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Found 1,628 Skills
When you want to set up an agent loop, cron-scheduled task, or recurring workflow that runs autonomously in Claude Code. Judgment layer on top of ScheduleWakeup, CronCreate, and the /loop skill — decides whether to use dynamic pacing (self-scheduling wake-ups), cron scheduling (fixed intervals), or a one-shot loop; tunes delay to avoid the 5-minute cache-miss cliff; designs idempotent loop bodies; sets bail-out conditions so loops don't run forever. Examples of loops to loopify — weekly review pulse, daily brief generation, hourly monitoring of a metric, periodic vault compilation, upstream-check for an adapted skill, sponsorship-pipeline refresh, YouTube-transcript-batch-download, morning startup routine. Triggers on "/loopify," "set up a loop," "schedule this task," "run this daily," "run this weekly," "cron this," "make this recurring," "automate this on a schedule," "keep this running until X." Part of the -ify trifecta (skillify / toolify / loopify) for extending Claude Code. NOT for authoring a new skill — that's skillify. NOT for adding a tool/integration — that's toolify.
Use Agent Pulse to inspect local AI-agent activity across Hermes, Claude Code, Codex, DeepSeek, OpenClaw, Copilot, Aider, Qwen, OpenCode, Goose, Cursor, Antigravity, and Amp logs. Use when the user asks about AI-agent sessions, tokens, tool/search calls, model usage, estimated cost, budgets, forecasts, health checks, reports, setup diagnosis, web/API/metrics exports, or MCP integration.
Design and implement comprehensive evaluation systems for AI agents. Use when building evals for coding agents, conversational agents, research agents, or computer-use agents. Covers grader types, benchmarks, 8-step roadmap, and production integration.
Review Caveman Cloud evidence read-only: costs, Cave Score, Cave Plan, workflows, traces, latency, errors, compression, routing, and verified savings. Use when the user asks what Caveman found, where LLM spend goes, why cost or quality changed, which workflows need attention, or asks for a trace or analytics review. Prefer Caveman MCP tools; fall back to CLI JSON.
Wire the current repository through the Caveman Cloud gateway so every LLM request is measured — cost, tokens, latency — with zero behavior change. Use when the user pastes the Caveman setup prompt, says "set up caveman", or wants LLM spend observability added to an app. Requires the gateway URL and a Cave API key (the setup prompt carries both).
Use Agent Pulse to inspect AI agent activity, token usage, tool calls, model usage, cost, budgets, forecasts, reports, local log sources, health checks, and MCP tools. Use when the user asks to check how much AI agents have been used, what sessions ran, what models cost, whether spending is high, generate Agent Pulse reports, diagnose Agent Pulse setup, or expose Agent Pulse data to other agents.
MUST USE when investigating performance issues on a ClickHouse-managed Postgres instance. Provides an evidence-based RCA workflow that scrapes the Prometheus endpoint for system signal, pulls per-digest evidence from the Slow Query Patterns API, and recommends (does not apply) a fix.
Track aircraft and ships from public ADS-B and AIS feeds. Use when tracking a flight or tail number, following a vessel or IMO/MMSI, investigating aircraft or ship ownership, or analyzing movement patterns of a plane or boat.
Track aircraft and vessels from public ADS-B and AIS broadcasts using ADS-B Exchange, Flightradar24, FlightAware, MarineTraffic, VesselFinder and Equasis. Use when following a tail number or flight, looking up an ICAO 24-bit hex code, registration or callsign, tracing a ship by IMO number or MMSI, checking a flag of convenience or port-call history, investigating who owns a private jet or vessel, or analysing AIS gaps and dark-fleet behaviour.
Watch for the next dev/prod error or request in a Convex app and react to it.
Set up Sentinel production error capture in your own Convex deployment.
Query a running Convex app's logs + health in natural language (official MCP): failures, slow/expensive functions, deploy causality — scoped, evidence-backed, with a dashboard deep link.