Cursor Grok Workflow
Description
Hand the grunt work to ten Cursor agents at once. Keep every decision yourself. A Cursor Agent CLI fan-out skill for Claude Code and Codex — built around the fact that the model will report success for work it never performed.
Installation
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open the source below and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
README
Cursor-Grok-Workflow (`cursor-w`)
**Hand the grunt work to ten Cursor agents at once. Keep every decision yourself.**
This is a skill for coding agents — Claude Code, Codex, or any harness that can read a `SKILL.md` and run a Node script. It lets your agent dispatch up to 10 Cursor Agent CLI subagents in parallel (running Grok), each with its own task, and then verify what they actually did.
Ported from [grok-w](https://github.com/sauerlandtreffi/grok-w), which does the same thing with the xAI Grok Build CLI.
Why this exists
Fanning out work to subagents is easy. Trusting the answers is not.
The model will report success for work it never performed. Not occasionally, and not in a way that looks like failure.
grok-w measured this on grok-4.6 across 22 real tasks: a `node --version` it never ran (and got wrong), files it claimed to have written that were never on disk, facts "extracted" from a file it never opened. Every one came back schema-valid, confident, and `status: ok`.
So this is not a thin fan-out wrapper. **The verification is the product.**
The tell is mechanical, and Cursor makes it directly observable: its `stream-json` output emits an event per tool call, so the runner counts them.
**A task that needed to look at the world, and made zero tool calls, made its answer up.**
The runner flags that as `suspectNoToolCall`. The doctrine treats a flagged result as fabricated until you prove otherwise — by opening the files and running the proof command yourself.
**A second tell had to be added for Cursor**, and it is the more useful one. Measured live: a shell command dispatched without `--force` comes back `rejected` — five attempts, every one refused — while the process still exits **0** with `subtype: "success"` and `is_error: false`. The task made five tool calls, so the zero-tool-call flag never fires, and nothing in the machine-readable result says the work was blocked. Only the event stream knows:
**`rejectedToolCalls > 0` ⇒
Related Skills
Agency Agents
A complete AI agency at your fingertips - From frontend wizards to Reddit community ninjas, from whimsy inject
AI Awesome Llm Apps
100+ AI Agents, Agent Skills and RAG Apps - Free and Open Source.
AI Firecrawl
🔥 The API to search, scrape, and interact with the web for AI
AI Artifacts Builder
Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web tech
AI Headroom
Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agen
AI CrewAI
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewA
AI