AgentLoop vs WorkClaw: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of AgentLoop and WorkClaw — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
AgentLoop
Edward Yi
AgentLoop turns a single ChatGPT plan into unattended Codex worker + independent-critic cycles that build against your local rubric until the work passes.
Key features
- Fresh Worker Per Cycle: Each build cycle spawns a clean Codex worker with fresh context so long-running loops do not accumulate stale state or memory drift.
- Independent Critic Process: A separate fresh process grades every result against your rubric so passing tests never become permission to stop looking.
- Rubric in GUIDELINES.md: Definition-of-done lives as plain Markdown in your repo and is read on every cycle, so standards persist while prompts do not.
- Evidence Carried in Files: Worker output, critic verdicts, and fixes are written to project files so the next cycle inherits the actual state of the work.
- Bounded Goal + Cycle Budget: You cap the loop with a goal.md and cycle budget so unattended runs stop at a predictable ceiling.
- MCP Status Interface: Ask ChatGPT for status through MCP so you can monitor cycles, verdicts, transcripts, and cost without opening the dashboard.
- Local-first Install: git clone the pinned v1.1.0 release and run node src/daemon.js — no npm install, no hosted workspace, MIT licensed.
Best for
- Shipping a bounded feature: Add a CSV export across UI, API, and regression suite while the critic enforces end-to-end behavior and edge cases.
- Migration work: Run an unattended migration where fresh workers apply the change and the critic verifies each step against a rubric.
- Hardening pass: Give AgentLoop a hardening goal so it iterates on defects the existing test suite misses, like malformed input handling.
- Product polish loop: Point AgentLoop at a polish goal with clear acceptance criteria and let it converge to VERDICT: PASS.
- Unattended overnight runs: Kick off a long loop, monitor cycle verdicts, and cancel from the dashboard or via MCP when the receipt looks right.
- Enforcing team standards: Codify team engineering standards in GUIDELINES.md so every worker builds against the same definition of done.
WorkClaw
Workmate Labs
A team of customizable, collaborative AI coworkers that work 24/7 in Slack, Teams, and email across 3,000+ apps.
Key features
- Collaborative AI Coworkers: Customizable Claws that work proactively and collaborate with your team and each other.
- Works Where You Do: Each Claw collaborates over Slack, Teams, email, and 3,000+ connected apps.
- Always-On Cloud Computers: Every Claw runs 24/7 on its own cloud computer to get real work done autonomously.
- Custom Skills: Turn team workflows into reusable skills by chatting, or install battle-tested skill packs and tweak them.
- Enterprise Security: Admin controls, a human-approval credential vault, per-Claw data separation, and SOC 2 Type II certification.
- One-Click Setup: Deploy as many WorkClaws as your team needs in a few minutes, all in the cloud.
Best for
- Research Assistance: Delegate background research that runs while the team focuses elsewhere.
- Scheduling and Follow-ups: Automate meeting scheduling, reminders, and follow-up messages.
- Email Drafting: Draft and send routine emails in the team's voice and style.
- Reporting: Generate recurring reports and summaries from connected tools.
- Data Entry: Offload repetitive data entry across 3,000+ integrated apps.