Tagged articles

Tool Scheduling

3 articles · Page 1 of 1

Oct 1, 2026 · Artificial Intelligence

Pi vs DeepSeek Harness: Agent Loop Design for Continuation, Closure & Recovery

This article compares Pi and DeepSeek Harness agent loop architectures across four control points—input attribution, tool scheduling, closure permissions, and persistent evidence—revealing how each handles mid-task user constraints, parallel tool execution, token truncation, and crash recovery through distinct runtime contracts and durable extensions.

Agent ArchitectureDeepSeek HarnessPi

0 likes · 20 min read

Pi vs DeepSeek Harness: Agent Loop Design for Continuation, Closure & Recovery

Code Mala Tang

Jun 18, 2026 · Artificial Intelligence

From Tool Calls to Real Execution: Inside Claude Code’s 43‑Tool Scheduling System

The article dissects Claude Code’s tool runtime, detailing how a unified TypeScript interface, a feature‑gated registry, a seven‑stage dispatch pipeline, and a concurrency scheduler transform model‑generated tool_use blocks into safe, parallel or serial system operations, including dynamic MCP extensions.

Claude CodeLLM Tool ExecutionMCP

0 likes · 19 min read

From Tool Calls to Real Execution: Inside Claude Code’s 43‑Tool Scheduling System

AIWalker

Apr 6, 2026 · Artificial Intelligence

How TIR‑Agent Turns Image‑Restoration Tools into a Learnable Decision‑Making Agent

The paper introduces TIR‑Agent, an image‑restoration agent that learns a tool‑calling policy via supervised fine‑tuning and reinforcement learning, addressing exploration stagnation and multi‑objective reward imbalance, and demonstrates over 2.5× faster inference and superior multi‑metric performance on synthetic and real degradation datasets.

Computer VisionMulti-Objective OptimizationReinforcement Learning

0 likes · 18 min read

How TIR‑Agent Turns Image‑Restoration Tools into a Learnable Decision‑Making Agent