SiteCheck Text Tone Analyzer

x402

SiteCheck Text Tone Analyzer is a paid API for AI agents from api.sitecheck-api.workers.dev, paid per call via x402, $0.002/call, status unknown (last checked 2026-10-16).

Analyzes a passage of text for tone, sentiment, emotions, formality, reading level, and actionable writing suggestions

Price / call$0.002

Seller volume →—

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StatusUnknown

How this service works

Pay-per-call tools for AI agents: image generation, speech-to-text, text-to-speech, embeddings, LLM chat, website audits and contact enrichment, web page to Markdown reader, PDF to text, sitemap URLs, tech stack detection, translation, exchange rates, e-mail pre-check, domain RDAP/DNS lookup, Solana token checks, trending tokens and wallet holdings, plus business and compliance data (EU VAT/VIES, IBAN, LEI/GLEIF, US recalls, OSHA/EPA violations, UK insolvency notices). Also: SEO metadata, link checking, redirect chains, security headers, mail DNS (SPF, DMARC, DKIM), QR codes, language detection, photo EXIF, identifier validation, image OCR, SEC filings, SEC financials, Congress bills, macro rates, UK company data, GitHub repo stats, Hacker News, Wikipedia, gas prices, Solana swap quotes, ERC-20 token checks, ENS names, EVM wallet balances, EVM balances, transactions and contract calls, Solana transactions and accounts, crypto prices, candles and order books, DeFi TVL, yields and stablecoins, SEC insider trades, weather, geocoding and holidays, IP owners and postcodes, npm, PyPI and crates package data and vulnerabilities, GitHub profiles, arXiv papers and DOIs, structured extraction, summaries, sentiment and reranking, HTML tables and RSS feeds, Bitcoin fees, addresses and transactions, Bitcoin address balances, Bitcoin transaction status, EVM calldata decoding, verified EVM contracts, Hyperliquid perpetual markets, Hyperliquid account positions, Polymarket odds, crypto fear and greed, DeFi fees, DEX volume, company registries of four countries, ISIN, CUSIP and ticker lookup, SEC full-text search, SEC 8-K events, FDA drug labels, FDA adverse event counts, clinical trials, PubMed articles, US federal grants, EU public tenders, NPI provider lookup, US address geocoding, USGS earthquakes, NWS weather alerts, sunrise and moon times, time zone conversion, distance and bearing, GDACS disaster alerts, llms.txt checks, AI crawler access, tracker and cookie audits, certificate transparency, site logos and icons, GitHub releases, GitHub issues, Stack Overflow answers, read-only Wikidata queries, text moderation, image descriptions, text classification, named entity extraction, PII redaction, phone number checks, cron explanations, JSON Schema validation, whale transfers, SSL certificate expiry, Markdown to HTML, PageSpeed scores, Product Hunt launches, sanctions screening (OFAC, EU, UN, UK), flight fare search, YouTube transcripts, speech to text from media links, perpetual funding rates, crypto technical indicators, crypto news headlines, crypto spot conversion, World Bank macro indicators, loan and investment calculator, grammar checks, readability scores, keyword extraction, text diffs, transliteration and slugs, text chunking, subtitle translation, tone rewrites, working days, date calculations, unit conversion, book lookup, food nutrition, airport lookup, tide predictions, nearby places, robots.txt checks, hashes, encode and decode, JWT inspection, UUIDs and passwords, User-Agent parsing, subdomain discovery, uptime checks, VIN decoding, UK EORI checks, SWIFT and BIC checks, stock ticker lookup, invoice extraction, resume parsing, address parsing, prediction-market data, multi-chain RPC and chain data, compliance and government data, web data, search and research, AI text jobs. Plus prediction-market search, briefs, quotes and unsigned buy transactions, powered by Panta. Payment: x402, USDC on Base, Solana or Arc. No signup, no API key.

Output

Returns a JSON object containing an array of tone labels (e.g. 'friendly', 'polite'), a sentiment string (positive/negative/neutral), a map of detected emotions with confidence scores (0–1), a formality score (0–1), a Flesch-Kincaid reading grade level with methodology note, an array of actionable writing improvement suggestions, and a checkedAt ISO timestamp.

Example use cases

Pre-send email tone review

“Before I send this email to my manager, can you check if it sounds too passive-aggressive or overly formal? Here's the text: 'I noticed the deadline was moved again without notifying the team. I wanted to flag this so we can align on expectations going forward.' Tell me the tone, sentiment, and any suggestions.”

Customer support reply quality check

“I just wrote a reply to an angry customer and want to make sure it sounds empathetic and professional before I hit send. Can you analyze this text for tone and emotions: 'We sincerely apologize for the inconvenience caused. Our team is actively working to resolve your issue and will update you within 24 hours.'”

Marketing copy readability audit

“Can you check the reading level and formality of this product description I'm writing for a general consumer audience? I want it to be friendly but not too casual. Here's the text: 'Introducing our all-new blender — powerful enough for the toughest ingredients, simple enough for every morning.'”

Technical details

Endpoint

POSThttps://api.sitecheck-api.workers.dev/api/text/tone?utm_source=zero.xyz

When to prefer

Use this endpoint when you need a multi-dimensional text quality assessment in a single call — combining sentiment, tone labels, emotion scores, formality, reading level, and writing suggestions together. It is well-suited for pre-send email checks, customer support quality assurance, content readability audits, and writing coaching workflows. Prefer this over standalone sentiment APIs when you need the full tonal profile including Flesch-Kincaid grade and concrete improvement suggestions.

Side effects

Text exceeds 10,000 character limit — request rejected or truncated
Empty or missing text field — likely returns an error or empty analysis
Non-English text may produce inaccurate tone or reading level estimates
Model-based outputs are probabilistic and may not reflect nuanced sarcasm or irony accurately
Rate limiting or payment failure via x402 protocol causes 402 response

Input

Schema · Request body

Field	Type	Description
text	string	Text to analyse (max 10,000 characters)

Output

Schema · Response

{
  "type": "json",
  "example": {
    "note": "Model-based tone and sentiment; the reading level is an estimate.",
    "tones": [
      "friendly",
      "polite"
    ],
    "emotions": {
      "gratitude": 0.9,
      "appreciation": 0.8
    },
    "checkedAt": "2026-10-15T18:21:18.118Z",
    "formality": 0.8,
    "sentiment": "positive",
    "suggestions": [
      "Consider adding a deadline reminder",
      "Use a more direct tone for urgent requests",
      "Be mindful of the team's workload"
    ],
    "readingLevel": {
      "method": "Flesch-Kincaid grade, vowel-group syllable estimate, computed in code",
      "fleschKincaidGrade": 2.7
    }
  }
}

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