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

A side-by-side comparison of CleanSlop and hob — 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.

SmartAppsCo

Paid

A macOS workspace that runs Claude Code, Codex and OpenCode side by side, keeping parallel agent work, automations and secrets under your control.

Multi-CLI Agent Panes: Runs Claude Code, Codex and OpenCode side by side in tiled panes and terminals so several agents can be directed from one window.
Agent Handoff and Coordination: Agents pass scoped work between each other — one builds a command palette while another indexes the workspace — with each handoff visible to you.
Automations with Scheduling: Turns recurring jobs such as bug intake, feedback triage or weekly release notes into repeatable runs that follow the same steps every time.
Secret Management: API tokens and deploy credentials are stored in hob and injected at run time, so no agent or inference provider ever sees them.
Pull Request Workflow: Open, comment on and close pull requests in-app, with the diff, the conversation and the change all in one place, driven by hand or via the hob pr command.
Remote Issue Management: Connects to GitHub and Git hosts so issues can be triaged, filed and closed from the same surface the agents work in.
Local-First Architecture: The workspace and its database live on your own machine, with end-to-end encryption when you reach it from another device.
Durable Session History: Keeps a local record of runs and conversations that outlives the terminal session, so agent work can be reviewed or recovered later.

Supervising Parallel Agents: Direct several coding agents working on different parts of a feature at once without losing track of what each one changed.
Recurring Maintenance Automation: Schedule a weekly release-notes run or a daily user-feedback triage pass that executes identically every time.
Bug Intake Pipelines: Reproduce a reported issue, file it and summarize it as a single automated run triggered on demand.
Reviewing Agent Output Before Merge: Inspect the diff, conversation and resulting pull request together so generated changes get a real review instead of a blind merge.
Working Across Providers: Compare how Claude Code, Codex and OpenCode handle the same task using your existing subscriptions rather than resold tokens.
Remote Development: Leave agents running on a machine at the office and check in securely from another device over an encrypted connection.
Keeping Credentials Out of Prompts: Run agent tasks that need deploy tokens or API keys without ever exposing those secrets to the model.