Agent

Sat, 19 Jul 2025 10:50:10 +0800

Agent

What is an agent

An AI agent is an LLM wrapped in a loop that can act, not just answer. The model decides which tool to call, observes the result, and repeats until the goal is met. The essential ingredients are:

A model — the reasoning engine.
Tools — functions it can call (run a command, read a file, search the web).
A loop — plan → act → observe → re-plan, until done.
Context / memory — the task, prior steps, and relevant project knowledge.

A plain chatbot returns text. An agent edits files, runs tests, fixes the failures, and reports back — it closes the loop on real work.

What is an agent plugin

A plugin packages reusable capability so you don’t re-teach the agent every time. Across today’s tools a plugin typically bundles some of:

Slash commands — custom prompts/workflows you invoke by name.
Subagents — specialized helpers the main agent can delegate to.
Skills — domain knowledge loaded on demand.
Hooks — scripts that fire on events (e.g. before a commit).
MCP servers — connections to external systems (see MCP).

Plugins make an agent extensible and shareable: install one and the agent gains new commands and integrations instantly.

Three mainstream agents

Agent	Form	Strength	Trade-off
Claude Code	CLI / IDE	Deep autonomy, rich plugin + MCP + skills ecosystem	Terminal-first; needs a Claude subscription/API
Cursor	Full IDE (VS Code fork)	Best inline editing UX, multi-model, great for exploration	You switch editors; agent autonomy is shallower
GitHub Copilot	IDE extension + coding agent	Native GitHub/PR integration, huge install base	Less open/customizable, ecosystem-locked

The differences in short:

Claude Code is the most agentic and the most open to extend — plugins, skills, hooks and MCP make it programmable. Best when you want the agent to drive multi-step work autonomously.
Cursor wins on editing experience. It’s an IDE, so completions, diffs and context-picking feel native. Best for hands-on, in-editor coding.
Copilot wins on integration and ubiquity. It lives where your code already is (GitHub, VS Code, JetBrains) and its coding agent can take an issue to a PR. Best for teams already standardized on GitHub.

There is no single winner — pick by how much autonomy vs. inline control you want, and how much you care about extensibility vs. zero-setup integration.

Developing a plugin

Using Claude Code’s plugin system as the concrete example, a plugin is just a directory with a manifest plus the components it adds:

my-plugin/
├── .claude-plugin/plugin.json # name, version, description
├── commands/ # slash commands (markdown prompts)
├── agents/ # subagent definitions
├── skills/ # on-demand knowledge
├── hooks/ # event scripts
└── .mcp.json # MCP servers to wire in

The workflow is roughly:

Scaffold the directory and plugin.json manifest.
Add a command — a markdown file whose body is the prompt the agent runs.
Optionally add subagents, skills, hooks, or MCP servers.
Install it locally to test, then publish via a marketplace/repo so others can install it.

You’re not writing model code — you’re writing prompts, configuration, and small scripts that compose into reusable behavior.

Resources

https://docs.claude.com/en/docs/claude-code

https://cursor.com/

https://github.com/features/copilot

Coding Agent on Morgoth

Agent

Agent

What is an agent

What is an agent plugin

Three mainstream agents

Developing a plugin

Resources