Reviews codebases, architectures, PRs, and technical plans for vanity engineering — code and systems built for the developer's ego, resume, or intellectual pleasure rather than delivering user or business value. Triggers on: "review this code", "is this over-engineered", "code review", "architecture review", "complexity audit", "vanity check", "is this necessary", "simplify this", "tech debt review", or any request to evaluate whether code or architecture is justified by actual requirements. Also trigger when the user shares a codebase and asks for feedback, when discussing framework/library choices, when reviewing PRs, or when someone is debating whether to refactor or rebuild. Nudge activation when you detect patterns of unnecessary abstraction, premature optimization, or resume-driven technology choices in code the user shares — even if they haven't asked for a vanity review.

Automate Asana tasks via Rube MCP (Composio): tasks, projects, sections, teams, workspaces. Always search tools first for current schemas.

Docker and Kubernetes patterns. Triggers on: Dockerfile, docker-compose, kubernetes, k8s, helm, pod, deployment, service, ingress, container, image.

Investigate production issues, query logs and metrics, and explore dashboards on the Mattermost Grafana instance at grafana.internal.mattermost.com.

Single entry point for all AEM as a Cloud Service Workflow skills. Covers workflow model design, custom process step and participant chooser development, launcher configuration, workflow triggering, and production support including debugging stuck/failed workflows, triaging incidents with Cloud Manager logs, thread pool analysis, and Sling Job diagnostics for the Granite Workflow Engine.

Adaptive thinking partner that helps clarify, challenge, and refine ideas through persistent questioning. Auto-detects domain (product, architecture, debugging, process, general) and user mode (exploring, deciding, refining) to adapt question style. Actively pushes back on weak reasoning — flags contradictions, challenges assumptions, stress-tests claims. Produces context-appropriate artifacts when done (design doc, hypothesis list, decision matrix, or key insights). Use this skill when: (1) brainstorming or exploring an idea before implementation, (2) requirements are vague and need clarification, (3) making architectural or product decisions, (4) debugging and need to form hypotheses, (5) refining an approach that's mostly decided. Triggers on: 'brainstorm', 'clarify', 'think through', 'explore', 'help me figure out', 'what should I consider', 'let's think about', 'what could go wrong', 'help me decide'.

Server-side Luzmo resource operations - CRUD, automation, and bulk API scripts. Use for listing, searching, creating, or deleting dashboards, datasets, themes, users, groups. Triggers on: "list all dashboards", "delete dataset", "bulk update", "automate", "script", "find resources". Critical: all deletes are irreversible and require explicit user confirmation before execution. Not for embedding saved dashboards/charts (use core), auth setup (use core), or data ingestion (use data-integration).

Create comprehensive, phased implementation plans with sprints and atomic tasks. Use when user says: "make a plan", "create a plan", "plan this out", "plan the implementation", "help me plan", "design a plan", "draft a plan", "write a plan", "outline the steps", "break this down into tasks", "what's the plan for", or any similar planning request. Also triggers on explicit "/planner" or "/plan" commands.

Implement Customer.io enterprise reference architecture. Use when designing integration layers, event-driven architectures, or enterprise-grade Customer.io setups. Trigger: "customer.io architecture", "customer.io design", "customer.io enterprise", "customer.io integration pattern".

Tune CodeRabbit review configuration: learnings, code guidelines, and noise reduction. Use when fine-tuning review quality, training CodeRabbit with team preferences, adding code guidelines, or reducing false positives. Trigger with phrases like "coderabbit tune reviews", "coderabbit learnings", "coderabbit guidelines", "reduce coderabbit noise", "coderabbit false positives".

Execute this skill should be used when the user asks about "how sprints work", "sprint phases", "iteration workflow", "convergent development", "sprint lifecycle", "when to use sprints", or wants to understand the sprint execution model and its convergent diffusion approach. Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.

Execute this skill should be used when the user asks about "writing specs", "specs.md format", "how to write specifications", "sprint requirements", "testing configuration", "scope definition", or needs guidance on creating effective sprint specifications for agentic development. Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.

Run ADR conformance checks, explain failures, and identify required ADR/doc updates for the current change.

AI-powered codebase security scanner that reasons about code like a security researcher — tracing data flows, understanding component interactions, and catching vulnerabilities that pattern-matching tools miss. Use this skill when asked to scan code for security vulnerabilities, find bugs, check for SQL injection, XSS, command injection, exposed API keys, hardcoded secrets, insecure dependencies, access control issues, or any request like "is my code secure?", "review for security issues", "audit this codebase", or "check for vulnerabilities". Covers injection flaws, authentication and access control bugs, secrets exposure, weak cryptography, insecure dependencies, and business logic issues across JavaScript, TypeScript, Python, Java, PHP, Go, Ruby, and Rust.

End-to-end test-fix workflow generate test sessions with progressive layers (L0-L3), then execute iterative fix cycles until pass rate >= 95%. Combines test-fix-gen and test-cycle-execute into a unified pipeline. Triggers on "workflow:test-fix-cycle".

Specification generator - 7 phase document chain producing product brief, PRD, architecture, epics, and issues with Codex review gates. Triggers on generate spec, create specification, spec generator, workflow:spec.

Your pathfinder for navigating unknown codebases. Investigates with precision, implements surgically, and never assumes — if it doesn't know, it says so. Maintains a .notebook/ knowledge base that grows across sessions, turning every discovery into lasting intelligence. Summons available skills, MCPs, and docs when the mission demands. Use when fixing bugs, implementing features, refactoring, investigating flows, or any development task in unfamiliar territory. Triggers on "fix this", "implement this", "how does this work", "investigate this flow", "help me with this code". Do NOT use for greenfield scaffolding, CI/CD, or infrastructure provisioning.

Router for the gstack skill suite. (gstack)

Z.AI CLI providing: - Vision: image/video analysis, OCR, UI-to-code, error diagnosis (GLM-4.6V) - Search: real-time web search with domain/recency filtering - Reader: web page to markdown extraction - Repo: GitHub code search and reading via ZRead - Tools: MCP tool discovery and raw calls - Code: TypeScript tool chaining Use for visual content analysis, web search, page reading, or GitHub exploration. Requires Z_AI_API_KEY.

This skill should be used to explain or reason about the foundational concepts of context engineering: what context is, the anatomy of a context window, how attention mechanics work, the U-shaped attention curve, why context quality matters more than quantity, and the mental models needed to interpret every other context-engineering decision. Use this for conceptual explanation, onboarding, and background reading. Route operational work to the specialized skills: debugging attention failures goes to context-degradation, token-efficiency work goes to context-optimization, conversation summarization goes to context-compression, and project-shape decisions go to project-development.