Загрузка видео...

Не удалось загрузить видео

Возникла проблема при загрузке этого видео. Это может быть связано с временными проблемами сети или видео может быть недоступно.

На главную

Meet Optimus Prime Agent. Transform between GUI and terminal instantly. Same conversation, zero context lost. Track costs, split views, and save your favorite commands. Prime Agent, roll out.

super.engineering

6,114 subscribers

17,012 просмотров • 14 дней назад •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

Комментарии: 18

Фото профиля kevin

kevin13 дней назад

this is so sick

Фото профиля Fitz

Fitz14 дней назад

That’s hot

Фото профиля Daniel Zarifpour

Daniel Zarifpour14 дней назад

cc: @PrimeIntellect

Фото профиля Seth Karten

Seth Karten13 дней назад

Wow prime agent with a gui is nice. How does it handle subagents and swarm view?

Фото профиля KC

KC14 дней назад

It's probably inadvertent, but quoting Optimus Prime to sell the agent one day after the voice of Optimus Prime dies. It's just uncomfortable for me.

Фото профиля Monty

Monty14 дней назад

sweet

Фото профиля moku

moku14 дней назад

Please add linux or windows support 🥺🥺

Фото профиля Ganidhu

Ganidhu14 дней назад

super cool concept!

Фото профиля capad / aadarsh

capad / aadarsh14 дней назад

Optimus Prime is such a sickk and perfect name for it wtf..

Фото профиля Brook Tang

Brook Tang14 дней назад

another beautiful terminal after otty.

Фото профиля mqotip

mqotip13 дней назад

Wait… same conversation, zero context lost when switching GUI vs terminal? How is that even possible 👀

Фото профиля Monty

Monty14 дней назад

can't change the model in chat mode, uses default from CLI, and no fast toggle in chat mode.

Фото профиля Ymir

Ymir14 дней назад

Does this support running the agents on a remote machine with port forwarding to yours over tailscale?

Фото профиля Guaryonline

Guaryonline11 дней назад

where can i get this

Фото профиля Kaloyan Stoyanov

Kaloyan Stoyanov14 дней назад

Hey, so i love how this looks and how you took Arc/Dia sidebars but the problem is that for soem reason on my mac its not 120fps but instead 60 so everything looks laggy and so i wanted to ask you if there's is some kind of a fix for that?

Фото профиля pozitiv4ik

pozitiv4ik14 дней назад

bro, I really like your project, but add the ability to make a chat system instead of a worktree. sometimes you dont need to create one

Фото профиля elliott

elliott14 дней назад

But can I has?

Фото профиля Danny

Danny14 дней назад

but can it run doom?

Похожие видео

Oneshot Bloomberg-style stock market board by Kimi Agent. Stocks, price action, and real-time context — all at your fingertip via terminal commands. All you need is a prompt; Kimi handles the rest.

Oneshot Bloomberg-style stock market board by Kimi Agent. Stocks, price action, and real-time context — all at your fingertip via terminal commands. All you need is a prompt; Kimi handles the rest.

Kimi Product

86,152 просмотров • 7 месяцев назад

We built MiniMax a CLI coding agent like Claude Code, powered by MiniMax M3. It can: → Read files → Write code → Run shell commands autonomously → Understand large codebases with long-context reasoning → Handle real multi-file engineering tasks → Work entirely inside your terminal And it's fully hackable. Swap prompts. Add tools. Customize workflows. Make it your own. No GUI. Just code. Built for developers who live in the terminal.

We built MiniMax a CLI coding agent like Claude Code, powered by MiniMax M3. It can: → Read files → Write code → Run shell commands autonomously → Understand large codebases with long-context reasoning → Handle real multi-file engineering tasks → Work entirely inside your terminal And it's fully hackable. Swap prompts. Add tools. Customize workflows. Make it your own. No GUI. Just code. Built for developers who live in the terminal.

Darshal Jaitwar

18,861 просмотров • 2 месяцев назад

Introducing Design Mode for Cursor! 🧑‍🎨🤖 Vibe code and vibe design in one place, stay in the flow. Uses the same existing AI agent that's in your favorite coding tool, same context, intertwined.

Introducing Design Mode for Cursor! 🧑‍🎨🤖 Vibe code and vibe design in one place, stay in the flow. Uses the same existing AI agent that's in your favorite coding tool, same context, intertwined.

Tom Krcha

859,304 просмотров • 1 год назад

Custom Statusline in Antigravity CLI🚦⚙️ Track agent state, context window, subagents all right from the footer of your terminal. Been using this one created by Jochen Kirstätter (JoKi) and I'm obsessed. Will share link to copy it below 👇

Custom Statusline in Antigravity CLI🚦⚙️ Track agent state, context window, subagents all right from the footer of your terminal. Been using this one created by Jochen Kirstätter (JoKi) and I'm obsessed. Will share link to copy it below 👇

Jack Wotherspoon

26,224 просмотров • 2 месяцев назад

just shipped thred!! context that carries your work forward. Claude → Codex → Cursor → whatever comes next. thred gives every agent one shared memory for decisions, revisions, evidence, and unfinished work — so the next agent starts where the last one stopped. built on MCP. powered by temporal memory with HydraDB. no more re-explaining the codebase. no more lost decisions between sessions. just save → switch → resume. built for Hack Hydra | Memory + Context Retrieval.

just shipped thred!! context that carries your work forward. Claude → Codex → Cursor → whatever comes next. thred gives every agent one shared memory for decisions, revisions, evidence, and unfinished work — so the next agent starts where the last one stopped. built on MCP. powered by temporal memory with HydraDB. no more re-explaining the codebase. no more lost decisions between sessions. just save → switch → resume. built for Hack Hydra | Memory + Context Retrieval.

nikhil · sys/quests

20,771 просмотров • 25 дней назад

Your engineering team is about to snap. And your AI coding agent is making it worse. Introducing CodeRabbit Agent for Slack 🎉 A second brain for engineering teams. Because your tribal knowledge lives in Slack threads nobody can find. At CodeRabbit, we review millions of PRs every week and know how ace engineering teams operate on the planet. The same three things slow every team we see: - Context and decisions that live elsewhere. - Lack of a team-level durable knowledge base - And a trust layer that gives a safety net to your teams Built for Agentic SDLC workflows, CodeRabbit Agent for Slack solves all three problems in one shot while enabling teams to collaborate in real-time with the Agent. CodeRabbit Agent is Slack-native and builds your team’s operating context from every thread, every decision, every conversation your team has ever had. Make your team’s context compound!

Your engineering team is about to snap. And your AI coding agent is making it worse. Introducing CodeRabbit Agent for Slack 🎉 A second brain for engineering teams. Because your tribal knowledge lives in Slack threads nobody can find. At CodeRabbit, we review millions of PRs every week and know how ace engineering teams operate on the planet. The same three things slow every team we see: - Context and decisions that live elsewhere. - Lack of a team-level durable knowledge base - And a trust layer that gives a safety net to your teams Built for Agentic SDLC workflows, CodeRabbit Agent for Slack solves all three problems in one shot while enabling teams to collaborate in real-time with the Agent. CodeRabbit Agent is Slack-native and builds your team’s operating context from every thread, every decision, every conversation your team has ever had. Make your team’s context compound!

Harjot Gill

4,777,289 просмотров • 4 месяцев назад

Autobots, roll out! Defend the Earth against the Decepticons in the new Transformers DLC! Play as Optimus Prime, Bumblebee and more as you battle familiar foes like Megatron and Starscream. While you’re at it, grab your free Transformers Hoodie in the Dressing Room!

Autobots, roll out! Defend the Earth against the Decepticons in the new Transformers DLC! Play as Optimus Prime, Bumblebee and more as you battle familiar foes like Megatron and Starscream. While you’re at it, grab your free Transformers Hoodie in the Dressing Room!

Minecraft

345,355 просмотров • 1 год назад

Bloome is actually smart for coding workflows i added Claude Code, Codex, DeepSeek and a Project Lead agent into one group chat each agent independently built their own version one challenged the logic, one defended, one fixed missing details and the final website stayed inside the same thread no copy paste between agents no lost context just one group chat for getting work done Bloome

Bloome is actually smart for coding workflows i added Claude Code, Codex, DeepSeek and a Project Lead agent into one group chat each agent independently built their own version one challenged the logic, one defended, one fixed missing details and the final website stayed inside the same thread no copy paste between agents no lost context just one group chat for getting work done Bloome

Chetaslua

48,810 просмотров • 2 месяцев назад

THIS GUY BUILT A COMMAND CENTER FOR MANAGING AI AGENT TEAMS he was running 20+ agents through openclaw. all from terminal tabs and Discord. 12 tabs open. still losing track of who's doing what. which cron failed. so he built a dashboard that gives you one place to see everything: > org map showing the full agent hierarchy, who reports to who and what tools each agent has > chat with any agent through a real UI instead of bouncing between terminals > kanban board for tracking tasks across all agents > cron monitor with pipeline visualizations so you can see which jobs are failing > memory browser to read through all agent knowledge files in one place you can even point it at your openclaw workspace and it auto-discovers every agent from their config files. zero setup. AND ITS OPEN SOURCE TOO.

THIS GUY BUILT A COMMAND CENTER FOR MANAGING AI AGENT TEAMS he was running 20+ agents through openclaw. all from terminal tabs and Discord. 12 tabs open. still losing track of who's doing what. which cron failed. so he built a dashboard that gives you one place to see everything: > org map showing the full agent hierarchy, who reports to who and what tools each agent has > chat with any agent through a real UI instead of bouncing between terminals > kanban board for tracking tasks across all agents > cron monitor with pipeline visualizations so you can see which jobs are failing > memory browser to read through all agent knowledge files in one place you can even point it at your openclaw workspace and it auto-discovers every agent from their config files. zero setup. AND ITS OPEN SOURCE TOO.

Om Patel

46,780 просмотров • 5 месяцев назад

Meet Hyperlink, the first AI super assistant that lives inside your computer. Your computer stores all your files and personal context. Hyperlink deeply understands them and gives cited answers instantly — like Perplexity for your local files. It turns your computer into a true AI OS, with 100% private on-device AI agent. Welcome to the new interface for personal intelligence.

Meet Hyperlink, the first AI super assistant that lives inside your computer. Your computer stores all your files and personal context. Hyperlink deeply understands them and gives cited answers instantly — like Perplexity for your local files. It turns your computer into a true AI OS, with 100% private on-device AI agent. Welcome to the new interface for personal intelligence.

NEXA AI

2,136,912 просмотров • 10 месяцев назад

$HERMES AGENT RUNS MONITORING, RESEARCH, LEAD DETECTION, AND COMPETITIVE ANALYSIS ON AUTOPILOT. AND KNOWS WHEN NOT TO SPEND YOUR TOKENS. the biggest unlock most people skip: Hermes cron jobs can decide ON THEIR OWN whether the LLM should wake up. WAKE AGENT — THE $0 GATE every cron job can run a Python script first. the script checks: did anything actually change? nothing changed: → script outputs {"wakeAgent": false} → LLM stays asleep → zero tokens spent something changed: → script outputs {"wakeAgent": true} → agent wakes up and handles it three gate patterns from official docs: → file-change: compare file mtime to last run. no change? sleep. → external-flag: another process drops a ready file. no flag? sleep. → HTTP-check: ping a URL, diff the response. same as last time? sleep. real example: monitor AWS costs every hour. script pulls current spend from AWS API. no spike? agent sleeps. zero cost. costs jump 40%? agent wakes, reports to Slack, takes action through Stripe MCP. you run 20 monitoring jobs a day. 18 of them find nothing. you pay for 2. NO AGENT — PURE SCRIPT, ZERO LLM some jobs don't need reasoning at all. TLS checks. uptime pings. disk alerts. heartbeats. hermes cron edit --no-agent --script check_health.py script runs. stdout goes straight to Telegram, Discord, or Slack. no LLM involved. flip any job between modes: hermes cron edit --agent # add LLM hermes cron edit --no-agent # remove LLM free monitoring that lives inside the same ecosystem as your agent. 4 MORE USE CASES THIS UNLOCKS: COMPETITIVE ANALYSIS weekly cron with script that diffs competitor pages. agent only analyzes actual changes. updates your tracking file and PRD skill automatically. PRD AS A SKILL save product requirements as a skill, not a document. skills load on demand into fresh context. documents drift. skills stay sharp. CONTENT REPURPOSING hand a video script to the agent. it drafts X and LinkedIn posts in your voice. writes to a review folder. you approve via Telegram. LEAD DETECTION webhook monitors inbox. agent spots potential leads. drafts responses using your business context. schedules meetings from your calendar. the pattern across all of these: scripts handle the mechanical work for free. the agent only spends tokens on reasoning that requires judgment. comment CRON and I'll send you 5 ready-to-paste cron configs with wakeAgent and no_agent patterns. full Hermes SOUL.MD guide 👇$

HERMES AGENT RUNS MONITORING, RESEARCH, LEAD DETECTION, AND COMPETITIVE ANALYSIS ON AUTOPILOT. AND KNOWS WHEN NOT TO SPEND YOUR TOKENS. the biggest unlock most people skip: Hermes cron jobs can decide ON THEIR OWN whether the LLM should wake up. WAKE AGENT — THE $0 GATE every cron job can run a Python script first. the script checks: did anything actually change? nothing changed: → script outputs {"wakeAgent": false} → LLM stays asleep → zero tokens spent something changed: → script outputs {"wakeAgent": true} → agent wakes up and handles it three gate patterns from official docs: → file-change: compare file mtime to last run. no change? sleep. → external-flag: another process drops a ready file. no flag? sleep. → HTTP-check: ping a URL, diff the response. same as last time? sleep. real example: monitor AWS costs every hour. script pulls current spend from AWS API. no spike? agent sleeps. zero cost. costs jump 40%? agent wakes, reports to Slack, takes action through Stripe MCP. you run 20 monitoring jobs a day. 18 of them find nothing. you pay for 2. NO AGENT — PURE SCRIPT, ZERO LLM some jobs don't need reasoning at all. TLS checks. uptime pings. disk alerts. heartbeats. hermes cron edit --no-agent --script check_health.py script runs. stdout goes straight to Telegram, Discord, or Slack. no LLM involved. flip any job between modes: hermes cron edit --agent # add LLM hermes cron edit --no-agent # remove LLM free monitoring that lives inside the same ecosystem as your agent. 4 MORE USE CASES THIS UNLOCKS: COMPETITIVE ANALYSIS weekly cron with script that diffs competitor pages. agent only analyzes actual changes. updates your tracking file and PRD skill automatically. PRD AS A SKILL save product requirements as a skill, not a document. skills load on demand into fresh context. documents drift. skills stay sharp. CONTENT REPURPOSING hand a video script to the agent. it drafts X and LinkedIn posts in your voice. writes to a review folder. you approve via Telegram. LEAD DETECTION webhook monitors inbox. agent spots potential leads. drafts responses using your business context. schedules meetings from your calendar. the pattern across all of these: scripts handle the mechanical work for free. the agent only spends tokens on reasoning that requires judgment. comment CRON and I'll send you 5 ready-to-paste cron configs with wakeAgent and no_agent patterns. full Hermes SOUL.MD guide 👇

YanXbt

96,056 просмотров • 3 месяцев назад

There's a free 120 billion parameter AI you can run on your own computer. Zero internet. Zero API costs. Zero monthly fees. It's called Nvidia Nemotron 3 Super. And it just changed what solopreneurs can do with AI agents. Here's the setup: → Download Ollama. Copy one command into your terminal. → Connect it to OpenClaw in under 10 minutes. → Your AI agent now runs 24/7 on WhatsApp, Discord, or Telegram. → It answers customers, runs tasks, and manages workflows while you sleep. → 256,000 token context window. It reads entire documents without forgetting. No subscriptions. No cloud. No one else touching your data. A full AI employee stack for $0. Save this. Set it up this weekend.

There's a free 120 billion parameter AI you can run on your own computer. Zero internet. Zero API costs. Zero monthly fees. It's called Nvidia Nemotron 3 Super. And it just changed what solopreneurs can do with AI agents. Here's the setup: → Download Ollama. Copy one command into your terminal. → Connect it to OpenClaw in under 10 minutes. → Your AI agent now runs 24/7 on WhatsApp, Discord, or Telegram. → It answers customers, runs tasks, and manages workflows while you sleep. → 256,000 token context window. It reads entire documents without forgetting. No subscriptions. No cloud. No one else touching your data. A full AI employee stack for $0. Save this. Set it up this weekend.

Julian Goldie SEO

29,325 просмотров • 6 месяцев назад

🥧 Introducing GooeyPi - A GUI for the Pi Family of Agents. Supports: Pi, Oh-My-Pi (OMP), and Prime Agent Very excited to share this with you all. Being into local models, I wanted to have a separate harness for my local models so I don't have to constantly switch configs. And I didn't want to go back to the TUI (nerds). But, I didn't want to miss out on all the features that I know and love. Turns out, I didn't have to. I just needed to build it myself. So I did. Features include: > Fully featured GUI experience > Agentic Browser > Realtime Voice Agent > Voice transcription (local or API) > Computer Use > Automation Desk > Agent to Agent messaging > Ask Question Tool > Git Control > Terminal > Pets > and more I tried to capture all of the most popular features I could in this first pass, but we're only just getting started. Available in BETA on MacOS, Linux, and Windows. I need testers! I have only tested on Mac and Linux. If you want to help me with this project, please reach out. Available:

🥧 Introducing GooeyPi - A GUI for the Pi Family of Agents. Supports: Pi, Oh-My-Pi (OMP), and Prime Agent Very excited to share this with you all. Being into local models, I wanted to have a separate harness for my local models so I don't have to constantly switch configs. And I didn't want to go back to the TUI (nerds). But, I didn't want to miss out on all the features that I know and love. Turns out, I didn't have to. I just needed to build it myself. So I did. Features include: > Fully featured GUI experience > Agentic Browser > Realtime Voice Agent > Voice transcription (local or API) > Computer Use > Automation Desk > Agent to Agent messaging > Ask Question Tool > Git Control > Terminal > Pets > and more I tried to capture all of the most popular features I could in this first pass, but we're only just getting started. Available in BETA on MacOS, Linux, and Windows. I need testers! I have only tested on Mac and Linux. If you want to help me with this project, please reach out. Available:

am.will

145,452 просмотров • 29 дней назад

Cross-context Personal Knowledge Base with Social Graph🧠 Introducing Cross-context Personal Knowledge Base with Social Graph. Your Memory, Across Every Conversation Most AI forgets you the moment a chat ends. Teamily's Personal Knowledge Base remembers — across every group, every agent, and every context. Powered by your social graph, it connects the dots between your work, relationships, and ideas, so your AI always knows who you are, what you care about, and what happened before. No setup. No tagging. Just intelligence that grows with you. 🙌Try the prompt today: “visualize my knowledge base with social graph” #teamily #AI #Agent #KnowledgeBase #Social #SocialGraph

Cross-context Personal Knowledge Base with Social Graph🧠 Introducing Cross-context Personal Knowledge Base with Social Graph. Your Memory, Across Every Conversation Most AI forgets you the moment a chat ends. Teamily's Personal Knowledge Base remembers — across every group, every agent, and every context. Powered by your social graph, it connects the dots between your work, relationships, and ideas, so your AI always knows who you are, what you care about, and what happened before. No setup. No tagging. Just intelligence that grows with you. 🙌Try the prompt today: “visualize my knowledge base with social graph” #teamily #AI #Agent #KnowledgeBase #Social #SocialGraph

Teamily AI

13,287 просмотров • 4 месяцев назад

New course: Spec-Driven Development with Coding Agents, built in partnership with JetBrains, and taught by Paul Everitt | @pauleveritt@fosstodon.org. Vibe coding is fast, but often produces code that doesn't match what you asked for. This short course teaches you spec-driven development: write a detailed spec defining what to build, and work with your coding agent to implement it. Many of the best developers already build this way. A spec lets you control large code changes with a few words, preserve context across agent sessions, and stay in control as your project grows in complexity. Skills you'll gain: - Write a detailed specification to define your mission, tech stack, and roadmap, giving your agent the context it needs from the start - Plan, implement, and validate features in iterative loops using a spec as your agent's guide - Apply the same repeatable workflow to both new and legacy codebases - Package your workflow into a portable agent skill that works across agents and IDEs Join and write specs that keep your coding agent on track!

New course: Spec-Driven Development with Coding Agents, built in partnership with JetBrains, and taught by Paul Everitt | @[email protected]. Vibe coding is fast, but often produces code that doesn't match what you asked for. This short course teaches you spec-driven development: write a detailed spec defining what to build, and work with your coding agent to implement it. Many of the best developers already build this way. A spec lets you control large code changes with a few words, preserve context across agent sessions, and stay in control as your project grows in complexity. Skills you'll gain: - Write a detailed specification to define your mission, tech stack, and roadmap, giving your agent the context it needs from the start - Plan, implement, and validate features in iterative loops using a spec as your agent's guide - Apply the same repeatable workflow to both new and legacy codebases - Package your workflow into a portable agent skill that works across agents and IDEs Join and write specs that keep your coding agent on track!

Andrew Ng

465,101 просмотров • 5 месяцев назад

Here's a little video about how we're thinking about session and tab management in the Superlogical multiplexer and some of the GUI we're experimenting with to make it a productive and intuitive space for your work. We're designing the client from the beginning to handle the modern terminal sprawl: local and remote sessions, long lived processes, agent harnesses, rich TUI apps, ephemeral processes, and everything in between.

Here's a little video about how we're thinking about session and tab management in the Superlogical multiplexer and some of the GUI we're experimenting with to make it a productive and intuitive space for your work. We're designing the client from the beginning to handle the modern terminal sprawl: local and remote sessions, long lived processes, agent harnesses, rich TUI apps, ephemeral processes, and everything in between.

almonk

28,045 просмотров • 1 месяц назад

Anthropic's multi-agent researcher just explained how to actually build a graph of Claude agents: "Multi-agent is where fundamentally you have multiple agents or multiple Claudes working at the same time - one parent agent delegates tasks to five sub-agents that can each then work in parallel." the real architecture: parent agent → delegates to sub-agents (as tools) → sub-agents run in parallel → results roll back up the failure mode nobody talks about: "Overbuilt multi-agent systems spend too much time just talking back and forth with each other and not actually making progress on the main task." sound familiar? that's every bloated human org chart too in this 19-minute conversation, an Anthropic researcher lays out the real framework: parent → sub-agents → tools → context protection = the actual shape of a working agent graph

Anthropic's multi-agent researcher just explained how to actually build a graph of Claude agents: "Multi-agent is where fundamentally you have multiple agents or multiple Claudes working at the same time - one parent agent delegates tasks to five sub-agents that can each then work in parallel." the real architecture: parent agent → delegates to sub-agents (as tools) → sub-agents run in parallel → results roll back up the failure mode nobody talks about: "Overbuilt multi-agent systems spend too much time just talking back and forth with each other and not actually making progress on the main task." sound familiar? that's every bloated human org chart too in this 19-minute conversation, an Anthropic researcher lays out the real framework: parent → sub-agents → tools → context protection = the actual shape of a working agent graph

rewind

27,195 просмотров • 1 месяц назад

This is literally the easiest way to build an AI agent. Zero code. You only need to run a couple of commands. (I've said this before, but Google ADK is my favorite way to build code-first agents.) Here is what you need to do: 1. Open your terminal and create an empty folder 2. Run `uv init` inside the folder (if you don't have uv installed, you are really missing out!) 3. Install the google-adk library using the following command: `uv add google-adk`. 4. At this point, you can use the ask to create your agent with a single command: `uv run adk create --type=config my_agent`. This will ask you a couple of questions, including your GEMINI_API_KEY (you can create one online). 5. The command above will create a my_agent/root_agent.yaml file. Open it and add the following two lines at the end of the file so your agent can use Google to search for stuff: tools: - name: google_search 6. You have everything you need now. Run the adk web interface and start playing with your agent: `uv run adk web` That's it! Literally zero code. The agent works off the YAML configuration file.

This is literally the easiest way to build an AI agent. Zero code. You only need to run a couple of commands. (I've said this before, but Google ADK is my favorite way to build code-first agents.) Here is what you need to do: 1. Open your terminal and create an empty folder 2. Run `uv init` inside the folder (if you don't have uv installed, you are really missing out!) 3. Install the google-adk library using the following command: `uv add google-adk`. 4. At this point, you can use the ask to create your agent with a single command: `uv run adk create --type=config my_agent`. This will ask you a couple of questions, including your GEMINI_API_KEY (you can create one online). 5. The command above will create a my_agent/root_agent.yaml file. Open it and add the following two lines at the end of the file so your agent can use Google to search for stuff: tools: - name: google_search 6. You have everything you need now. Run the adk web interface and start playing with your agent: `uv run adk web` That's it! Literally zero code. The agent works off the YAML configuration file.

Santiago

140,922 просмотров • 9 месяцев назад

10 GitHub repos with ⭐ 450k+ combined stars that stop your agent from wasting tokens 1. caveman 98k⭐ - makes your AI agent talk like a caveman. Same answers, 65% fewer output tokens. 2. rtk 76k⭐ - CLI proxy that filters git/test/docker output before it hits your context. Up to 90% less bash noise. 3. mem0 63k⭐ - memory layer for AI agents. Stops your agent from re-explaining the same context every session. 4. context7 60.7k⭐ - pulls exact, up-to-date docs into context instead of your agent guessing and burning tokens on retries. 5. aider 48k⭐ - builds a map of your repo instead of loading the whole codebase into context. 6. code-review-graph 30k⭐ - graphs your codebase so your agent reads 2-3 files instead of the whole repo. Up to 376x fewer tokens per question. 7. serena 28k⭐ - gives agents symbol-level code access instead of reading full files line by line. 8. repomix 28k⭐ - compresses your entire repo into an AI-friendly format. ~70% token reduction. 9. ccusage 18k⭐ - shows you exactly where your Claude Code sessions are burning tokens. 10. GPTCache 8k⭐ - semantic cache for LLM calls. Stop paying twice for the same question. Save this before your next agent session burns through your subscription 👇

10 GitHub repos with ⭐ 450k+ combined stars that stop your agent from wasting tokens 1. caveman 98k⭐ - makes your AI agent talk like a caveman. Same answers, 65% fewer output tokens. 2. rtk 76k⭐ - CLI proxy that filters git/test/docker output before it hits your context. Up to 90% less bash noise. 3. mem0 63k⭐ - memory layer for AI agents. Stops your agent from re-explaining the same context every session. 4. context7 60.7k⭐ - pulls exact, up-to-date docs into context instead of your agent guessing and burning tokens on retries. 5. aider 48k⭐ - builds a map of your repo instead of loading the whole codebase into context. 6. code-review-graph 30k⭐ - graphs your codebase so your agent reads 2-3 files instead of the whole repo. Up to 376x fewer tokens per question. 7. serena 28k⭐ - gives agents symbol-level code access instead of reading full files line by line. 8. repomix 28k⭐ - compresses your entire repo into an AI-friendly format. ~70% token reduction. 9. ccusage 18k⭐ - shows you exactly where your Claude Code sessions are burning tokens. 10. GPTCache 8k⭐ - semantic cache for LLM calls. Stop paying twice for the same question. Save this before your next agent session burns through your subscription 👇

unicode

66,891 просмотров • 29 дней назад