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Optimizing AI Context Window FinOps

geminiignore-finops

sickn33/agentic-awesome-skills

This skill guides the creation and maintenance of a `.geminiignore` file. By systematically filtering out machine-generated noise—such as build artifacts, dependency lock files, logs, and caches—it significantly optimizes the AI agent's context window. This process improves processing speed and, critically, reduces token consumption costs (FinOps).

GitHub Actions Pipeline Debugger

github-actions-debugger

sickn33/agentic-awesome-skills

A specialized diagnostic skill designed to analyze failing GitHub Actions workflow logs. It identifies the root cause of crashes, such as missing secrets, environment mismatches, or deprecated syntax. The output provides precise YAML or code diffs required to fix the pipeline and optimize CI/CD processes.

Apple HIG Presentation Components

hig-components-dialogs

sickn33/agentic-awesome-skills

Provides Apple Human Interface Guidelines for presentation components like alerts, action sheets, popovers, sheets, and digit entry views. Helps choose the right modal presentation, craft concise alert text, and adapt to platform conventions.

Grafana Loki Log Aggregation

sickn33/agentic-awesome-skills

This skill covers configuring Grafana Loki for log aggregation and analysis within DevOps environments. It includes setting up Promtail for log shipping, deploying via Docker or Kubernetes, and writing LogQL queries for filtering. Ideal for replacing ELK stacks with a lighter-weight solution for monitoring application and system logs.

Make Scenario Automation and Monitoring

make-automation

sickn33/agentic-awesome-skills

A powerful tool utilizing Rube MCP to automate interactions with Make (formerly Integromat) scenarios. It allows users to retrieve detailed operation logs, monitor usage data, and validate critical configuration parameters such as supported languages and timezones. Ideal for building comprehensive workflow monitoring dashboards and ensuring the integrity of complex integration pipelines.

Semantic Memory for AI Agents

sickn33/agentic-awesome-skills

A self-hosted, semantic memory service designed for AI agents. It allows agents to save worklogs, decisions, and notes, and recall this knowledge across sessions based on meaning rather than exact keywords. Using pgvector and structured workspaces, it maintains persistent, context-aware knowledge bases, making it ideal for collaborative AI projects.

Push Metadata and Logs to Monte Carlo

monte-carlo-push-ingestion

sickn33/agentic-awesome-skills

An expert agent designed to collect critical data assets—including metadata, data lineage, and query logs—from any data warehouse platform. It uses the push ingestion API to send this data directly to Monte Carlo. This method is essential for integrating data sources that cannot be reliably covered by standard pull collectors, such as custom lineage paths or historical query logs.

Configure Object Storage Solutions

sickn33/agentic-awesome-skills

This skill covers configuring and managing object storage solutions like AWS S3, MinIO, and GCS. It includes CLI operations for bucket management, uploading/downloading files, setting up versioning, implementing bucket policies for access control, and configuring lifecycle rules for cost optimization. Suitable for DevOps engineers managing application assets, backups, logs, and media files in cloud or on-premises environments.

Odoo Shopify Data Sync

odoo-shopify-integration

sickn33/agentic-awesome-skills

This skill enables seamless integration between Odoo and Shopify platforms. It guides users to synchronize product catalogs, real-time inventory levels, incoming orders, and customer data. The process covers using official Odoo connectors or building custom integrations via Shopify REST and Odoo XMLRPC APIs, including webhook implementation and Python code snippets for automation.

OpenTelemetry Observability Implementation

sickn33/agentic-awesome-skills

Implement vendor-neutral observability using OpenTelemetry standards for traces, metrics, and logs. Configure collectors, set up Kubernetes deployments, and instrument Python services. Supports Prometheus, Jaeger, and Loki backends. Essential for unified monitoring in microservices and infrastructure environments.

Progressive Estimation for AI-Assisted Projects

progressive-estimation

sickn33/agentic-awesome-skills

This skill provides sophisticated project estimation by adapting to human-only, hybrid, or agent-first development modes. It uses research-backed PERT statistics and confidence bands (P50, P75, P90) to forecast development timelines for tasks, backlogs, and capacity planning. It continuously calibrates estimates based on actual completion data, ensuring accuracy in AI-assisted and hybrid development environments.

Structured Data Schema Generator

schema-markup-generator

sickn33/agentic-awesome-skills

This skill generates robust JSON-LD structured data markup for various web components, including blogs, FAQs, tools, and SaaS pages. By implementing standard Schema.org types (WebSite, Article, FAQPage, etc.), you can significantly improve your SEO, boost click-through rates (CTR), and provide clear context to both search engines and AI systems. Includes implementation guidance for modern frameworks like Next.js.

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