AI Token Calc by Libor Benes

AI Token Calc is a Firefox sidebar extension that provides real-time token estimation for AI prompts across multiple model families - completely offline and privacy-first.

Critical Distinction: This tool estimates tokens using character-to-token ratio approximations. Results are heuristic indicators (±20% accuracy) for planning purposes, not exact counts. Exact counts are provided by official tokenizers.

Purpose:
Optimize AI prompt usage by estimating token consumption before submission:
• Estimate tokens for OpenAI (GPT), Anthropic (Claude), Google (Gemini).
• Track characters, words, and lines in real-time.
• Manage context window limits and API costs.
• Copy formatted statistics for documentation.
• Plan complex prompts within token budgets.

Designed and Built for:
• AI users managing token budgets across platforms.
• Developers optimizing prompts for cost efficiency.
• Content creators drafting long-form AI instructions.
• Researchers tracking prompt complexity.
• Anyone concerned about context limits in AI interactions.

Privacy-First Design:
• 100% offline processing.
• No data collection or transmission.
• No tracking or telemetry.
• Deterministic calculations.
• Session persistence using local storage only.
• Unlike cloud-based tools, it keeps your prompts completely private while providing instant token estimates.

AI Token Calc as Part of a AI Analysis Toolkit:
The Toolkit is designed for systematic analysis and optimization of AI communication. Together with its companion tools, it enables end-to-end management of human-AI interaction.

The Complete AI Communication Workflow:
• AI Prompt Linter → Analyzes prompt structure & clarity.
Purpose: Optimize how humans write instructions to AI systems.
Focus: Prompt engineering, clarity checking, instructional quality.

• AI Intent Indicator → Analyzes directive patterns in prompts.
Purpose: Understand instruction types given to AI.
Focus: Directive strength, compliance review, security analysis.
Key distinction: Highlights indicators, does NOT infer intent.

• AI Output Indicator → Analyzes governance language in AI responses.
Purpose: Assess how AI communicates risks, policies, compliance.
Focus: Governance awareness, risk communication, policy alignment.
Key distinction: Highlights indicators, does NOT verify compliance.

• AI PII Scanner → Detects personal data in text.
Purpose: Prevent accidental privacy leaks before AI submission.
Focus: PII detection (emails, phones, SSNs, addresses).
Key distinction: Pattern-based detection, not comprehensive.

• AI Token Calc → Estimates token usage for AI models.
Purpose: Optimize prompts within context and cost limits.
Focus: Token budgeting, multi-model comparison, cost estimation.
Key distinction: Approximate estimates, not exact tokenization.

Why Five Specialized Tools:
Each tool serves a distinct professional need in the AI communication lifecycle:
• Before writing: Use AI Prompt Linter to understand effective structure.
• While writing: Use AI Token Calc to manage prompt length and costs.
• Before submission: Use AI PII Scanner to check for sensitive data.
• During review: Use AI Intent Indicator to analyze directive patterns.
• After response: Use AI Output Indicator to review governance communication.

Practical Workflow Example: Cost-Conscious AI Development.
A development team optimizing AI integration:
• First, draft the prompt with AI Prompt Linter:
• Ensure clarity, structure, and effective instruction design.
• Then, check token budget with AI Token Calc:
• "This prompt is 450 tokens for GPT-4 - within our 500 token limit."
• Next, scan for sensitive data with AI PII Scanner:
• Verify no customer emails or internal IPs in example code.
• Analyze directive strength with AI Intent Indicator:
• Review if instructions are appropriately strong/permissive.
• Finally, review AI responses with AI Output Indicator:
• Verify AI acknowledges constraints and communicates risks properly.

Shared Design Philosophy:
All five tools share the same core principles:
• 100% offline operation: No data leaves your browser.
• Deterministic processing: Same input → same output.
• Transparent methods: All calculations explicitly defined.
• Professional focus: Designed for critical workflows.
• Privacy-first: Built for sensitive organizational environments.

Choosing the Right Tool:
• For prompt optimization: Start with AI Prompt Linter, monitor tokens with AI Token Calc.
• For privacy compliance: Always use AI PII Scanner before AI submission.
• For governance teams: Use AI Intent Indicator for prompts, AI Output Indicator for responses.
• For cost management: Focus on AI Token Calc to optimize token usage across models.
• For security review: Combine AI PII Scanner and AI Intent Indicator.

This toolkit enables organizations to systematically write, review, optimize, and govern their AI communications with professional-grade tools that respect privacy and provide transparent, reproducible analysis.

Technical Features:
• Real-time token estimation as you type.
• Multi-model comparison (GPT, Claude, Gemini).
• Character, word, and line counting.
• Session persistence (auto-saves between sessions).
• Copy formatted statistics to clipboard.
• 100,000 character capacity.
• Manifest v3 compliant.
• Zero external dependencies.
• Total size: 35 KB.

Token Estimation Method:
Uses character-to-token ratios based on observed averages:
• OpenAI (GPT): ~4.0 characters per token.
• Anthropic (Claude): ~4.2 characters per token.
• Google (Gemini): ~4.5 characters per token.

Caveats:
• Estimates vary ±20% from actual token counts.
• Based on English text patterns (other languages may differ).
• Does not use official tokenizers (for privacy/offline operation).
• Does not account for special tokens or model-specific formatting.
• Best used for planning, not precise billing calculations.

This extension is ideal for anyone working with AI systems who needs quick, private token estimates without sending data to external services. Perfect for prompt engineering, cost optimization, and context management.