Provides concrete guidance on building terminal emulators in Swift using SwiftTerm, including configuring terminal views, parsing ANSI/VT100 escape sequences, managing PTY connections, and optimizing text rendering performance. Use when the user is building a terminal app, console view, or xterm-compatible emulator in Swift, integrating SwiftTerm into a SwiftUI or UIKit/AppKit app, working with PTY or SSH stream bridging, handling keyboard input and escape sequences, or optimizing terminal rendering on macOS, iOS, or visionOS.

Reviews contracts for compliance issues, drafts and audits privacy policies, assesses GDPR/CCPA/HIPAA/SOX/PCI-DSS obligations, identifies regulatory requirements, and flags legal risks across multiple jurisdictions. Use when the user asks about legal compliance, regulatory requirements, GDPR, CCPA, privacy policies, terms of service, contract review, data protection, data handling, legal review, or industry-specific regulations such as HIPAA, SOX, or PCI-DSS.

Drives a multi-turn conversation with a LiveKit agent running locally to see what it does. Use when the user says "test my agent", "try my agent", "does this work", "why did it call that tool", "it says the wrong thing when I ask X", "test this change", or whenever you have edited an agent and need to check how it behaves. Wraps `lk agent debugger`: start the agent in text mode, send turns, read the tool calls, handoffs, errors and logs behind each reply, and restart after an edit. It runs without audio or a LiveKit room at one LLM call per turn, so it is the preferred way for a coding agent to live-test during development, and the default when the user says "test" without naming unit tests or simulations.

Builds voice and chat AI agents with LiveKit Agents and LiveKit Cloud. Use when the user asks to "build a voice agent", "create a LiveKit agent", "add voice AI to my app", "implement handoffs", "structure an agent workflow", "my agent is slow / too chatty", "it says it booked but nothing was saved", "make it confirm before committing", "it keeps re-asking things the caller already said", or is writing code against the LiveKit Agents SDK. Covers architecture: designing for latency, keeping context small, splitting a monolithic agent into handoffs and tasks, and designing for voice. Also covers keeping the model in charge of meaning while code owns state, approvals, and effects. For API specifics use reading-livekit-docs. To check behavior use debugging-livekit-agents and testing-livekit-agents.

Use when authoring, creating, refining, or troubleshooting agent skills — scaffold SKILL.md and frontmatter, write and optimize the trigger description, structure the body with progressive disclosure, validate structure, and test or debug activation. Also when building a new skill from scratch, when a skill won't trigger, loads incorrectly, or the agent ignores it entirely. Use when a skill misbehaved in the current session and needs adjustment based on learnings.

Review a Confluent agent skill in this repo against the Agent Skills spec (agentskills.io), Confluent conventions in CLAUDE.md, the PR template gates, and the evals-as-contract rule. Use this skill whenever the user asks to review, audit, validate, or lint a skill; opens or inspects a PR that adds or modifies anything under `skills/`; asks about spec conformance, lazy-loading, frontmatter shape, trigger overlap, or eval coverage; or wants a pre-merge sanity check on skill changes. Do NOT trigger for general code review of application code; security review; auditing schemas, producer/consumer configs, PII tagging, or Terraform generation for Schema Registry (handled by `kafka-schema-registry`); runtime/log analysis of skill behavior (use `tools/skill_review_dashboard.py`); or any changes that don't touch the `skills/` tree.

Query the OpenAI developer documentation via the OpenAI Docs MCP server using CLI (curl/jq). Use whenever a task involves the OpenAI API (Responses, Chat Completions, Realtime, etc.), OpenAI SDKs, ChatGPT Apps SDK, Codex, MCP integrations, endpoint schemas, parameters, limits, or migrations and you need up-to-date official guidance.

This skill should be used when the user asks to "investigate issue", "investigate

Audit Google Ads measurement, Search, Shopping, Performance Max, Demand Gen, YouTube-linked inventory, keywords and search terms, negative-keyword generation or review, creative assets, bidding, budgets, settings, and policy. Use for Google Ads, AdWords, Search campaigns, search terms reports, broad negatives, Shopping, Performance Max, PMax, Demand Gen, GAQL, Google conversion tracking, or Google campaign optimization.

Reviews and improves Claude Code skills against official best practices. Supports three modes - self-review (validate your own skills), external review (evaluate others' skills), and auto-PR (fork, improve, submit). Use when checking skill quality, reviewing skill repositories, or contributing improvements to open-source skills.

libllm - LLM API client for OpenAI-compatible endpoints. LlmApi class handles chat completions and embeddings via HTTP. Supports GitHub Models, Azure OpenAI, and standard OpenAI endpoints. Handles streaming responses, token counting, and multi-tool parallel call fixes. Use for LLM completions, embeddings, and AI model integration.

Use when the user has an idea for an app, tool, or feature and wants to be interviewed in depth first — answering structured clarifying questions until the requirements are fully pinned down — before it gets built end-to-end. Triggers - "ask me questions then build", "interview me about my idea", "help me spec this out and build it", vague ideas the user wants to shape interactively.

Use for Vercel cost and performance optimization on deployed projects, especially Next.js, SvelteKit, Nuxt, and limited Astro apps. Collect Vercel metrics, usage, project config, and code scan results first; investigate only metric-backed candidates; produce ranked recommendations grounded in verified files and version-aware Vercel/framework docs. Trigger for Vercel bill reduction, slow or expensive routes, caching opportunities, Function Invocations, Build Minutes, Fast Data Transfer, Core Web Vitals, Bot Management, Fluid compute, or cost breakdown requests.

Use when someone wants to find a recorded Paper session, theirs or anyone's in the org — "did anyone work on X", "find the session where…", "search paper sessions", "which session was that", "pull up that agent run" — or to browse sessions by time, author, or harness when there is no phrase to search. Covers `paperctl search` and `paperctl sessions` over recorded sessions (tapes).

Utility tools via uni CLI. Use when user wants weather, stock prices, currency conversion, QR codes, or URL shortening. Services: weather, stocks, currency, qrcode, shorturl.

uni CLI overview and meta commands. Use for general uni questions, multi-command execution (uni run), saved flows, natural language (uni ask), plugins, config, aliases, history. For specific services, use their dedicated skills (uni-wa, uni-telegram, uni-google, etc.)

Use when parallelizing development, running multiple agents, splitting work across agents, coordinating parallel tasks, or decomposing PRDs for concurrent execution. Breaks work into independent agent workstreams.

Reference for configuring tool permissions when launching Claude Code agents. Use when setting up --allowedTools flags, restricting file access, or configuring agent permissions.

Inspect a Kotlin + Spring repository before making changes or answering implementation, debugging, build, architecture, or review questions. Use when the agent must map modules, Spring Boot/Kotlin/Gradle/JDK versions, compiler plugins, profiles, dependencies, runtime stack, and architectural boundaries so later advice stays compatible with the real project.

Turn Notion specs into implementation plans, tasks, and progress tracking; use when implementing PRDs/feature specs and creating Notion plans + tasks from them.