korchasa/delegate-to-ide

Delegate to Another AI IDE

You are NOT the courier — the worker subagent is. This skill exists to keep the child CLI's transcript out of your context. If you shell out to codex / claude / opencode / cursor-agent yourself from this parent session, you defeat the point — every byte of the child's output then lands in your working context. Always invoke the subagent instead.

When to use this skill vs ai-ide-runner

• Use this skill (delegate-to-ide) when the user wants the other IDE to do a task on their behalf and only the final result needs to surface in the current chat. The child's intermediate work stays in the subagent's isolated context.
• Use ai-ide-runner when the user wants a one-shot relay (second opinion on a single question), a fan-out comparison across several IDEs, or a cross-model comparison within one IDE. There the child's full output IS the deliverable, and isolation buys nothing.

Workflow

Step 1 — Parse the user's intent

Extract:

• {target_ide} — codex, claude, opencode, or cursor-agent. If the user named only a vendor or a model, map to the vendor's native IDE (Anthropic / Claude → claude; OpenAI / GPT / o-series → codex; Cursor's own Composer → cursor-agent). Reach for OpenCode only when the user says "in OpenCode", asks for OpenRouter billing, or asks to fan out across providers (in which case ai-ide-runner is almost certainly the better skill).
• {model} — optional. If unspecified, leave to the worker (it uses the target's flagship alias).
• {task_prompt} — the actual task description the target IDE should execute. Strip routing scaffolding ("delegate to Codex:", "have Claude do …") so the worker passes a clean prompt to the child CLI.

Step 2 — Invoke the worker subagent

Per-host invocation syntax:

• Claude Code: use the Agent / Task tool with subagent_type=worker.
• OpenCode: use the @worker <task prompt> mention syntax.
• Cursor / Codex (no native subagent dispatch): subagent invocation is unavailable on these hosts. Surface this limitation clearly to the user and route them to ai-ide-runner for one-shot relay. Do NOT silently fall back to running the child CLI inline — that would defeat the context-isolation point that motivates this skill.

Pass the worker a single block containing:

Target IDE: {target_ide}
Model: {model or "default"}
Task prompt:
{task_prompt}

Step 3 — Relay the worker's reply

The worker returns a labelled, quoted block with the child CLI's output. Surface that block to the user verbatim — do NOT add commentary inside the quoted block, do NOT paraphrase the child's content, do NOT translate or re-style. Brief framing outside the block (e.g. "Codex returned:") is fine.

If the worker reports that the host has no subagent mechanism (see Step 2, Cursor / Codex case), pass that message through and stop.

Output contract

This skill's final message MUST consist of:

1. A short preface naming the target IDE (one line).
2. The worker's quoted block, byte-for-byte. The substantive content words inside the block come from the child runtime's stdout (or from the hook reason payload on sandbox runs), NOT from the parent model's weights.
3. (Optional) A short follow-up question to the user.

Do not, under any circumstances, run claude -p / codex exec / opencode run / cursor-agent -p from this parent session. If you find yourself drafting such a Bash call, STOP — go to Step 2 and invoke the subagent instead.

Scope boundaries

This skill covers invocation routing: parsing the user's intent, choosing the worker as the execution vehicle, and surfacing the worker's reply. It does NOT:

• compare runs across IDEs or models (use ai-ide-runner);
• fan out one prompt across multiple IDEs (also ai-ide-runner);
• install CLIs, run authentication flows, or persist transcripts;
• carry multi-turn delegated conversations (single-shot only — multi-turn via session resume is a future enhancement).