Skill UI

Automates creating a post-mortem doc, scheduling a review meeting, and notifying the team via Google Chat so incident reviews are centralized and timely.

Audit Google Meet attendance by listing recent conferences, participants, and session durations using the `gws meet` commands to confirm who joined and for how long.

Identify past-due Google Tasks via gws commands so items needing attention are surfaced quickly. The recipe lists task lists, filters for active tasks, and reviews due dates to spotlight and prioritize overdue work.

Automate creation of recurring Google Calendar meetings with attendees via the gws calendar CLI, then review upcoming slots using the agenda view.

Automates sharing a Google Docs file with editor access and immediately notifies collaborators via Gmail, ensuring team members can review or edit the document without manual permissions or email composition.

This meta-skill provides a comprehensive guide through the entire software development lifecycle (SDLC). It teaches senior-level engineering discipline, covering everything from vague idea refinement and specification design to planning, implementation, testing, code review, and deployment. It emphasizes core behaviors like surfacing assumptions, managing ambiguity, maintaining scope discipline, and enforcing technical simplicity.

Deploy applications or static sites to Vercel instantly via a script that packages your project, auto-detects frameworks, uploads artifacts, and returns preview and claim URLs without requiring authentication.

Guides multi-axis reviews before merging, checking correctness, readability, architecture, security, and performance while enforcing concise change sizing and descriptive commit messaging to keep PR history clear.

Streamlines the process of providing code review feedback by enforcing a highly structured, ultra-compressed format. It guides users to cut through noise and deliver actionable, single-line comments (Location: Problem. Fix.) while maintaining critical context like severity and technical rationale. Ideal for team settings prioritizing efficiency and high code quality.

Behavioral guidelines for writing, reviewing, and refactoring code with LLMs, emphasizing minimalism, clear assumptions, surgical edits, and verifiable success criteria to avoid common machine-assisted coding mistakes.

Guides configuring HTTP/HTTPS, SNMP, and SMB services plus verification and log review for penetration testing labs using Windows or Linux hosts.

This skill provides robust mechanisms to verify the integrity of AI agent plugins, tools, and dependencies. It generates deterministic SHA-256 manifests (INTEGRITY.json) for all components, allowing users to detect unauthorized modifications, track provenance, and ensure that deployed assets match their published versions. Use this during CI/CD pipelines, code review, and pre-production promotion to secure the entire agent ecosystem.