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

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

Paid

Shared team workspace where colleagues collaborate with Claude and Codex using the AI subscriptions they already pay for.

Shared Spaces: Team-level workspaces where threads, docs, and apps live together, so AI work from individual conversations compounds instead of disappearing.
Bring Your Own Subscriptions: Connect the Claude and Codex plans the team already pays for rather than buying a separate seat-based AI plan.
Self-Learning Memory: Context, memory, and skills accumulate in a shared company brain that keeps improving as the team works.
Shared Integrations: Securely share access to connected tools across a Space so teammates can act on the same systems without duplicating credentials.
Works Where You Communicate: Tag Type from Slack, email, or a meeting and have the work sync back to the dedicated desktop and mobile apps.
Always-On Automations: Unlimited skills and automations run 24/7 on shared cloud computers, so repeatable work continues outside active sessions.
Usage Controls and Permissions: Administrative controls over credits, access, and permissions across team members and Spaces.

Marketing Campaign Production: A growth team drafts a monthly product announcement email in a shared thread, pulling in past sends and recent releases.
Creative Asset Review: A brand team asks an agent for on-brand image directions inside a Slack channel and keeps the resulting thread in a shared Space.
Engineering Collaboration: Developers share Codex conversations so teammates can pick up context on a change instead of restarting from scratch.
Institutional Knowledge Capture: Turn one-off AI conversations into a durable, searchable team memory rather than private chat history.
Recurring Workflow Automation: Set up repeatable skills and automations that run on a schedule against the team's connected tools.