Loading...
Loading...
Found 416 Skills
Enhance a plan with parallel research agents for each section to add depth, best practices, and implementation details
Implement approved OpenSpec proposal using DAG-scheduled multi-agent parallel execution
2-stage pipeline: trace (causal investigation) -> deep-interview (requirements crystallization) with 3-point injection
Resolve all pending CLI todos using parallel processing, compound on lessons learned, then clean up completed todos.
Comprehensive verification with parallel test agents. Use when verifying implementations or validating changes.
Orchestrates end-to-end autonomous AI research projects using a two-loop architecture. The inner loop runs rapid experiment iterations with clear optimization targets. The outer loop synthesizes results, identifies patterns, and steers research direction. Routes to domain-specific skills for execution, supports continuous agent operation via Claude Code /loop and OpenClaw heartbeat, and produces research presentations and papers. Use when starting a research project, running autonomous experiments, or managing a multi-hypothesis research effort.
Orchestrate subagent workflows for complex tasks that benefit from decomposition, role-based delegation, and parallel execution. Use when Codex should assemble a temporary team of subagents, choose roles from a reusable role library, create a controlled fallback role when no preset role fits, coordinate read-heavy work in parallel, or handle write-heavy work with ownership boundaries, staged execution, and an integrator-led merge path.
Run yourself in a loop with programmatic control via the Agent SDK. Use for long-running tasks like optimization, research, iterative improvement, multi-agent coordination, or any multi-step workflow where you need to repeat, branch, or track progress.
C-suite orchestration layer that routes founder questions to the right advisor role(s), triggers multi-role board meetings for complex decisions, synthesizes outputs, tracks decisions, and manages cross-functional alignment. Every C-suite interaction starts here. Use when coordinating executive decisions, routing strategic questions, managing board meetings, synthesizing multi-perspective advice, tracking decision history, resolving inter-department conflicts, or when user mentions chief of staff, orchestrator, c-suite coordinator, executive routing, board coordination, decision synthesis, advisor routing, multi-agent coordination, or strategic orchestration.
Aggressively clean up a codebase by removing AI slop, dead code, weak types, defensive over-engineering, duplication, and legacy cruft. Orchestrates 8 specialized subagents in parallel to deduplicate code, consolidate types, kill unused code, untangle circular dependencies, strengthen weak types, remove unnecessary try/catch, delete deprecated/legacy paths, and strip unhelpful comments. Use when the user asks to 'clean up the codebase', 'remove slop', 'improve code quality', 'remove dead code', 'kill AI slop', 'tighten types', 'remove legacy code', 'deduplicate code', 'DRY this up', 'untangle dependencies', or wants a thorough code quality pass. Also use when the user mentions code smells, technical debt cleanup, or refactoring for clarity — even if they don't use the word 'slop'.
Comprehensive map for multi-brain, orchestration, and agent governance. Triggers when users ask to 'view the orchestration ecosystem', 'how do agents work together?', 'multi-brain workflows', or 'give agents access'.
Creates and orchestrates multi-agent pipelines on the iii engine. Use when building AI agent collaboration, agent orchestration, research/review/synthesis chains, or any system where specialized agents hand off work through queues and shared state.