CleanSlop vs Jackalope: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of CleanSlop and Jackalope — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

CleanSlop

Freemium

Scans vibe-coded apps for launch-blocking issues like leaked keys and data exposure, and reports what to fix first, right from your coding agent.

Agent-Native Scanning: Tell Claude Code, Codex, Cursor or other agents to scan with CleanSlop and fix findings where you build.
System-Level Code Mapping: Maps routes, background jobs, data and external services so each finding follows a real call path.
Prioritized Reports: Findings grouped as needs attention, worth a look and minor, worst first.
Evidence for Every Finding: Shows where each issue lives in your code and why it was flagged.
Plain-English Fixes: Explains what is wrong, why it matters and what to do about it.
Copy for LLM: Hands any report to your AI tool so it can apply the fixes.
GitHub App Integration: Scan only the repositories you select, read-only access.
Expert Triage Calls: Book a 15-minute call with a CleanSlop engineer to walk through findings.

A solo founder checks a Next.js and Supabase app built with an AI coding assistant before launching.
A developer discovers an exposed AI API key bundled into browser code and moves it to a server route.
A side-project builder verifies that one user's data cannot be read by another through database policies.
A Claude Code user runs a scan from the terminal and has the agent fix the top findings.
A team lead gets a short prioritized list instead of hundreds of linter warnings.
An indie hacker books an expert triage call to confirm an ambiguous finding.

Jackalope Digital LLC

Free

A desktop workspace for running Codex, Claude Code, Grok, OpenCode, Kimi Code and Antigravity in parallel Git worktrees.

Parallel Tasks in Git Worktrees: Every task runs in its own worktree so multiple agents work simultaneously without colliding, with dependencies set when one change needs another.
Six Supported Agents: Assign Codex, Claude Code, Grok, OpenCode, Kimi Code or Antigravity per task, using each agent's own installed CLI and permission rules.
Interactive Codebase Map: Browse resolved file dependencies to trace the reach of a change and choose what to inspect next during review.
Carried-Forward Project Context: Save project guidance once; new tasks match relevant guidelines to the prompt, inherit defaults, and let you inspect what the agent actually received.
Unified Code Review: Read each result beside its original brief, combine related patches into one review, request another pass, and decide what enters the project.
Named Account Profiles: Keep work and personal agent accounts separate with per-project defaults and per-account usage tracking.
Agent Browser and Computer Use: A separate browser session per task lets agents navigate pages, fill forms, capture screenshots and run accessibility checks; Windows desktop control adds approved window clicks, typing and scrolling.
Cross-Agent Messaging: Tasks share a project inventory with ownership, scopes and dependencies, and agents can send direct task messages or project broadcasts through a durable inbox.

Running Experiments Side by Side: Try two different approaches to the same problem with different agents and compare the resulting patches before choosing one.
Reviewing Agent Output Safely: Keep every generated change behind a human review step, with checks attached to the code they tested.
Comparing Coding Agents: Assign the same brief to Codex, Claude Code and Grok to see which handles your codebase best.
Separating Work and Personal Accounts: Use the right provider account per project without re-authenticating or risking cross-billing.
Understanding a Change's Blast Radius: Use the codebase map to see which files a proposed change touches before merging it.
Automating Verification: Let agents drive a sandboxed browser to fill forms, screenshot results and run accessibility audits as part of a task.