AgentiLoop/Agent - Open Source PR Review Scorecard

Agent! now supports macOS 14.6 or later, Apple Silicon and Intel, latest release. The Best AI agent for Mac: drives any app via Accessibility, codes/builds in Xcode, automates AppleScript, JXA, Swift and SMAppService shell (user/root). 23 LLM providers, local/cloud, plus on-device Apple Intelligence and Jev guard. Auto-Pilot, MCP, Avatar.

C-Rank Grade: A (Welcoming) - 60/100

External PR Merge Rate: 86%

Response Time: 9h

First Timer Success: 80%

Frequently Asked Questions

Is AgentiLoop/Agent welcoming to first-time open-source contributors?

AgentiLoop/Agent has a recorded first-timer success rate of 80.0%. Repositories ranked A typically provide actionable feedback during code reviews and actively nurture new community contributors.

How fast can I expect code review feedback on my pull request?

Maintainers in AgentiLoop/Agent respond to incoming external pull requests in approximately 9.5 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 59.6 C-Rank™ score (A Tier) represent?

The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 59.6 places AgentiLoop/Agent in the A tier.

What is the external contributor pull request merge rate for AgentiLoop/Agent?

The external contributor pull request merge rate for AgentiLoop/Agent is 85.7%, based on public PR activity from non-core contributors.

Are there Good First Issues available in AgentiLoop/Agent?

AgentiLoop/Agent does not currently have active "good first issue" tags indexed, but accepts external contributions through standard GitHub issue tracking.

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AgentiLoop/Agent

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Active (30d)A•Welcoming(60/100)Swift

Agent! now supports macOS 14.6 or later, Apple Silicon and Intel, latest release. The Best AI agent for Mac: drives any app via Accessibility, codes/builds in Xcode, automates AppleScript, JXA, Swift and SMAppService shell (user/root). 23 LLM providers, local/cloud, plus on-device Apple Intelligence and Jev guard. Auto-Pilot, MCP, Avatar.

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AI Maintainer Review Guidelines

Review Persona

Empathetic Technical Mentor

Warmth Score
7.5/10
Patience Score
8.2/10
Nitpick Rate
20%

Collaborative maintainer environment in AgentiLoop/Agent. Reviews community pull requests with focus on project quality.

What Contributors Actually Say

Discussions in AgentiLoop/Agent focus heavily on practical implementation feedback, code formatting standards, and issue reproduction details.

Hidden Friction Signals

Unlinked PRs without issue context and changes that fail automated test suites face the highest review friction.

Unwritten Rules

  • •1) Keep PR scope strictly aligned with the linked issue.
  • •2) Ensure local linters pass before opening a review.
  • •3) Maintain full test coverage for modified logic.

Top PR Submission Do's

  • •Ensure code complies with the project coding style
  • •Keep PRs scoped to a single concern
  • •Include context and link to the related issue

Top PR Friction Pitfalls (Don'ts)

  • •Do not submit PRs without linking an issue
  • •Do not break existing tests without fixing them
  • •Do not mix unrelated refactors in a single PR
Response Velocity
9 hours
Standard maintainer review cycle

Average Response Latency

Tracks hours until a maintainer leaves a review, comment, or PR response.

Merge Efficiency
85.7%
High acceptance rate for external PRs

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
80.0%
Strong first-timer PR acceptance rate

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
1 core
Single maintainer review bottleneck
Diagnostic Health HUD
85.7%
Merge Gauge
80.0%
1st-Timer
Community Vibe81/100

Embed C-Rank Badge

Show contributors that your repository actively reviews and merges external pull requests.

GetMerged C-Rank badge for AgentiLoop/Agent
[![GetMerged C-Rank](https://getmerged.abhishekco.de/api/badge/AgentiLoop/Agent)](https://getmerged.abhishekco.de/AgentiLoop/Agent?utm_source=github&utm_medium=badge)

Active Good First Issues (4)

View on GitHub

Agent! is a 100% native Swift 6.2 / SwiftUI Mac app that runs an autonomous task loop against 18 LLM providers with your own API keys — reading a codebase, building an Xcode project, driving any app through the Accessibility API, or texting you the result over iMessage. Its native, bring-your-own-key design is the point for Mac users: work stays on the machine, and a task can't declare itself done until its goal criteria carry evidence. That breadth is why the provider list matters: a fallback chain that auto-switches on 429s or timeouts is only as useful as the providers behind it. OrcaRouter speaks the same OpenAI chat-completions shape as the existing OpenRouter and Requesty entries, so it would slot into the picker as another route for long unattended runs. I'm an engineer on the OrcaRouter team, and I'd like to propose OrcaRouter as an optional provider. It would not replace or change any existing provider — just add one more entry beside the current 18. What it could add here

📅 Opened Sep 10, 2026💬 1 comment
Quality: 90/100Contribute

Hi — we represent A2Agent and would like to explore a technical and commercial integration with AgentiLoop Agent. AgentiLoop already supports custom OpenAI-compatible endpoints through API Mode. We would like to verify A2Agent against this integration path, including: automatic model discovery; streaming and non-streaming chat; structured error handling; long-context and multimodal compatibility. If useful, we can contribute a tested configuration guide, optional provider profile, compatibility tests, or documentation following your preferred approach. Separately, with your permission, we would like A2Agent to be listed in the README or project page under Supported Providers, Integrations, Partners, or another section you prefer: A2Agent — an OpenAI- and Anthropic-compatible API gateway providing access to multiple LLM providers. Would you be open to the technical integration and, separately, the link listing? Please let us know your preferred implementation scope, wording, lin

📅 Opened Sep 9, 2026💬 1 comment
Quality: 90/100Contribute

What Agent! ships signed release builds on GitHub Releases, but there's no brew install --cask path. A Homebrew cask makes installation a one-liner and gets Agent! discovered by Homebrew users. Recipe Read the Homebrew cask cookbook Write a cask formula pointing at the latest release artifact (app name is Agent!.app, min macOS 26.4) Either submit it to homebrew/homebrew-cask (preferred, needs the repo to meet their notability bar) or create a tap repo (e.g. macOS26/homebrew-agent) and PR the formula + a README install snippet here Definition of done brew install --cask agent (or brew install macOS26/agent/agent) installs the latest release README Quick Start updated with the brew one-liner No Swift knowledge required — Ruby formula + docs only.

📅 Opened Aug 29, 2026💬 0 comments
Quality: 90/100Contribute

What The README leads with a static screenshot. A short (10–20s) animated GIF showing Agent! doing something Claude Code/Cursor can't — e.g. building an Xcode project, driving Safari, or automating a Mac app via Accessibility — would dramatically improve first impressions. Recipe Build Agent! from source (./build.sh — see CONTRIBUTING.md, no Apple Developer account needed) or download a release Record a short screen capture of a compelling task (QuickTime or screencapture) Convert to an optimized GIF (e.g. ffmpeg + gifsicle), keep it under ~10 MB Drag-and-drop the GIF into a PR editing README.md, placing it right below the badges Definition of done GIF appears near the top of the README, under 10 MB, shows a real task end-to-end No Swift knowledge required — this is a docs/media contribution.

📅 Opened Aug 29, 2026💬 0 comments
Quality: 100/100Contribute
Looking for more Swift beginner tasks?Explore Swift GFI

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Contributor Compatibility & Review Speed Analysis for AgentiLoop/Agent

When evaluating whether to contribute to AgentiLoop/Agent, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.

Currently, maintainers of AgentiLoop/Agent acknowledge new external contributions in approximately 9 hours. Out of all submitted pull requests from non-core authors in the last 180-day window, 85.7% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to AgentiLoop/Agent

01

Is AgentiLoop/Agent welcoming to first-time open-source contributors?

AgentiLoop/Agent has a recorded first-timer success rate of 80.0%. Repositories ranked Welcoming typically provide actionable feedback during code reviews and actively nurture new community contributors.

02

How fast can I expect code review feedback on my pull request?

The initial maintainer response time averages ~9 hours. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 59.6 C-Rank™ score represent?

The C-Rank™ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 59.6 places AgentiLoop/Agent in the Welcoming tier.

04

What is the external contributor pull request merge rate for AgentiLoop/Agent?

The external pull request merge rate is 85.7%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.

05

Are there beginner Good First Issues open in AgentiLoop/Agent?

AgentiLoop/Agent does not have open beginner labels indexed currently, but external PRs for bugs and documentation improvements are evaluated via normal issue triage.

GetMerged C-Rank™ Indexing Standard

All metrics displayed for AgentiLoop/Agent are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.