@jcil/cli
v2.14.0
Published
Project Culpepper — the Grok-native autonomous coding agent xAI hasn't shipped yet. Idea to deployed in under two minutes.
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Project Culpepper
The Grok-native autonomous coding agent xAI hasn't shipped yet. So Matt Marren built it.
Idea-to-deployed in under two minutes — real GitHub, real Vercel, real production. Feature-complete enough to use today, open-source enough for xAI to fork tomorrow.
npm install -g @jcil/cli
jcilWhy this exists
xAI has not shipped a first-party autonomous coding agent for Grok. Project Culpepper is what one looks like when you build it from first principles using Grok 4.2 Reasoning under the hood and the architectural patterns from Anthropic's Claude Code as the scaffolding.
It is not affiliated with xAI. It is what one developer built while waiting for the official version. If xAI ships one tomorrow, fork this and take what's useful. Until then, this is the placeholder — and the placeholder already ships real apps to real production.
What it actually does
In one prompt, autonomously:
- Reads, writes, edits, and refactors source files
- Runs shell commands, builds projects, runs tests, fixes failures, re-runs
- Spins up background processes (dev servers, builds, deploys) and monitors them
- Drives your local CLI ecosystem to push code, file issues, open and merge PRs, and deploy to production
- Generates documents, spreadsheets, images, and videos
- Spawns focused, hard-isolated sub-agents for parallel work
- Speaks the standard external-tool-server protocol — drop-in compatible with the entire ecosystem
- Tracks its own work in a persistent task queue, checkpoints to disk when budgets are reached, and resumes across sessions
Built for overnight runs
Most coding agents make you sit there and watch. Culpepper is built for the opposite use case: set a budget, hand it a brief, walk away. It works while you sleep. When the budget runs low it warns at 75%, slows down at 90%, and gracefully checkpoints to disk at 100% so you can pick up exactly where it left off in the morning.
You can also drive it from a cron job, CI script, or shell pipeline:
# One-shot, headless, JSON output for piping into other tools
jcil --prompt "review the diff and post a summary to #eng" \
--budget 5 \
--format jsonThe showcase
You: Build and ship a "Quote of the Day" service.
API + tests + landing page + deploy + repo + tracking issue.[~80 seconds, autonomous]
* Source repo created and pushed
* Live in production at a public URL
* Tracking issue filed with the URL
* Tests written and passing
* Server, landing page, deploy config all verifiedReal run. Real platforms. Real cleanup afterward.
Two ways to run it
Culpepper has two tiers, and you can switch between them at any time.
Managed mode (recommended for most users)
Sign in with your JCIL.AI account on first launch. No API key required. Billed through JCIL with full session, rate-limit, and cost safety nets in place.
jcilBYOK mode (for power users)
Bring your own xAI API key. Hit api.x.ai directly with no markup, no JCIL
session, and no rate limits beyond xAI's own quota. Your key, your bill, your
unlimited overnight runs.
export XAI_API_KEY=xai-...
jcil --byok # interactive
jcil --byok --prompt "..." # headlessHow it compares on cost
Grok 4.2 Reasoning powers it: roughly 7-12× cheaper than Claude Opus 4.6 ($2 input + $6 output per 1M tokens vs $15 + $75) with comparable autonomy depth. The full end-to-end production showcase costs about a dollar.
Quick start
npm install -g @jcil/cli
jcilSign in on first launch, then talk to it. Or:
jcil resume <session-id> # resume a saved session
jcil --prompt "..." # one-shot headless run
jcil --help # all flagsCommon commands inside the REPL
Type /help for the full list. Most-used:
/auto autonomous mode (requires explicit confirmation)
/budget 5 cap session spend; auto-checkpoint when reached
/save manually save a session checkpoint
/sessions list saved sessions
/resume <id> resume a saved session
/tasks persistent task queue
/cost running session cost
/exit quitSecurity
Culpepper is built for autonomous agents handling real credentials on real machines. The stack includes:
- A multi-tier permission model that requires explicit confirmation for autonomous operation
- A command and path validator that blocks destructive and credential-exfiltration patterns
- SSRF and DNS-rebinding protection on every outbound request
- Subprocess credential scrubbing
- Hard tool restrictions for sandboxed sub-agents (filtered at the API boundary, not just the prompt)
- Indirect prompt-injection detection on file and URL contents
- Loop guards and runaway-call detection
- An append-only audit log of every tool call
Specific defense details are intentionally not documented here.
Verification
The release process runs a full test arsenal — unit tests, capability tests, real engineering scenarios, real platform integration against GitHub and Vercel, an end-to-end MCP test against the official filesystem server, the budget mode + checkpoint resume test, and an idea-to-deployed showcase — all green before publish.
Author
Matt Marren · [email protected]
License
MIT
