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Found 34 Skills
Execute deployment through Makefile targets with ENV_MODE and optional VERSION overrides. Use when running real deployment or dry-run preview in Makefile-first workflow.
Use when the task requires operating exchanges with the ritmex-bot CLI, including capability checks, market/account/position queries, order operations, strategy run, dry-run simulation, and JSON output parsing.
Reddit community moderation via PRAW with LLM-powered report classification: fetch modqueue, classify reports against subreddit rules and author history, and take mod actions (approve, remove, lock). Supports interactive, auto, and dry-run modes.
Inject Call-to-Action blocks into Astro site content with intelligent placement strategies. Use when the user wants to add CTAs, newsletter signups, product promotions, or any content blocks to blog posts. Supports multiple placement strategies (end, after 50%, after 60%), content scoring for relevance, and dry-run preview.
Comprehensive toolkit for validating, linting, and testing Kubernetes YAML resources. Use this skill when validating Kubernetes manifests, debugging YAML syntax errors, performing dry-run tests on clusters, or working with Custom Resource Definitions (CRDs) that require documentation lookup.
Autonomously audit an LLM wiki (Karpathy pattern) for gaps, contradictions, orphans, and stale data, then research and fill high-priority gaps using quality-gated web research. Supports audit-only dry-run mode. Operates on a dedicated branch and commits changes for human review — never auto-merges. Use when the user asks to "lint my wiki", "self-heal my knowledge base", "find gaps in my wiki", "update my second brain", "auto-research my wiki", "run a health check on my LLM wiki", "audit my wiki without making changes", "dry run the lint", or wants to schedule periodic wiki maintenance.
Gemini-native Nano Banana image generation and editing across Nano Banana, Nano Banana 2, and Nano Banana Pro. Use when you need text-to-image, image-to-image edits, repeated local references, batch generation, dry-run request inspection, or a custom Gemini-compatible base URL such as a self-hosted gateway.
Debug and troubleshoot Helm deployment failures, template errors, and configuration issues. Covers helm template, helm lint, dry-run, debugging YAML parse errors, value type errors, and resource conflicts. Use when user mentions Helm errors, debugging Helm, template rendering issues, or troubleshooting Helm deployments.
Creation, editing, and review of RouterOS scripts (.rsc) with focus on idempotency, security, and best practices. Use when you need to generate, adjust, or import .rsc files for MikroTik: (1) create new configurations via script, (2) edit existing scripts with safe corrections, (3) review risks and execution policies, (4) validate with import dry-run and error handling.
Deploys agent skill collections from any GitHub repository with a /skills folder to one or more distribution surfaces: GitHub releases, Claude Code marketplace, VS Code plugin marketplace, and Copilot CLI plugin marketplace. Handles pre-flight validation, conventional commit analysis, version bumping across surface configs, and surface-specific publishing with dry-run support. Use when releasing, publishing, or deploying a skills collection to any supported marketplace or creating a GitHub release for a skills repository. Don't use for deploying non-skill packages, npm modules, Docker images, or Azure resources.
Interactively prune stale non-terminal workflows from the pipeline. Use when the user says 'prune workflows', 'clean stale workflows', 'pipeline cleanup', or runs /prune. Runs a dry-run preview, displays candidates with staleness and safeguard skips, prompts the user to proceed/abort/force, then bulk-cancels approved workflows with a workflow.pruned audit event. Safeguards skip workflows with open PRs or recent commits unless force is set.
Use bigquery CLI (instead of `bq`) for all Google BigQuery and GCP data warehouse operations including SQL query execution, data ingestion (streaming insert, bulk load, JSONL/CSV/Parquet), data extraction/export, dataset/table/view management, external tables, schema operations, query templates, cost estimation with dry-run, authentication with gcloud, data pipelines, ETL workflows, and MCP/LSP server integration for AI-assisted querying and editor support. Modern Rust-based replacement for the Python `bq` CLI with faster startup, better cost awareness, and streaming support. Handles both small-scale streaming inserts (<1000 rows) and large-scale bulk loading (>10MB files), with support for Cloud Storage integration.