The actual benchmarks from the original plugin: → Average 65% output token reduction across 10 real prompts
→ Range: 22-87% depending on task type
→ Coding explanations saw the highest compression
→ Code blocks themselves stayed identical One tester ran it for 6 days on a
TOOLS
-
Performance Benchmarks of AI Plugin Token Reduction
By
–
-
How to optimize Claude’s output using custom skills
By
–
Julius Brussee's caveman plugin hit 51,000+ GitHub stars in two weeks. It cuts Claude's output tokens by 65%. I turned it into a Claude skill you can build in 30 seconds. Copy the prompt below. Ask Claude to build the skill. Save it in your Customize settings.
-
Multi-agent system that iterates on game mechanics
By
–
Can AI truly iterate on game mechanics, not just generate one-off code? CreativeGame Team (Univ. of Bristol, SJTU, Shandong Univ., Nanjing Univ., Sreal AI) built a multi‑agent system that treats game mechanics as explicit objects. It uses programmatic rewards (not subjective
-
SmallCode: A Terminal-Native Coding Agent for Local AI Models
By
–
SmallCode is a terminal-native coding agent designed from the ground up to extract useful work from local models (7B-20B) running on consumer hardware.
-
Running local terminal AI agents with Ollama
By
–
It runs locally without any cost. SmallCode is not a model. It's a terminal agent. Here's Gemma 4 model on @ollama
: https://
ollama.com/library/gemma4 I'd suggest to read the post before commenting LOL -
Local AI coding agent workflow with Hermes orchestrator
By
–
LOCAL AI coding agent finally make sense with Hermes orchestrator. Hermes routes work through Kanban. SmallCode uses Ollama models on a Mac mini for scoped patches, tests, and repo cleanup. Claude and Codex do the heavy lifting. All of it tracked in a single Kanban board.
-
AI-driven protein design tools for biologists from MIT
By
–
Bringing #AI-driven protein-design tools to biologists everywhere
by Zach Winn @MIT Learn more: https://
bit.ly/4ckoT4T #ArtificialIntelligence #MachineLearning #ML -
Manus AI Agent Adds Persistent Memory for Recurring Tasks
By
–
🆕 Manus just dropped Scheduled Tasks 2.0 – and it's not just "run this again at 9 AM."
— Futurepedia – Learn to Leverage AI (@futurepedia_io) 19 mai 2026
Now your recurring tasks carry full context. Same conversation. Same files. Same project setup.
Your AI agent finally has memory between runs.
🔗 https://t.co/RaCxZrv5vK#Manus #AITools… pic.twitter.com/tnZpQIv4INManus just dropped Scheduled Tasks 2.0 – and it's not just "run this again at 9 AM." Now your recurring tasks carry full context. Same conversation. Same files. Same project setup. Your AI agent finally has memory between runs. https://
manus.im/blog/manus-sch
edules
… #Manus #AITools -
A Guide to Setting Up Local AI Environments
By
–
Gentle reminder that all you need to start with Local AI is: – 2x RTX 3090s (pick up for $700-$900 on r/hardwareswap) – Qwen 3.6 27B / Gemma 4 31B – Your favorite agent (Claude Code / OpenCode / etc) – Self-hosted SearXNG for web access And you got yourself Opus 4.5 at home
-
Composer 2.5: Efficiency and AI Capability
By
–
Intelligence too cheap to meter. This is the real deal. Composer 2.5 is an efficiency-beast