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AIQualityHQ LogoAIQualityHQ
AI Quality Assurance • Prompt Security • Token Intelligence

Automated QA & Security Guardrails for Prompts and AI Agents

Live Prompt Quality Checker
100/ 100
Quality prompt

This prompt has a strong structure. Ship it to any model.

Prompt Structure
100
Memory & State
0
Context Grounding
75
Trust & Accuracy
95
PII & Privacy
100
Security & Safety
0

All checks passed. Zero structural, privacy, or security issues detected.

Developers and AI teams need to catch prompt defects, red-team injection vectors, and optimize token costs before shipping to users. AIQualityHQ provides deterministic quality linting, adversarial security scanners, and subword token intelligence today — with multi-model testing workflows as the platform evolves.

Built for AI developers, prompt engineers, and AppSec teams — validating output contracts, enforcing role boundaries, red-teaming adversarial inputs, and eliminating token bloat.

Need to measure token bloat or model headroom?Analyze AI token usage

38 Rules

Deterministic prompt linter

15 Detectors

OWASP LLM-01 security checks

30+ Models

Context & token intelligence registry

Browser-Native

Local-first, reproducible & fast

Recognition

Ranked by product-hunting communities for speed, privacy & depth.

Top 2Smol Startup — Daily Winner
6 DimensionsDeterministic rule engine
< 10msBrowser-native execution

AIQualityHQ is independently listed across LaunchTry, Shipstry, Launch List, Verified Tools, IndieHunt, Toolfio and EarlyHunt — no artificially inflated ratings or reviews.

Core Flagships

AI Quality Engineering Tools for Every Stage of the Prompt Lifecycle

From initial prompt design to adversarial defense, token optimization, and automated refactoring — purpose-built browser tools that help teams Check → Secure → Fix → Optimize → Audit.

Core Entry
1. Lint & Verify

Prompt Linter & Contract Checker

Evaluate prompt structure, constraints, clarity, and output schemas against 38 deterministic rules running locally in your browser.

38 Rules • 6 DimensionsOpen Linter
OWASP LLM-01
2. Red-Team & Secure

Prompt Injection Security Scanner

Red-team prompts and RAG contexts against 15 deterministic detector modules covering direct hijacking, exfiltration, and context poisoning.

15 Threat DetectorsOpen Scanner
AI Compiler
3. Refactor & Fix

Prompt Rewriter & Target Compiler

Automated prompt refactoring for detected defects. Resolves constraint conflicts, adds delimiters, and provides side-by-side Git visual diffs.

Visual Diff • Auto-FixOpen Rewriter
BPE Precision
4. Token Intelligence

AI Token Analyzer

Decompose prompts into architectural layers (System, User, Context, Tools) with exact subword BPE precision and multi-model cost tables.

o200k_base • SubwordsAnalyze Tokens
Product Architecture

The AIQualityHQ Suite by Product Domain

Eleven browser-native applications organized across five core domains. Deterministic tools run locally in your browser with zero network calls; AI-assisted features are clearly labeled.

Domain 1Deterministic

Prompt Quality & Linting

Static analysis for prompt templates, system instructions, and RAG conditioning. Catches conflicting constraints, role ambiguity, missing output delimiters, and formatting issues before code execution.

Domain 2OWASP LLM-01

Prompt Security & Guardrails

Pre-deployment red-teaming and exploit detection. Evaluates inputs against direct prompt overrides, RAG context poisoning, behavioral jailbreaks, and system prompt exfiltration vectors.

Domain 35 Dedicated Tools

Token & Cost Intelligence

Comprehensive token counting, subword fragmentation, cost estimation, and context capacity engineering. Built with exact BPE tokenizer logic and calibrated cross-provider models running directly in your browser with zero cloud storage.

Domain 4Synthesis & Fix

Prompt Engineering & Synthesis

Active instruction authoring and automated defect fixing. Synthesize production-ready system prompts with role parameters or compile defective drafts into optimized model-specific prompts.

Domain 5GEO & AEO

AI Visibility & LLM Auditing

Diagnose domain discoverability and brand grounding across frontier AI engines. Validate your llms.txt file and evaluate generative engine optimization (GEO) metrics.

Financial & Performance Engineering

Eliminate Token Bloat & Optimize Model Context Windows

Every uncompressed prompt burns context headroom and drives unnecessary API expenditure. Follow the complete token engineering cycle: Measure → Detect Waste → Compare Tokenizers → Verify Headroom → Optimize.

ROI & Savings Calculator

Calculate Your Token & API Cost Savings

See how much static prompt pre-filtering & token optimization saves your team vs cloud evals.

Browser-Native Engine • 0 Cloud API Fees
50,000 calls/mo
5k/mo100k/mo500k/mo
800 tokens (~600 words)
100 tokens1,500 tokens3,000 tokens
Estimated Annual Savings
$216.00/ year
Monthly Token Savings:$18.00/mo
Tokens Saved From Bloat:7200k tokens/mo
Evaluation Latency:<8ms (vs 350ms cloud)

Estimates assume an average 18% token-bloat reduction from optimization and failed-injection filtering, and a 350ms cloud evaluation latency. Actual results vary by prompt and provider.

Deconstruct BPE Tokens

Break down prompts into system, context, user, and schema layers with subword precision.

Open Token Analyzer →

Detect Conversational Fluff

Automatically identify polite filler and redundant formatting that waste token bandwidth.

Open Waste Analyzer →

Context Window Headroom

Monitor utilization gauges and avoid "Lost in the Middle" attention degradation risks.

Open Calculator →

Cross-Model Tokenizer BPE

Compare token efficiency and subword chunking across OpenAI, Anthropic, Google & Meta.

Open Comparison →
OWASP LLM-01 Top 10 Red-Teaming

Red-Team Prompts Against Injections & Adversarial Jailbreaks

Adversarial inputs compromise AI behavior in two distinct ways: single-turn instruction hijacking (prompt injections) and persona modulation (jailbreaks). AIQualityHQ provides dedicated scanners for both threat vectors:

  • Prompt Injection Vectors: Malicious user input or tainted RAG documents overriding system constraints or extracting sensitive system instructions.
  • Behavioral Jailbreaks: DAN personas, hypothetical scenarios, and multi-turn roleplay tactics designed to bypass safety filters.

Prompt Injection Scanner

Evaluates prompts against 15 deterministic detection modules. Scans for direct override syntax, typoglycemia, and exfiltration probes.

Open Injection Scanner →

AI Jailbreak Detector

Tests guardrail resilience against adversarial persona modulation, developer mode exploits, and simulated framing attacks.

Open Jailbreak Detector →
How It Compares

Deterministic. Reproducible. Private. By Design.

Most prompt evaluation tools are just another LLM call — spending tokens to grade tokens with non-reproducible outputs. AIQualityHQ provides a deterministic static analysis and BPE token engine running directly in your browser.

CapabilityAIQualityHQ Local EngineAsking an LLM to GradeGeneric Cloud Tools
Deterministic & reproducible scores varies run to run LLM-backed
Local browser execution (prompt text remains on device) sent to provider cloud processing
Instant evaluation (< 10ms, zero rate limits) seconds + queues network latency
Free browser tools without required API keys API token cost subscriptions
Exact subword BPE token & context analytics rough estimate± basic counter
Prompt injection & jailbreak security red-teaming rarely included

Local analysis tools (Prompt Linter, Token Analyzer, Context Calculator, Injection Scanner) execute fully locally. AI-assisted features (Prompt Rewriter, AI Audit) connect to external providers and are clearly demarcated.

Evaluation Criteria

Six Core Dimensions of Prompt Quality

Every prompt evaluated in AIQualityHQ is graded against six deterministic dimensions to isolate vulnerabilities and ensure output precision.

Structural Integrity

1. Prompt Structure

Validates role assignments, task demarcation, formatting delimiters, explicit output specifications, and structural clarity.

Read Structure Guide →
Contextual State

2. Memory & State

Evaluates how effectively conversational history and variable context are referenced without overloading token windows.

Calculate Context Headroom →
RAG Grounding

3. Context Grounding

Measures document retrieval parameters, citation requirements, and grounding constraints to prevent out-of-bounds answers.

Read Grounding Guide →
Hallucination Risk

4. Trust & Accuracy

Flags ambiguous instructions, unverified assumptions, and factual grounding gaps that contribute to hallucinated LLM responses.

Read Trust & Accuracy Guide →
Data Protection

5. PII & Privacy

Detects exposed email addresses, API tokens, phone numbers, and raw user variables requiring sanitization.

View Privacy Policy →
Red-Teaming

6. Security & Safety

Scans for prompt injection attacks, DAN jailbreak overrides, missing system instruction locks, and output boundary violations.

Read Security Mitigation Guide →
Developer Workflow

CHECK → SECURE → FIX → OPTIMIZE → TEST

Deterministic prompt quality checks, adversarial security red-teaming, and token intelligence engineered for pre-production CI/CD pipelines.

1
CHECK

Prompt Linting

Validate constraints and schema contracts against 38 deterministic rules.

Open Linter →
2
SECURE

Security Scan

Red-team prompt text and RAG context against 15 injection and jailbreak vectors.

Open Scanner →
3
FIX

Refactor Prompt

Remediate linter violations and compile model-specific candidate instructions.

Open Rewriter →
4
OPTIMIZE

Token Efficiency

Eliminate conversational bloat and benchmark cross-model tokenizer costs.

Analyze Tokens →
5
TEST

Automate & Eval

Export Promptfoo CLI configurations for automated multi-model regression runs.

View Docs →
Technical Research

Engineering Guides & AI Quality Research

In-depth technical architecture blueprints, testing methodologies, and governance frameworks from the AIQualityHQ engineering team.

Explore all 26 AI engineering guides
Cornerstone Framework

Modern AI Software Testing Framework

The authoritative 3,100-word cornerstone guide exploring the two dimensions of modern AI QA and the four pillars of AI-driven test automation.

Read Full Guide
Agent Governance

Autonomous AI Agent Governance

Defense-in-depth security architectures, human-in-the-loop gates, and deterministic execution boundaries for enterprise autonomous agents.

Read Governance Blueprint
AI Visibility

Generative Engine Optimization (GEO)

How to configure llms.txt, structure entity documentation, and maximize brand citations in ChatGPT, Perplexity, and Claude.

Read Visibility Guide
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Frequently Asked Questions

Common questions about AIQualityHQ. Visit our full FAQ page for detailed technical guides.

What tools are included in the AIQualityHQ suite?
AIQualityHQ provides a comprehensive AI quality engineering platform organized into five core domains: Prompt Quality & Linting (Prompt Linter, Quality Report Viewer), 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 (Prompt Linter, Token Analyzer, Token Waste Analyzer, Context Window Calculator, Tokenizer Comparison, Optimizer, Injection Scanner, Jailbreak Detector, System Prompt Generator) run locally in your browser using client-side JavaScript and WebAssembly — your prompt text does not leave your machine. AI-powered tools (Prompt Rewriter, AI Audit) communicate with your configured or backend AI provider and are clearly labeled.
How is AIQualityHQ different from asking an LLM to review my prompt?
AIQualityHQ relies on deterministic static analysis rules, subword BPE tokenization, and heuristic security scanners, producing instant, 100% reproducible diagnostic scores in your browser without model hallucinations, API costs, or data privacy risks.
Can AIQualityHQ protect against prompt injection and jailbreaks?
Yes. The Prompt Injection Security Scanner and AI Jailbreak Detector evaluate inputs against 15 known threat vectors (direct overrides, RAG context poisoning, DAN personas, role-play bypass, and system prompt extraction) aligned with OWASP LLM-01 to identify vulnerabilities before shipping to production.
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 and attention degradation before sending requests to paid LLM endpoints.

Ready to harden your AI prompts?

Catch prompt quality problems, red-team injection vectors, and eliminate token bloat with deterministic QA and security guardrails.

Browser-native tools run locally in your browser — no mandatory signup or API key required. AI-powered tools are clearly labeled.