Cursor Delegate logo

Cursor Delegate

CommunityPopular
amElnagdy
cursor-delegate

Delegate a coding task to the Cursor Agent CLI (`cursor-agent`) as a background implementer, then review its diff and land it yourself. Use this whenever the user wants to hand implementation work to Cursor — phrasings like "have Cursor implement X", "delegate this to Cursor", "run it through Cursor Agent", or "use Cursor to implement/fix/refactor" — or wants to run a queue of coding tasks through Cursor while staying the reviewer. DO NOT USE for tasks small enough to do inline, or when the user wants the code written directly without delegating.

Overview

PublisheramElnagdy
Repositorydelegate-skills
Skill namecursor-delegate
Stars
2.1K
Forks
167
Bundled files
5
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by amElnagdy on GitHub. Read the source before you install it.

Installation

Install the Cursor Delegate AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/amElnagdy/delegate-skills.git /tmp/delegate-skills
mkdir -p .claude/skills
cp -r /tmp/delegate-skills/skills/cursor-delegate .claude/skills/cursor-delegate
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cursor Delegate in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Cursor Delegate on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Cursor Delegate is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Cursor Delegate

You are the orchestrator. Hand a bounded coding task to a separate implementer — the Cursor Agent CLI — then review what it produced and land it yourself. You write the brief and own the judgment; Cursor does the typing in its own session; you verify and commit.

The loop needs only a shell command and file access, so any comparable orchestrator can drive it.

When NOT to use this

  • The task is small enough to do inline; delegation overhead is not worth it.
  • The cursor-agent CLI is not installed or authenticated (run cursor-agent login).
  • You want to write the code yourself, or you only need Cursor's opinion on code you wrote (a --read-only dispatch covers that — see below — but a plain review may not need delegation at all).

Prerequisites (check once)

  1. cursor-agent --version succeeds. If not, follow the installer for your platform at cursor.com/cli, inspect what it will run, and authenticate with cursor-agent login.
  2. cursor-agent status shows you logged in.
  3. You are in (or will point --cd at) the target git repository. The relay passes --trust, so point it only at repositories you trust.

Choose the model

Omitting --model uses your Cursor default (usually auto — Cursor picks). To pin one, pass --model <name> with a name from the account's live cursor-agent models output — select from that list rather than inventing a name. Parameterized forms like <name>[context=1m,effort=high] are forwarded as-is. The model that actually served the run is recorded as resolvedModel in result.json.

The loop

Run these five steps per task. Steps 1, 4, and 5 require judgment; 2 and 3 are mechanical.

1. Write the brief

Cursor sees only the text you send plus what it can inspect in the workspace — no chat history or shared context. Include the goal, current state, what to change, what to leave untouched, the project's actual gates, and a report contract. Tell Cursor not to commit. Keep one task per brief. See references/writing-the-brief.md.

2. Dispatch

Use the bundled helper. It wraps cursor-agent -p, feeds the brief on stdin, captures the structured event stream, and writes result.json. (<skill-dir> is the installed folder containing this SKILL.md.)

bash
node "<skill-dir>/scripts/relay.mjs" --brief brief.txt --cd /path/to/repo
# read-only (plan mode — review/diagnosis, no edits):  add --read-only
# write-capable without automatic command approval:   add --no-force
# explicitly override Cursor's sandbox for this run:  add --sandbox enabled|disabled
# pin a model from `cursor-agent models`:              add --model <name>
# resume the most recent session:                      add --resume-last  (delta brief only)
# resume a specific session:                           add --session <id> (delta brief only)
# hard time limit (watchdog):                          add --timeout 2h  (the 30m default suits short runs; implementation briefs routinely need 1-2h)
# see all options:                                     node .../relay.mjs --help

The child process's cwd pins the workspace. On Cursor 2026.07.23 or newer, use repeatable --add-dir flags only for extra workspace directories. The relay writes artifacts under the system temp dir by default and never commits. See references/dispatch-and-poll.md.

3. Wait for completion

The helper blocks until Cursor finishes. Run it with the orchestrator's background-command facility, or background it in the shell and poll for result.json. A pre-run usage error exits 2 and writes no result; a missing cursor-agent exits 127 and writes status: "cursor_agent_unavailable".

Trust process state and the working tree over a progress display. Completion means the process exited and result.json exists. Cursor's full report is the finalMessage field in result.json (also printed in full on stdout between the report markers).

Windows + hooks caveat: if the user has Cursor hooks configured (~/.cursor/hooks.json, or Claude Code PreToolUse hooks, which cursor-agent imports), dispatching from a Git Bash (MSYS) console makes cursor-agent feed PowerShell-syntax hook wrappers to bash, so every command Cursor tries to run is blocked — edits still land, gates do not run. Dispatch from a PowerShell or cmd console instead. Details: references/dispatch-and-poll.md.

4. Review — do not trust the self-report

Treat Cursor's final message and gate claims as claims:

  • Re-run the project's gates yourself.
  • Read the diff against the brief, starting with touchedFiles.
  • Run relevant guard skills if installed.
  • Round-trip migrations and grep for dangling references after removals or renames.

See references/review-and-land.md.

5. Land it

The implementer edits the working tree; the orchestrator commits. Commit only after the gates pass and the diff holds. If rework is needed, send a delta brief with --resume-last or --session <id>, then review again.

Autonomy and permissions

A fresh run defaults to write-capable with --force: Cursor runs commands without approval unless your Cursor config explicitly denies them, so ordinary gates (tests, linters, builds) run headlessly. --no-force keeps the run write-capable but withholds automatic command approval; commands that require approval are refused because a headless run cannot prompt. --read-only switches to Cursor's plan mode (read-only analysis, no edits, no --force). The relay always passes --trust to keep headless runs from stalling on the workspace-trust prompt, which is why --cd must only ever point at repositories you trust. Pass --sandbox enabled or --sandbox disabled only when you need to override Cursor's sandbox for that dispatch. The requested value is recorded as sandbox in result.json; it does not claim what Cursor actually applied. The permission mode Cursor reports is recorded as permissionMode; inspect touchedFiles and the diff after every run.

Read-only second opinions

--read-only doubles as a clean way to get an adversarial second opinion with no write risk: dispatch a brief that lists the agreed points, then each contested point with both positions, and ask Cursor to defend or concede each — deliverable in its final message, touching no files.

Authorization model

Delegation is something the human opts into. Once they have ("run this queue", "proceed"), committing verified, gate-passing work is the agreed contract. Two limits remain: surface, don't absorb (report Cursor's design decisions, defensible-but-unasked turns, and non-blocking nitpicks) and stop for scope changes (if correct completion needs going beyond the brief, ask instead of expanding the mandate). See references/review-and-land.md.

References

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Cursor Delegate AI skill do?

Delegate a coding task to the Cursor Agent CLI (`cursor-agent`) as a background implementer, then review its diff and land it yourself. Use this whenever the user wants to hand implementation work to Cursor — phrasings like "have Cursor implement X", "delegate this to Cursor", "run it through Cursor Agent", or "use Cursor to implement/fix/refactor" — or wants to run a queue of coding tasks through Cursor while staying the reviewer. DO NOT USE for tasks small enough to do inline, or when the user wants the code written directly without delegating.

Why use Cursor Delegate on TypingMind?

Because you install it once and use it with any model. Cursor Delegate is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Cursor Delegate in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/amElnagdy/delegate-skills/tree/master/skills/cursor-delegate. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Cursor Delegate?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Cursor Delegate?

As many as you like. As long as a model supports skills, you can use Cursor Delegate with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Cursor Delegate AI skill free?

Yes. It is published on GitHub by amElnagdy under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇