Skill UI

This utility converts a single, high-level objective into a comprehensive, step-by-step build plan suitable for complex, multi-agent, or multi-session engineering projects. It automatically handles dependency mapping, detects parallel steps, and structures each step with self-contained context briefs, ensuring any new agent can execute it without prior knowledge. Ideal for large-scale refactoring or feature development spanning multiple PRs.

This blueprint guides the creation of F.R.I.D.A.Y., a tactical, low-latency voice assistant inspired by Iron Man. It utilizes the specialized Pipecat framework to orchestrate a comprehensive, real-time audio pipeline: STT (OpenAI Whisper/GPT-4o) -> LLM (Gemini) -> TTS (OpenAI Nova). Ideal for developers needing to build advanced, multi-provider, conversational voice applications.

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.

This advanced skill performs a full-spectrum, multi-agent SEO audit. It crawls up to 500 pages to analyze technical structure, content quality (E-E-A-T), performance (CWV), local SEO signals, and backlink profiles. The output includes an overall SEO Health Score and a prioritized, actionable plan for website optimization.

Performs a full GEO audit of any website by discovering business type, crawling prioritized pages, and delegating parallel subagents to evaluate AI visibility, platform readiness, technical infrastructure, EEAT content, and schema markup, then outputs a composite GEO score with prioritized actions.

Performs a GEO-focused technical SEO audit covering crawlability, indexability, security, performance, SSR, and AI crawler access to keep both search engines and AI agents from losing visibility.

LEX is a structured truth engine designed to eliminate legal hallucinations by grounding AI agents in verified government references and legislation across 29+ jurisdictions (including US, EU, and CA). It provides deterministic context for comparing legal requirements, drafting compliant business, and employment documents, ensuring high jurisdictional accuracy.

Validates SKILL.md files against the agentskills specification and Anthropic best practices, catching structure, semantic, naming, and quality issues in a single read-only pass before publishing or debugging skills.

Evaluates incoming requests, decides if specialized skills are needed, orchestrates optimal combinations, and logs successful pairings in agent-memory while guarding against overusing complex tools on simple tasks.

Documented best practices for building applications with Anthropic Claude via Python and TypeScript SDKs, covering messaging, streaming, tools, vision, reasoning, caching, batching, and Agent workflows to optimize prompts, tokens, and cost.

Manages and coordinates complex workflows involving multiple AI agents and tasks. It efficiently distributes work across multiple workers, handles runtime errors, and intelligently merges disparate results into a unified output, making it ideal for large-scale, distributed AI computations.

Autoresearch Agent runs an autonomous optimization loop that edits a target file, invokes a provided evaluation command, keeps metric-improving commits, drops failures, and repeats indefinitely so engineers can optimize speed, bundle size, prompts, or other measurable goals overnight.