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Found 6,554 Skills
Implement Syncfusion React Scheduler component for calendar, event scheduling, and appointment management. Use this when building scheduling systems, calendar applications, booking systems, or time management interfaces. Covers all scheduler views (Day, Week, Month, Timeline, Agenda, Year), data binding, resource scheduling, recurring events, CRUD operations, drag-and-drop scheduling, customization, accessibility, and advanced features.
Scoring formulas and analytical frameworks for GitHub workflow agents. Covers repository health scoring (0-100, A-F grades), priority scoring for issues/PRs/discussions, confidence levels for analytics findings, delta tracking (Fixed/New/Persistent/Regressed), velocity metrics, contributor metrics, bottleneck detection, and trend classification. Use when computing scores, tracking remediation progress, building prioritized dashboards, or detecting workflow bottlenecks.
Guides the agent through Capgo OTA release workflows including bundle uploads, compatibility checks, channels, cleanup, and encryption key setup. Use when managing Capgo bundle and channel operations. Do not use for native build requests or organization administration.
Guides the agent through upgrading a Capacitor plugin from v6 to v7. Use when the plugin targets Capacitor 6 and needs the v7 migration path. Do not use for app upgrades, other major versions, or non-Capacitor plugins.
Manages persistent Knowledge Graph for specifications. Caches agent discoveries and codebase analysis to remember findings across sessions. Validates task dependencies, stores patterns, components, and APIs to avoid redundant exploration. Use when: you need to cache analysis results, remember findings, reuse previous discoveries, look up what we found, spec-to-tasks needs to persist codebase analysis, task-implementation needs to validate contracts, or any command needs to query existing patterns/components/APIs.
Autonomously optimize an existing AI skill by running it repeatedly against binary evals, mutating one instruction at a time, and keeping only changes that improve pass rate. Based on Karpathy-style autoresearch, but applied to SKILL.md iteration instead of ML training. Use when optimizing a skill, benchmarking prompt quality, building evals for a skill, or running self-improvement loops on reusable agent instructions. Triggers on: skill-autoresearch, optimize this skill, improve this skill, benchmark this skill, eval my skill, run autoresearch on this skill, self-improve skill.
Manage AI coding agents on a visual Kanban board. Run parallel agents through a To Do→In Progress→Review→Done flow with automatic git worktree isolation and GitHub PR creation.
Multi-agent swarm orchestration where AI agents spawn, coordinate, and self-organize into collaborative teams. Use when running parallel AI agent tasks, orchestrating multi-agent workflows across Claude Code / Codex / Cursor / custom agents, isolating agent workspaces via git worktrees, tracking task dependencies across agents, or running autonomous experiments. Triggers on: clawteam, agent swarm, spawn agents, multi-agent team, agent orchestration, parallel agents, agent coordination, swarm intelligence, agent spawn, clawteam spawn, agent worktree, agentic team, ml agent experiments, autonomous agents, agent team.
Use chat rooms through the Paseo CLI. Use when the user says "chat room", "room", "coordinate through chat", "shared mailbox", or wants agents to communicate asynchronously.
Senior Multi-Agent Systems (MAS) Architect for 2026. Specialized in Model Context Protocol (MCP) orchestration, Agent-to-Agent (A2A) communication, and recursive delegation frameworks. Expert in managing complex task handoffs, shared memory state, and parallel subagent execution for high-autonomy engineering missions.
Test-Driven Development enforces the RED-GREEN-REFACTOR discipline on every code change an agent produces.
Use when the agent wants to define, list, inspect, or execute GUI macros via the OpenClaw Macro System CLI. Macros are parameterized, CLI-callable workflows — the agent invokes `macro run <name>` and the system handles backend routing (plugin, file transform, accessibility, compiled GUI replay).