Word Counter · Analyze text statistics
Analyze text to return word count, character count, and structural statistics.
What it does
Analyze text to return word count, character count, and structural statistics.
- Validate content length against platform limits
- Calculate reading time estimates
- Audit document word counts for billing
Ideal buyer
Content platforms, editors, and applications needing lightweight text analysis without heavy NLP infrastructure.
Run this through your governed agent wallet.
- 01Bootstrap AXON once with
npx @axon402/init. - 02Use the AXON runtime MCP tools to
search_x402_servicesorinspect_x402_offerfor this service. - 03Quote, test-buy, then run the governed paid fetch through AXON.
Send this
Prompt for your agent
A natural-language instruction for your LLM agent — with this endpoint exposed as a tool — to call this resource. Not sent to the endpoint; the endpoint consumes the JSON body below.
Pasting this prompt into a raw ChatGPT or unconfigured agent will notexecute the paid endpoint flow. Run it through an agent with the AXON runtime / MCP tools exposed (see “Use with AXON” above) so the 402 challenge, quote, and governed fetch are handled for you.
“Count the words and characters in this article: 'The quick brown fox jumps over the lazy dog.'”
Endpoint request body
The JSON payload your agent sends to the endpoint.
{
"text": "The quick brown fox jumps over the lazy dog."
}Advanced HTTP details
For integrators who need the raw protocol surface. Most agents should use AXON above instead of calling these directly.
curl fallback
curl https://word-counter-production.up.railway.app/api/count \ -H "Content-Type: application/json" \ -H "X-PAYMENT: [signed_payment_envelope]" \ -d '{"text":"The quick brown fox jumps over the lazy dog."}'
Payment & settlement details
Raw on-chain settlement parameters. AXON above handles these automatically through quote / test-buy / governed fetch.
Price & network
Trust & risk
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Category proxy — we don't track live co-purchase signals yet.