mergeiqScore the complexity of any GitLab MR or GitHub PR using a 4-dimension framework: Size (20%), Cognitive Load (30%), Review Effort (30%), and Risk/Impact (20%...
Install via ClawdBot CLI:
clawdbot install larryfang/mergeiqGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Calls external URL not in known-safe list
https://gitlab.com/api/v4/projects/PROJECT_ID/merge_requests/IID?include_diff_stUses known external API (expected, informational)
api.github.comAudited Apr 16, 2026 · audit v1.0
Generated Mar 21, 2026
A software development team uses MergeIQ to automatically score open pull requests by complexity before weekly review sessions. This helps them prioritize which PRs to tackle first, ensuring high-complexity changes get attention early and reducing bottlenecks in the deployment pipeline.
A fintech company integrates MergeIQ into their GitLab CI/CD pipeline to flag high-risk PRs involving security updates or regulatory changes. This triggers mandatory second reviews by senior engineers, ensuring compliance and minimizing vulnerabilities before merging.
An engineering manager sets up MergeIQ to generate weekly complexity trend reports for their team. By analyzing scores over time, they identify patterns in cognitive load and review effort, enabling data-driven decisions to improve code review processes and team efficiency.
A maintainer of a large open-source repository on GitHub uses MergeIQ to triage incoming pull requests from contributors. The tool helps quickly assess complexity, allowing them to delegate simpler changes to new contributors while focusing personal effort on high-impact, complex submissions.
A large enterprise with multiple development teams uses MergeIQ across GitLab and GitHub to build a centralized dashboard for engineering directors. This provides insights into complexity scores and dimension breakdowns, aiding in resource allocation and identifying teams that may need additional support.
Offer MergeIQ as a cloud-based service with tiered pricing based on the number of repositories or users. This model provides recurring revenue through monthly or annual subscriptions, appealing to teams seeking easy integration without managing infrastructure.
Sell on-premise licenses to large organizations that require data privacy and custom integrations. This includes support, training, and the ability to adjust scoring weights to align with internal engineering metrics, generating high-value contracts.
Provide a free version with basic complexity scoring for individual developers or small teams, while charging for advanced features like historical trend analysis, API access, and team dashboards. This drives user adoption and upsells to paid tiers.
💬 Integration Tip
Start by using the CLI tool with basic API calls to score a single PR, then integrate the Python library into existing CI/CD pipelines for automated complexity checks on every merge request.
Scored Apr 19, 2026
Interact with GitHub using the `gh` CLI. Use `gh issue`, `gh pr`, `gh run`, and `gh api` for issues, PRs, CI runs, and advanced queries.
Essential Git commands and workflows for version control, branching, and collaboration.
Git commits, branches, rebases, merges, conflict resolution, history recovery, team workflows, and the commands needed for safe day-to-day version control. U...
Query and manage GitHub repositories - list repos, check CI status, create issues, search repos, and view recent activity.
Advanced git operations beyond add/commit/push. Use when rebasing, bisecting bugs, using worktrees for parallel development, recovering with reflog, managing subtrees/submodules, resolving merge conflicts, cherry-picking across branches, or working with monorepos.
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