Ellipsis is an AI developer tool that automatically reviews code and fixes bugs on pull requests. Trusted by 9,300+ Github users. We launched on Product Hunt! Since then, we've grown to over 9,300+ developers using the product in 29,000+ codebases. We're free for public GitHub repositories! Simply install to use. Ellipsis is an AI teammate capable of answering questions, creating release notes, feature development, and fixing build issues. We understand that a wrong, confident answer is worse than a non-answer. When Ellipsis is confused, it's explicit about it. Ellipsis will never commit code without your explicit permission. You can configure Ellipsis to raise a side-PR so it's changes are clear. Ellipsis is SOC 2 Type 1 certified. To request a copy of our report, please email team@ellipsis.dev or schedule a call with a founder.
Features & Capabilities
—Get deep, LLM-powered code reviews on every commit of every pull request
—Our code review AI can run and debug code, catching issues that traditional static code analysis tools can’t.
—Add your own review rules to customize the review behavior.
—Ellipsis can learn from your feedback to improve.
—Hide old reviews in bulk to reduce clutter on long-running PRs.
—Modify confidence_threshold to show fewer/more comments.
—Add rules to enforce your team’s style guide using the UI or code in your ellipsis.yaml file.
—If quiet mode is enabled, Ellipsis will only leave reviews when it has comments, so “Looks good to me” reviews will be skipped.
Disable automatic code review using auto_review_enabled.
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—Enable auto-review on draft PRs using auto_review_draft.
—Disable auto-review on particular branches by specifying names (or Unix shell-style wildcards).
—Allow Ellipsis to approve PRs using enable_approve_prs.
Ellipsis.dev is an AI agent profile on explainx.ai. The directory summarizes positioning, optional website links, and community ratings so buyers and developers can compare agents before visiting the vendor.
How are Ellipsis.dev reviews calculated?
This page shows 75 ratings with an average of about 4.6 out of 5, combining illustrative sample rows with signed-in user reviews—always validate claims on the official product site.
Where can I browse more agents?
Use the explainx.ai agents index at /agents to filter by category, upvotes, and related listings.
✓Save 5-10 hours/week on routine coordination tasks
Information Synthesis
Gather data from multiple sources and summarize
Example: Research competitor pricing across 5 websites, create comparison table
✓Reduce research time from hours to minutes
Decision Support
Analyze options and recommend actions
Example: Review 20 vendor proposals, score against criteria, rank top 3
✓Make data-driven decisions faster
Architecture
AI agents combine large language models with tools, memory, and decision-making logic to autonomously complete multi-step tasks without constant human guidance.
LLM Core
Large language model for reasoning and decision-makingUnderstand tasks, plan steps, generate responses
Tool Integration
APIs, databases, external services the agent can callTake actions beyond text generation (search, compute, write files)
Memory System
Short-term (conversation) and long-term (persistent) memoryMaintain context across interactions and learn from past actions
Orchestration Logic
Decision engine for choosing next actionPlan multi-step workflows and handle errors/edge cases
Implementation Guide
Prerequisites
Clear task definition and success criteria
APIs and tools agent will need to access
Approval workflows for sensitive actions
Monitoring and logging infrastructure
Steps
1Define agent scope and capabilities
2Integrate necessary tools and APIs
3Build orchestration logic for task planning
4Test with low-risk tasks in sandbox
5Monitor performance and iterate
6Scale to production use cases
Key Considerations
Best Practices
✓ Do
Start with narrow, well-defined tasks
Monitor agent actions and outcomes
Provide human oversight for critical decisions
Iterate based on real-world performance
Measure ROI: time saved, errors reduced, costs
✗ Don't
Don't deploy without testing edge cases
Don't give agent access to sensitive systems without safeguards
Don't ignore agent errors—investigate and fix root cause
Don't scale before proving value on pilot tasks
Performance & Optimization
Key Metrics
Task completion rate: % of tasks agent completes successfully
Time to completion: Agent vs. human baseline
Error rate: % of tasks requiring human intervention
Cost per task: LLM costs vs. human labor savings
Optimization Tips
Cache common workflows to reduce redundant LLM calls
Fine-tune decision logic based on failure patterns
Expand tool library to handle more use cases
Implement human-in-loop for high-stakes decisions
agent reviews
Ratings
4.6★★★★★75 reviews
★★★★★Aarav Gupta· Dec 20, 2024
Ellipsis.dev is among the more trustworthy entries we bookmarked; the explainx.ai profile reads like a practitioner summary.
★★★★★Yuki Lopez· Dec 16, 2024
We compared Ellipsis.dev with three neighbors in the same category; this one had the most concrete “what it does” framing.
★★★★★Luis Robinson· Dec 12, 2024
According to our evaluation, Ellipsis.dev benefits from clear positioning — fewer buzzwords than typical agent landing pages.
★★★★★Mia Gill· Dec 4, 2024
Ellipsis.dev is among the more trustworthy entries we bookmarked; the explainx.ai profile reads like a practitioner summary.
★★★★★Rahul Santra· Nov 27, 2024
We piloted Ellipsis.dev for two weeks; the registry summary and category tag matched what the product actually emphasizes.
★★★★★Ira Huang· Nov 23, 2024
Ellipsis.dev reduced evaluation time — saves/upvotes on explainx.ai correlated with fewer surprises in the trial.
★★★★★Aarav Ghosh· Nov 19, 2024
We piloted Ellipsis.dev for two weeks; the registry summary and category tag matched what the product actually emphasizes.
★★★★★Meera Singh· Nov 15, 2024
Ellipsis.dev is a strong agent listing on explainx.ai — the profile made it easy to compare capabilities before we signed up on the vendor site.
★★★★★Hiroshi Thomas· Nov 11, 2024
Ellipsis.dev reduced evaluation time — saves/upvotes on explainx.ai correlated with fewer surprises in the trial.
★★★★★Soo Liu· Nov 7, 2024
Solid agent profile: Ellipsis.dev links out cleanly and the on-site reviews add signal beyond marketing copy.
showing 1-10 of 75
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Security: What actions can agent take without approval?
Reliability: What happens when agent fails mid-task?
