grill-with-docs

Discover and install specialized agent skills from the open ecosystem when users need extended capabilities. Helps identify relevant skills by domain and task when users ask "how do I do X" or "find a skill for X" Provides npx skills find [query] command to search interactively and npx skills add <package> to install from GitHub or other sources Recommends skills based on install count (prefer 1K+), source reputation (official sources like Vercel, Anthropic), and GitHub stars to ensure quality Checks the skills.sh leaderboard first for battle-tested, popular options before running CLI searches

Relentless interviewing skill that stress-tests plans and designs through systematic questioning. Conducts deep-dive questioning across all aspects of a plan, walking through decision trees branch-by-branch until shared understanding is reached Automatically explores the codebase to answer questions where code context is available, reducing redundant back-and-forth Designed for design reviews, architecture validation, and pre-implementation planning where thorough vetting prevents downstream issues

Fast, persistent browser automation with session continuity across sequential agent commands. Supports three browser modes: headless Chromium, real Chrome with profile support, and cloud-hosted remote browsers with proxy configuration Includes 15+ command categories covering navigation, page inspection, interactions, data extraction, cookie management, and JavaScript execution Offers cloud session management, local server tunneling via Cloudflare, and parallel subagent execution through remote sessions Built-in Python integration for setting variables, accessing the browser object, and running scripts within the automation context

Analyze codebases for architectural friction and propose module-deepening refactors as testability improvements. Explores codebases organically to surface shallow modules, tightly-coupled components, and untested seams rather than following rigid heuristics Applies John Ousterhout's "deep module" principle: small interfaces hiding large implementations for better testability and AI navigability Generates multiple radically different interface designs (minimalist, flexible, caller-optimized, ports & adapters) via parallel sub-agents, then recommends the strongest approach Creates GitHub issue RFCs documenting the problem space, design trade-offs, and refactoring rationale