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OpenAI API Token Tracker – Stop Overpaying for Tokens

Hacker News

OpenAI API Token Tracker – Stop Overpaying for Tokens

Hey HN, I recently encountered an issue with OpenAI's API where my free credits were still available, but my credit card got charged multiple times. OpenAI support has been slow to respond, so I decided to build a simple CLI tool to track token usage and prevent unexpected charges. Features: - Command-line interface (CLI) - Real-time token usage tracking - Multi-language support (English, Japanese, Traditional Chinese) - Transparent logging for cost management GitHub Repository: [ https://github.com/limonene213u/openai-token-tracker ]( https://github.com/limonene213u/openai-token-tracker ) Would love to hear your feedback!

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
77%77% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: openai, open · Missing: mac, agents, macos
61%61% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal
52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
44%44% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: interface · Missing: plus, platform, intuitive
35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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