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Managing Projects and Issues in Linear

ComposioHQ/awesome-codex-skills

This skill provides a comprehensive, structured workflow for managing projects, issues, and team workflows within the Linear platform. It supports natural-language project management, allowing users to perform tasks like sprint planning, bug triage, and workload balancing by interacting with the Linear MCP server and various specialized tools.

GitHub PR Triage and Digest

meta-github-pr-watch-digest

opensquilla/opensquilla

Automates the daily triage of GitHub Pull Requests, CI/CD failures, and new issues. It uses the GitHub API to pull relevant information, summarizes the findings into actionable buckets (e.g., needing review, awaiting action, CI failed), and persists follow-up notes to long-term memory for context retention. Ideal for keeping track of complex development workflows.

Structured IT Troubleshooting and Support Plan

meta-home-it-rescue

opensquilla/opensquilla

Designed for complex troubleshooting in home or small-team environments. This meta-skill orchestrates the entire process, guiding users through symptom intake, environment capture, external knowledge lookup, and generating a safe, step-by-step, and reversible repair plan for issues involving networks, Docker, Git, printers, and more.

Automated Issue to Pull Request Pipeline

meta-issue-to-pr-autopilot

opensquilla/opensquilla

This meta-skill automates the process of handling a GitHub issue by fetching context, delegating the fix to a sub-agent, summarizing the resolution, and finally opening a pull request (PR). It is best suited for small, well-scoped issues with clear acceptance criteria. This pipeline simulates a complete development workflow.

Stack Trace Error Investigator

meta-stack-trace-investigator

opensquilla/opensquilla

This meta-skill is designed to automate the diagnosis of complex programming errors. When presented with a stack trace, traceback, or failing log, it orchestrates a multi-step investigation. It parses the trace, searches the repository history, checks relevant issues, and analyzes code diffs to provide a comprehensive brief for root cause analysis and debugging.

Sentry Error Diagnosis and Triage

ComposioHQ/awesome-codex-skills

This tool automates the diagnosis of production errors tracked by Sentry. By leveraging the Composio CLI, it retrieves comprehensive issue details, full stack traces, breadcrumbs, and associated commits. It maps stack frames to local source code, allowing agents to propose fixes and triage issues directly, eliminating manual copy-pasting.

Go Stack Trace Debugging Probe

stack-trace-go-probe

opensquilla/opensquilla

An internal utility designed for deep investigation of Go panics and stack traces. It helps identify Go-specific issues, such as nil pointer dereferences or unhandled errors, by suggesting minimal reproducible `go test` commands and targeted patch locations for robust debugging.

Still Image to Animated Video Fallback

video-still-animator

opensquilla/opensquilla

This skill converts a single still image (PNG/JPG) into a short, animated MP4 video using a slow Ken-Burns zoom effect and a silent audio track. It is designed specifically as an 'on_failure' fallback mechanism for AI video generation steps that might fail due to content moderation or other upstream issues, ensuring a complete deliverable can still be produced for downstream merging.

Analyze and Optimize AWS Costs

aws-cost-optimize

github/awesome-copilot

This workflow systematically analyzes deployed AWS resources and Infrastructure-as-Code (IaC) definitions. It collects usage metrics from CloudWatch and Cost Explorer to identify over-provisioning, unused resources, and inefficient configurations (e.g., right-sizing EC2, S3 lifecycle policies). It generates actionable cost optimization recommendations and creates structured GitHub issues for tracking and implementing savings.

AWS Resource Health Diagnosis And Remediation

aws-resource-health-diagnose

github/awesome-copilot

This comprehensive workflow analyzes the health status of various AWS resources (EC2, Lambda, RDS, DynamoDB, etc.). It uses AWS CLI to diagnose potential issues by analyzing CloudWatch logs, metrics, and performance data. The process culminates in classifying root causes and generating actionable, tiered remediation plans (Immediate, Short-term, Long-term) to ensure system resilience and stability.

AWS Well-Architected Framework Review

aws-well-architected-review

github/awesome-copilot

This workflow automates the AWS Well-Architected Framework (WAF) review. It scans Infrastructure as Code (IaC) files (Terraform, CloudFormation, CDK) and deployed AWS resources against 6 pillars (Security, Reliability, etc.). It identifies risks, generates detailed findings, and automatically creates trackable GitHub issues for remediation, ensuring adherence to industry best practices.

Standardize Power BI Naming Conventions

standardize-naming-conventions

data-goblin/power-bi-agentic-development

An interactive workflow for auditing and standardizing naming conventions (tables, columns, measures) in Power BI semantic models (TMDL). It ensures names are human-readable, consistent, and aligned with core business terminology, addressing technical issues like abbreviations, mixed casing, and inappropriate technical prefixes.

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