AIQualityHQ is a comprehensive platform designed for automated quality assurance, security guardrails, and token intelligence for prompts and AI agents. It empowers developers, prompt engineers, and AppSec teams to detect prompt defects, red-team injection vectors, and optimize token costs before deploying to users.

Key Features:

Deterministic Prompt Linting: Static analysis with 38 rules for structure, constraints, and output schemas.
OWASP LLM-01 Security Scanning: 15 detector modules for prompt injection, RAG context poisoning, and jailbreak detection.
AI Token Intelligence: Exact BPE token counting, waste analysis, cross-model comparison, and context window calculation.
Automated Prompt Refactoring: Rewrites and fixes detected defects, resolving conflicts and adding delimiters.
Browser-Native Execution: Tools run locally in your browser for privacy, speed, and reproducibility.
Cost Optimization: Reduces token bloat and estimates API expenditure savings.

Use Cases:
AIQualityHQ is invaluable for ensuring the robustness and security of AI applications throughout their lifecycle. Developers can use the Prompt Linter to validate initial prompt designs, ensuring structural integrity and adherence to output contracts. Before deployment, AppSec teams can leverage the Prompt Injection Security Scanner and Jailbreak Detector to red-team inputs, identifying and mitigating adversarial threats like direct overrides, data exfiltration, and persona bypasses.

Furthermore, the platform's Token Intelligence suite helps optimize operational costs and performance. Engineers can analyze token usage, detect conversational fluff, compare tokenizer efficiency across models (OpenAI, Claude, Gemini, Llama), and calculate context window headroom to prevent "Lost in the Middle" attention degradation. This comprehensive approach ensures prompts are not only secure and high-quality but also cost-efficient.

Pricing Information:
AIQualityHQ operates on a freemium model, offering many browser-native tools for free without requiring mandatory sign-up or API keys. AI-powered features are clearly labeled and may connect to external providers.

User Experience and Support:
The platform emphasizes a browser-native, local-first approach, ensuring instant evaluation (under 10ms) and reproducible results. Its intuitive interface is designed for AI developers and prompt engineers. Extensive documentation, articles, and a detailed FAQ page are available to guide users through its features and best practices.

Technical Details:
The core deterministic tools of AIQualityHQ are built using client-side JavaScript and WebAssembly, allowing them to run entirely within the user's browser. This architecture ensures prompt text remains on the device, guaranteeing privacy and eliminating network latency for static analysis and BPE token engine operations.

Pros and Cons:

Pros:
- Deterministic and reproducible quality scores.
- Enhanced privacy with local browser execution.
- Instant evaluation and zero rate limits.
- Free access to many powerful browser tools.
- Exact subword BPE token and context analytics.
- Comprehensive prompt injection and jailbreak security red-teaming.
Cons:
- AI-assisted features may require external API calls.
- No explicit cons mentioned in the provided text, indicating a strong focus on benefits.

Conclusion:
AIQualityHQ provides an essential toolkit for modern AI development, offering unparalleled prompt quality assurance, robust security guardrails, and intelligent token optimization. Its browser-native, deterministic approach ensures privacy, speed, and accuracy, making it a vital asset for any team building with large language models. Explore AIQualityHQ today to harden your AI prompts and streamline your development workflow.

AIQualityHQ

AIQualityHQ

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