[ACL 2026 Oral] "LightReasoner: Can Small Language Models Teach Large Language Models Reasoning?"
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Updated
May 22, 2026 - Python
[ACL 2026 Oral] "LightReasoner: Can Small Language Models Teach Large Language Models Reasoning?"
Noise-canceling context and long-term memory for your AI agent. Stop paying Claude to read 10,000 lines of terminal noise like a headphone for AI agent
Dev tools, optimized for agents. Structured, token-efficient MCP servers for git, test runners, npm, Docker, and more.
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An agentic memory database that cuts session tokens by 82–99%. One portable SQLite file — your agent's memory, anywhere.
Token-efficient data serialization for LLM/AI. 50% fewer tokens than JSON, 93% better value/token. Rust, schema validation, LSP.
Verified code context for agents
Claude Code skills for developers who code like cats — never more effort than the problem requires.
Persistent memory for Claude Code — 3-5x longer sessions, 60-80% fewer wasted tokens. Branch-aware, self-healing, token-efficient.
One-Click Agent Engineering Infrastructure on VPS. Deploy private multi-agent environments with a 50k-line Next.js Aircraft Carrier architecture. Replaces heavy code-generation loops with atomic MCP commands, eliminating file system parsing to drive AI token spend to absolute zero.
A curated list of strategies, tools, papers, and resources for reducing LLM token costs and improving efficiency in production.
The AI-native wire format for structured data. 100% comprehension on every frontier model. 50-92% fewer tokens than JSON. 43B+ lossless round-trips across 17 formats. Spec v3.2 Stable.
The web data layer for AI agents — fetch, search, crawl, extract, screenshot, and monitor the web with 50+ domain extractors and MCP.
The data integrity layer that stops AI agents from silently corrupting shared state — across sessions, time, and concurrent runs.
Open-source platform for token-efficient AI agents. Self-host with docker compose up.
Navigate your way - manual steering, steered autonomy, or autonomously. Kompass keeps AI coding agents on course with token-efficient, composable workflows.
MCP proxy: zero-code GCF adoption. Wraps any MCP server, converts JSON to GCF mid-flight. 53-71% fewer tokens. Works with any structured data.
A Codex skill for token-efficient subagent delegation and lean handoffs.
Coding agents forget your repo. mcp-brain is the missing memory layer — repo-aware, team-aware, lifecycle-aware. 63% Hit@10, zero LLM cost. Works with any MCP client.
A lightweight Python protocol and tool for agent-oriented documentation
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