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The coding agents tracker

One bookmark for coding agents, LLMs, and MCP.

Everything on the site about AI coding agents, LLMs, and the Model Context Protocol: Claude Code, Cursor, Copilot agent mode, the Microsoft Agent Framework, MCP servers and skills.

What to read first

Claude Code vs Cursor vs Copilot Agent Mode settles where each wins; Copilot Code Review vs Cursor Bugbot vs a Claude review action does it for review bots. For .NET, start with Microsoft Agent Framework 1.0, then Agent Framework vs Semantic Kernel for the fork. For MCP, what the protocol is and why IDEs ship it explains it; building a custom server in C# walks one end-to-end. Read both against MCP C# SDK 2.0, stateless by default; migrating a 1.x server to 2.x keeps older clients connected. If OAuth succeeds but every call gets 401, the token audience mismatch is the usual cause.

For Claude Code, writing a CLAUDE.md that changes model behaviour leads, and subtask vs fork vs background agent decides when work gets its own context. Before widening an allowlist, read the four permission-check bypasses closed in 2.1.251. What an agent skill is explains why skills beat a longer system prompt. On instruction files, Copilot Memory vs custom instructions vs AGENTS.md says which one the model reads, and consolidating .cursorrules and CLAUDE.md into one AGENTS.md ends the drift.

What’s on this page

The list below auto-collects posts tagged with any of: ai-agents, llm, mcp, claude-code, cursor, github-copilot, agent-skills, microsoft-agent-framework. Newest first.

The companion .NET 11 tracker collects the broader release; many posts overlap.

Index (220 posts)

2026 / 10

  • What Is Tool Calling and Why JSON Schemas Matter More Than Prompts

    Tool calling is a protocol, not magic: the model emits a structured request matching a JSON Schema you supplied, your code runs it, and the result goes back as a message. The schema and its descriptions are rendered into the model's prompt and, with strict mode, into a decoding grammar, so they shape behaviour more reliably than any system-prompt instruction. Here is how it works on claude-sonnet-5-5 and OpenAI strict mode, with schema patterns that make invalid calls impossible.

  • What Is the Difference Between an AI Agent and an AI Workflow?

    In a workflow, your code decides the next step and the model fills in each step. In an agent, the model decides the next step and your code only executes it. That one question (who owns the control flow) determines cost, latency, testability and failure modes. Here is the distinction as Anthropic, Microsoft Agent Framework and LangGraph define it, with the same task built both ways in Python against claude-haiku-4-5 and claude-sonnet-5-5.

  • Agent Framework 1.23: Function Middleware Can Finally Swap the Tool It Is Calling

    Microsoft Agent Framework .NET 1.23.0 honors assignments to FunctionInvocationContext.Function, so middleware can redirect a tool call to a different AIFunction. A new WrapWithPendingMiddleware helper keeps the rest of the chain in the loop.

  • What Is an Agent Skill, and How Is It Different from a System Prompt?

    An agent skill is a folder with a SKILL.md file that the agent loads on demand: only its name and description sit in the system prompt, the instructions arrive when a task matches, and bundled scripts run without ever entering context. Here is how that differs from a system prompt in cost, scope, invocation and trust, with the exact limits from the Agent Skills spec and Claude Code.

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