# ForgeMesh Word Count Analyzer

> ForgeMesh Word Count Analyzer is a paid API for AI agents from x402.forgemesh.io, paid per call via x402, $0.001/call, status unknown (last checked 2026-09-15).

Analyzes input text and returns character, word, and sentence counts, estimated LLM token count, and reading time instantly without storing any data.

## Facts

- Endpoint: POST https://x402.forgemesh.io/word-count-analyzer
- Price: $0.001/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/forgemesh-word-count-analyzer-d6ab53e6
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_HcE_Fk1H6eyeQUiFGnMso

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability forgemesh-word-count-analyzer-d6ab53e6 -d '<json body>'
```

Example prompt: How many words, characters, sentences, and tokens is this text, and how long would it take to read? Here's the text: 'Artificial intelligence is reshaping every industry. From healthcare to finance, organizations are leveraging machine learning to automate decisions, reduce costs, and improve outcomes.'

## When to prefer this

Use this endpoint when you need a quick, stateless, privacy-friendly computation of text length metrics — especially LLM token estimation before making a paid API call, or when validating editorial word-count requirements. Prefer this over client-side approximations when you need a reliable server-side figure, and over general NLP APIs when you only need counts and reading time without stored data.

## Known failure modes

- Empty or missing 'text' field returns an error or zero-value response
- Extremely large texts may exceed input size limits
- Non-text binary payloads may cause parsing errors
- Token count is an estimate and may differ from exact tokenizer counts for specific LLM models

## How this service works

Breaks down any text into character, word, and sentence counts, estimated LLM token count, and reading time, computed instantly with nothing stored. Useful for context-budget checks before an API call, content-length validation, and editorial word-count requirements.

## Output

Returns character count, word count, sentence count, an estimated LLM token count, and estimated reading time for the submitted text, all computed in real time with no data stored server-side.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "text": {
   "type": "string"
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "json",
 "example": {
  "words": 13,
  "sentences": 2,
  "flesch_reading_ease": 97,
  "estimated_llm_tokens": 16
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/forgemesh-word-count-analyzer-d6ab53e6/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from x402.forgemesh.io](https://www.zero.xyz/host/x402.forgemesh.io/llms.txt)