries intact. Finally, the model answers with citations."
},
"type": "http"
}
Promised output schema (from the provider)
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"properties": {
"input": {
"additionalProperties": false,
"properties": {
"method": {
"enum": [
"GET"
],
"type": "string"
},
"queryParams": {
"properties": {
"overlapTokens": {
"description": "Overlap tokens",
"type": "number"
},
"targetTokens": {
"description": "Target tokens per chunk",
"type": "number"
},
"text": {
"description": "Text",
"type": "string"
}
},
"required": [
"text"
],
"type": "object"
},
"type": {
"const": "http",
"type": "string"
}
},
"required": [
"type",
"method"
],
"type": "object"
},
"output": {
"properties": {
"example": {
"type": "object"
},
"type": {
"type": "string"
}
},
"required": [
"type"
],
"type": "object"
}
},
"required": [
"input"
],
"type": "object"
}