Web Search

Deep research that finds primary sources with named individuals, community sentiment from Reddit/HN/X, and news coverage. No summaries of summaries — actual quotes with URLs.

Debug microservices by enforcing end-to-end correlation (trace IDs, request IDs) and systematically locating propagation breaks or sampling gaps.

Have your Claw periodically check the AI Slop Wiki and build a living filter of patterns to avoid. Every piece of content your Claw creates runs through this filter first, so you never publish anything that reads like generic AI-generated filler.

A personal, local-first AI assistant that automates small daily tasks—organizing files, setting reminders, and monitoring system events—without touching sensitive data or taking risky actions without your approval.

Turn any development plan into a self-running pipeline. Build → Review → Security scan → Verify → Commit → Advance while you sleep — Kapilot handles each phase automatically and notifies you when it's done.

Daily monitoring of any Luma events page. Your Claw checks for new events, compares against what it saw yesterday, and alerts you when something new drops. Perfect for tracking community meetups, conferences, or any recurring event series.

Run a deep, no-sycophancy audit of your entire codebase and docs, dropping the results into docs/audits as a scorched-earth report. Dry humor included, crowd-pleasing strictly forbidden.

A research agent that tracks prior sessions and avoids redundant searches. It surfaces gaps in your existing knowledge base and picks up exactly where you left off.

Automate the daily flood of scientific papers by extracting the key ideas, methods, and conclusions so you can stay current in your field without reading everything yourself.

Too many papers, too little time, no reliable way to decide what to read next. This recipe builds a time-boxed, prioritized reading queue for any topic, project, or thesis chapter — with a built-in "rabbit-hole safe" capture channel for questions to research later.

GA4 is event-based and flexible—but teams often ship messy event names, missing parameters, and inconsistent conversions. This recipe audits your event taxonomy and produces a clean naming standard, a conversion map, and a QA checklist.