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Found 33 Skills
Command a Royal Navy agent squadron from sailing orders through execution and stand-down. Use when work can be parallelized, requires tight coordination, or needs explicit action-station controls, quality gates, and a final captain's log.
This skill should be used when the user asks to "implement a feature in an isolated worktree", "create a worktree from the current project branch", "open a PR from worktree changes", "merge feature PRs into main", "run multiple agents in parallel worktrees", or "handle worktree merge conflicts and incompatibilities".
AI agents as force multipliers for quality work. Core skill for all 19 QE agents using PACT principles.
Master context engineering for AI agent systems. Use when designing agent architectures, debugging context failures, optimizing token usage, implementing memory systems, building multi-agent coordination, evaluating agent performance, or developing LLM-powered pipelines. Covers context fundamentals, degradation patterns, optimization techniques (compaction, masking, caching), compression strategies, memory architectures, multi-agent patterns, LLM-as-Judge evaluation, tool design, and project development.
Agent orchestration patterns for agentic loops, multi-agent coordination, alternative frameworks, and multi-scenario workflows. Use when building autonomous agent loops, coordinating multiple agents, evaluating CrewAI/AutoGen/Swarm, or orchestrating complex multi-step scenarios.
Invoke for complex multi-step tasks requiring intelligent planning and multi-agent coordination. Use when tasks need decomposition, dependency mapping, parallel/sequential/swarm/iterative execution strategies, or coordination of multiple specialized agents.
Decompose complex tasks, design dependency graphs, and coordinate multi-agent work with proper task descriptions and workload balancing. Use this skill when breaking down work for agent teams, managing task dependencies, or monitoring team progress.
Dispatch independent subagents in parallel for unrelated problems spanning different subsystems. Use when 2+ failures have independent root causes, multiple subsystems are broken independently, or user requests concurrent investigation. Use for "parallel", "multiple failures", "independent bugs", "fix these concurrently". Do NOT use for related failures, shared-state problems, or exploratory debugging where root cause is unknown.
Agent skill for swarm-pr - invoke with $agent-swarm-pr
Enterprise session state management, token budget optimization, runtime tracking, session handoff protocols, context continuity for Claude Sonnet 4.5 and Haiku 4.5 with context awareness features
Set up and improve harness engineering (AGENTS.md, docs/, lint rules, eval systems, project-level prompt engineering) for AI-agent-friendly codebases. Triggers on: new/empty project setup for AI agents, AGENTS.md or CLAUDE.md creation, harness engineering questions, making agents work better on a codebase. ALSO triggers when users are frustrated or complaining about agent quality — e.g. 'the agent keeps ignoring conventions', 'it never follows instructions', 'why does it keep doing X', 'the agent is broken' — because poor agent output almost always signals harness gaps, not model problems. Covers: context engineering, architectural constraints, multi-agent coordination, evaluation, long-running agent harness, and diagnosis of agent quality issues.
Reference guide for Agentica multi-agent infrastructure APIs