Decode and inspect any JWT token — extracts header algorithm, payload claims, expiry status, issued-at time, audience, issuer, and subject without requiring the secret — so agents can debug auth issues, check token expiry, and extract identity claims from tokens in pipelines.

Turn event fields into a valid RFC 5545 .ics calendar file — handles timed and all-day events, escaping, line folding, and a deterministic UID for idempotent re-import — so agents can publish events that import cleanly into Google, Apple, and Outlook calendars. Add ?download=1 (or Accept: text/calendar) to receive the raw .ics file with a Content-Disposition attachment header instead of the JSON envelope. Pure compute, no LLM.

Check an IP address against 15 major DNS blacklists (Spamhaus, Barracuda, SORBS, etc.) simultaneously — returns which lists it appears on, a reputation score, and a threat classification so agents can make block/allow decisions instantly.

Translate many independent strings in one request — each with a caller ID preserved in the response — with per-item status, glossary and tone support, and partial success so one bad item never fails the batch, so agents can localize whole string tables in a single call.

Event extraction / event parsing — turn any caption, announcement, listing, or page text into a normalized calendar event via Claude Haiku. Resolves relative dates ("this Saturday 7pm") against post time + timezone, handles all-day/multi-day, and returns title, start/end, venue, address, city, price, organizer, url. Purpose-built for structured event data (no schema to define); pairs with /event-classify and /calendar/ics.

One-call market briefing for agents — BTC/ETH/SOL spot + 24h moves, major fiat crosses (USD/EUR, USD/GBP, USD/JPY, EUR/GBP), Base and Ethereum gas with USD transfer cost, and the crypto fear/greed index. Four sections fetched concurrently with graceful partial failure; any dead section is null with a finding, never a failed call. 60s cache; no API key.

Generate common typo and look-alike variations of a domain and check which are already registered — catches character swaps, omissions, additions, homoglyphs, and alternate TLDs so agents can detect typosquatting and brand-impersonation domains targeting a company.

Transform a source object into a target schema — matches fields by alias and structure deterministically, uses an LLM only for semantic mapping when needed, and supports mapping hints, transforms, and defaults, so agents can reshape data between systems with per-field confidence and a clear report of what mapped and what didn't.

Conform messy or inconsistent JSON to a target schema using Claude Haiku — renames keys, coerces types (string→number, "true"→boolean, etc.), and fills missing fields with null, returning JSON that matches the exact shape the caller specified so agents can normalize data from varied sources into one consistent structure.

Call OpenAI's gpt-5.4-mini via a single pay-per-call x402 endpoint — no OpenAI account or API key needed, pay $0.04 per request in USDC. Standard OpenAI chat.completions request/response shape, capped input and output.

Generate brandable startup/product names from a keyword using prefixes, suffixes, blends, and phonetic patterns, then check .com (or any TLD) availability for each via DNS — returns available names ranked by a brandability heuristic so agents can find a claimable brand without manual brainstorming plus one-by-one availability checks.

Determine a domain's age from registration data and archival history — tries RDAP, then port-43 WHOIS, then a Wayback-based estimate (age_source: rdap | whois | wayback_estimate | null), returning creation date, age in years, first Wayback capture, archived snapshot count, and a maturity signal so agents can assess trustworthiness and detect freshly registered domains used for fraud or phishing — including .io and TLDs without public RDAP.

Query a domain's DNS record across 10 geographically distributed public resolvers simultaneously — returns what each resolver sees, whether results are consistent, propagation percentage, and a readiness score so agents can confirm DNS changes have fully propagated globally.

Extract tabular data from messy text or HTML using Claude Haiku — detects columns and rows in unstructured content and returns clean structured JSON (columns + rows) so agents can turn pasted tables, HTML tables, and delimited text into usable data in one call.

Validate a domain's DNSSEC configuration over DNS-over-HTTPS: DS records at the parent zone, DNSKEY records at the domain, RRSIG signatures, NSEC/NSEC3, plus the validating resolver's AD bit — returns a full chain-of-trust assessment and readiness score so agents can verify DNS integrity before trusting resolution results.

Cheap, fast "is this a dateable event?" filter for social and web text — one tiny Haiku call returns is_event, confidence, and a one-line reason, so agents can screen every post for free-ish and only pay for full extraction on the ones that pass. Front-end filter to /event-extract; intentionally minimal output for cost/latency discipline.

Repair malformed JSON into valid JSON — fixes code fences, trailing commas, single quotes, unquoted keys, bad escapes, duplicate keys, truncation, and JSON buried in prose. A deterministic tokenizer runs first (no LLM cost), with an optional Haiku fallback, plus optional schema validation and type coercion — so agents can rescue broken model output or dirty data in one call.

Extract structured data from resume/CV text using Claude Haiku — returns name, contact info, skills, work experience, and education as clean JSON arrays so agents can automate applicant screening, candidate databases, and recruiting workflows from raw resume text.

Semantic similarity ranking — send a query plus up to 100 candidate texts, get the candidates back ranked by semantic similarity with scores. No vectors, no cosine math, no embedding model to manage: one call, one price, ranked results. Flat $0.02 per call in USDC via x402, no API key. For RAG retrieval, FAQ matching, and search result ordering.

Extract structured data from invoice or receipt text — or directly from an invoice URL (PDF, HTML, or plain text, fetched and parsed server-side) — using Claude Haiku: returns vendor, invoice number, dates, line items, subtotal, tax, total, and currency as clean JSON for accounts-payable, expense processing, and bookkeeping automation.