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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.

Knowledge Base Bootstrap Pipeline

meta-knowledge-base-bootstrap

opensquilla/opensquilla

This meta-skill provides a complete pipeline to bootstrap a domain knowledge base from any single seed input (URL, PDF, Git repository, or free text). It automatically classifies the source type, ingests the content using a multi-search engine, persists the summary to memory, and finally generates a structured XLSX index file, making the information immediately searchable and usable.

Meeting Notes to Actionable Workflow

meta-meeting-to-workflow

opensquilla/opensquilla

This meta-skill converts messy meeting inputs—such as transcripts, rough notes, or recordings—into highly structured, actionable outputs. It automatically extracts key decisions, assigns owners, generates follow-up tasks, and creates drafts for popular collaboration platforms like GitHub, Trello, or Notion, ensuring continuity from discussion to execution.

Automated PR Review and CI Auto-Fix

pr-review-ci-fix

ComposioHQ/awesome-codex-skills

Use the Composio CLI to automate the entire Pull Request review and Continuous Integration (CI) triage process for GitHub and GitLab. This tool fetches code diffs, analyzes failure logs, posts detailed inline review comments, and iteratively patches and re-runs CI checks until the code passes, significantly enhancing code quality and developer efficiency.

Install AI Skills From GitHub Repos

skill-installer

ComposioHQ/awesome-codex-skills

A utility for managing and installing specialized AI skills into the Codex environment. It supports fetching curated skills from predefined sources (like openai/skills) or installing custom capabilities directly from any GitHub repository, including private ones. It handles listing available skills, installing specific modules, and provides robust fallback methods (download/git sparse checkout).

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 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.

Find Similar Japanese NLP Resources

similar-resources

taishi-i/awesome-japanese-nlp-resources

This skill helps users discover alternatives, equivalents, or related tools/models/datasets for a specified Japanese NLP resource (GitHub repo, Hugging Face model, or tool). It first checks a bundled dataset and then expands the search via web research across GitHub and Hugging Face, providing a comprehensive list of related resources.

Power BI Project Development Format

data-goblin/power-bi-agentic-development

PBIP is the developer-mode file format for Power BI, transforming the opaque PBIX binary into a human-readable, folder-based structure. This structure is crucial for enabling robust source control (Git diffing), external editing using specialized tools like VS Code, and seamless multi-author collaboration. It standardizes how reports and semantic models are structured for professional BI development pipelines.

AI Collaboration Evidence Analyzer

alirezarezvani/claude-skills

This advanced tool surfaces critical, often unrecorded, evidence of human-AI collaboration during development sessions. It analyzes git diffs and conversational context across multiple layers to classify the signal level (HIGH/MEDIUM/LOW), measure technical complexity, detect decision forks, and quantify the specific contribution of the AI model, providing structured data for post-session retrospectives and accountability.

Verify Agent Claims Against Ground Truth Evidence

dos-verify-done-claims

sickn33/antigravity-awesome-skills

This skill provides a deterministic, git-only method to verify claims made by AI agents (e.g., 'done', 'shipped', 'fixed'). Instead of trusting the agent's self-report, it audits the commit's diff and git history using the DOS kernel (`dos verify`, `dos commit-audit`) to confirm if the claimed change genuinely occurred and is backed by non-forgeable evidence. It acts as a critical quality gate.

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