cursor-coding

name	cursor-coding
description	Spawn a Cursor coding agent for real code work. Use when the user asks for actual code changes -- refactors, bug fixes, new features, repo edits -- that need full file/terminal access and iterative tool calls. Hand off via the cursor_agent MCP tool.
version	1.0.0
author	Kevin Liu
license	MIT
metadata	{"agent-machines":{"tags":["cursor","coding","agents","mcp","delegation"],"related_skills":["agent-ethos","git-workflow","plan-mode-review","taste-output"]}}

Cursor Coding Agent (MCP)

I have an mcp_servers.cursor bridge wired up to the Cursor TypeScript SDK. When the user asks for actual code work -- refactor a file, fix a bug, add a feature, audit a repo -- I do not write the code in my own message. I delegate to a Cursor agent via the cursor_agent MCP tool.

The Cursor agent is the same model that runs in the Cursor IDE: full file access, terminal, codebase semantic search, lints, iterative tool calls until tests pass. I am the orchestrator; Cursor is the implementer.

When to call cursor_agent

Yes:

• "Refactor src/utils.ts for readability"
• "Find the bug in apps/website/auth.ts and fix it"
• "Add a unit test for the new pricing function"
• "Walk this repo and write a one-line summary of every public function in lib/"
• "Migrate the tailwind.config.ts entries to Tailwind v4"

No:

• "What is dependency injection?" -- I answer directly, no Cursor needed.
• "What's in this MEMORY.md?" -- I read it myself.
• "Should I use Postgres or SQLite?" -- discussion, not code.

How to call it

cursor_agent(
    prompt="Refactor src/utils.ts: extract the date helpers into a separate module, keep public API identical, run pnpm typecheck after.",
    working_dir="/home/machine/work/my-repo",
    model="composer-2",
    load_skills=["agent-ethos", "git-workflow", "taste-output"],
)

load_skills is non-negotiable

Always pass load_skills. Pick the skills that match the task. The bridge writes the requested skills into <working_dir>/.cursor/rules/from-agent.mdc so the spawned agent inherits the same conventions the parent agent follows. Without load_skills, the Cursor agent reverts to its defaults -- which are excellent, but generic.

Default bundle for any code work:

• agent-ethos -- minimal-fix philosophy, hard limits
• taste-output -- no skeleton stubs, no // TODO placeholders
• empirical-verification -- verify claims, don't guess

Add as needed:

• git-workflow -- when the task involves commits/branches
• frontend-design-taste -- UI work
• security-audit -- auth, payments, secrets
• production-safety -- anything touching prod resources
• reticle-design-system -- UI work on a Reticle-based project

After the agent runs

cursor_agent returns { agent_id, run_id, status, duration_ms, final_text, loaded_skills, working_dir }.

• status === "finished" -- work shipped. Read final_text for the summary, then verify by reading the files yourself if the user asked for guarantees.
• status === "error" -- the agent ran but failed mid-task. Read final_text for the failure reason, then either retry with a clearer prompt or surface it to the user.
• A thrown CursorAgentError -- auth, network, or config. Bridge returns the message; usually means CURSOR_API_KEY is missing or invalid.

Continuing a conversation

For follow-ups on the same task, use cursor_resume(agent_id=..., prompt=..., working_dir=..., load_skills=...). The Cursor agent retains full conversation context. Pass load_skills again -- they don't persist across resume.

What the user sees

The user sees only my final summary, not the raw stream. I report:

1. What the Cursor agent did (one paragraph from final_text)
2. Files changed (if I can detect via git status afterwards)
3. Whether tests/typecheck pass (I run them via terminal if relevant)

I do not paste 200 lines of agent transcript. The user trusts the delegation.

Gotchas

• working_dir must be absolute. Relative paths get rejected upstream.
• The Cursor agent runs as a subprocess of the bridge (Node) which runs as a subprocess of the agent runtime. Three-layer process tree. Long-running cursor_agent calls can hit the bridge's 600-second tool timeout -- for big refactors, split into multiple sequential calls instead.
• load_skills writes a .cursor/rules/from-agent.mdc file that gets cleaned up when the agent disposes. If the bridge crashes, that file may linger; remove it manually if you see it in git status.