RT

RTK – Simple CLI to reduce token usage in your LLM prompts

Hacker News

RTK – Simple CLI to reduce token usage in your LLM prompts

Hi, I developed and use an IA tool to save $$$ . https://github.com/pszymkowiak/rtk Save your token on any IA code solution: rtk gain from a session: RTK Token Savings ════════════════════════════════════════ Total commands: 650 Input tokens: 3.9M Output tokens: 204.4K Tokens saved: 3.7M (96.2%) By Command: ──────────────────────────────────────── Command Count Saved Avg% rtk find 38 2.1M 86.2% rtk git status 93 1.4M 85.4% rtk grep 67 84.5K 50.3% rtk read 63 49.9K 30.7% rtk ls 121 14.5K 52.9% rtk git push 138 9.4K 91.3% rtk env 28 8.4K 98.4% rtk run-test 9 6.4K 87.0% rtk summary 13 5.1K 70.3% rtk kubectl svc 9 3.0K 95.3% Free to Use ! Estimations: Tier Quota Brut Équivalent RTK Pro ($20) 6.0M tokens ~24M tokens Max 5x ($100) 30.0M tokens ~120M tokens Max 20x ($200) 120.0M tokens ~480M tokens

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Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
47%47% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: code · Missing: mac, agents, macos
46%46% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
34%34% 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
26%26% 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
5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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