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AIQualityHQ

Automated QA, security guardrails, and token intelligence for prompts and AI agents

  • Community votes0
  • DR by Ahrefs36 no change since last check
  • Started2025

Ahrefs Domain Rating set in type 17 Oct 2026, reset 17 Oct 2026.

AIQualityHQ metrics

Set in type for aiqualityhq.com: Ahrefs Domain Rating and Majestic link data, with the change since the last edition.
MetricValue
Domain Rating36 no change since last check
Trust Flow21 no change since last check
Citation Flow19 no change since last check
Referring domains231 no change since last check
External backlinks14,066 no change since last check

Ahrefs Domain Rating set in type 17 Oct 2026, reset 17 Oct 2026. Lead topic: Business (20). Majestic set 17 Oct 2026, reset 17 Oct 2026. Link data typeset by Majestic. Trust Flow, Citation Flow and Topical Trust Flow are trademarks of Majestic-12 Ltd.

AIQualityHQ domain colophon

From the registry's public RDAP record, checked 17 Oct 2026, 02:50 UTC.
Domain age3 months
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Browser-native platform providing deterministic quality analysis, security scanning, and token optimization for AI prompts and agents.

The story so far

Screenshot of the AIQualityHQ homepage
Homepage of AIQualityHQ

AIQualityHQ is a prompt quality engineering platform that helps teams ship better AI prompts with deterministic analysis. The platform provides eleven browser-native tools organized across five domains: prompt quality linting and contract checking, prompt injection and jailbreak detection, token and cost intelligence, prompt engineering and synthesis, and AI visibility. All core analysis tools run locally in your browser using deterministic rules that produce reproducible results in under 10 milliseconds, with no prompt data leaving your device. AI-powered features like the Prompt Rewriter and AI Audit are clearly labeled and connect to external providers. The platform evaluates prompts across six weighted dimensions: Prompt Structure, Memory & State, Context Grounding, Trust & Accuracy, PII & Privacy, and Security & Safety.

Typeset features

  • Six-dimension quality scoring with weighted evaluation

Pricing

Pricing model: Freemium

Free: $0/month with all 11 browser tools, 6-dimension scoring, injection scanner, token analysis, and 100 API requests/hour. Pro: $19/month ($15/month billed yearly) with 10,000 API requests/hour, REST API access, cloud history, and up to 5 API keys. Team: $49/month ($39/month billed yearly) with 50

See AIQualityHQ's full pricing (opens in a new tab)

Questions and answers

What tools are included in AIQualityHQ?

AIQualityHQ provides eleven browser-native tools across five domains: Prompt Quality & Linting (Prompt Linter), Prompt Security & Red-Teaming (Injection Scanner, Jailbreak Detector), Token & Cost Intelligence (Token Analyzer, Token Waste Analyzer, Tokenizer Comparison, Context Window Calculator, Length Optimizer), Prompt Engineering & Synthesis (Prompt Rewriter, System Prompt Generator), and AI Visibility (AI Audit Console).

Is my prompt data private and secure?

Browser-native analysis tools run locally in your browser using client-side JavaScript and WebAssembly, so your prompt text does not leave your machine. AI-powered tools like Prompt Rewriter and AI Audit communicate with your configured AI provider and are clearly labeled.

How does AIQualityHQ differ from asking an LLM to evaluate my prompt?

AIQualityHQ uses deterministic static analysis rules, subword BPE tokenization, and heuristic security scanners to produce instant, reproducible diagnostic scores in your browser without model hallucinations, rate limits, or API token costs for evaluation.

Can AIQualityHQ protect against prompt injection and jailbreaks?

Yes. The Prompt Injection Security Scanner and AI Jailbreak Detector evaluate inputs against known attack vectors including direct overrides, RAG context poisoning, DAN personas, role-play bypass, and system prompt extraction, aligned with OWASP LLM-01.

How does the Token Intelligence suite help reduce API costs?

The Token Intelligence tools calculate exact BPE token counts, identify conversational fluff and redundant formatting, compare token compression across frontier model tokenizers, and monitor context window utilization to prevent context overflow before sending requests to paid LLM endpoints.

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