Commandcode delegate
Delegate coding tasks to the Command Code CLI (`cmd`) only when the user explicitly requests it, while the orchestrator retains review and landing responsibility.
Skills for your AI
AI skills for AI & automation
Commit
ALWAYS use this skill when committing code changes — never commit directly without it. Creates commits following Sentry conventions with proper conventional commit format and issue references. Trigger on any commit, git commit, save changes, or commit message
Computer use agents
Build AI agents that interact with computers like humans do - viewing screens, moving cursors, clicking buttons, and typing text. Covers Anthropic's Computer Use, OpenAI's Operator/CUA, and open-source alternatives.
Computer vision expert
SOTA Computer Vision Expert (2026). Specialized in YOLO26, Segment Anything 3 (SAM 3), Vision Language Models, and real-time spatial analysis.
Conductor implement
Execute tasks from a track's implementation plan following TDD workflow
Conductor manage
Manage track lifecycle: archive, restore, delete, rename, and cleanup
Conductor new track
Create a new track with specification and phased implementation plan
Conductor revert
Git-aware undo by logical work unit (track, phase, or task)
Conductor setup
Configure a Rails project to work with Conductor (parallel coding agents)
Conductor status
Display project status, active tracks, and next actions
Conductor validator
Validates Conductor project artifacts for completeness, consistency, and correctness. Use after setup, when diagnosing issues, or before implementation to verify project context.
Context compression
When agent sessions generate millions of tokens of conversation history, compression becomes mandatory. The naive approach is aggressive compression to minimize tokens per request.
Context degradation
Language models exhibit predictable degradation patterns as context length increases. Understanding these patterns is essential for diagnosing failures and designing resilient systems.
Context driven development
Guide for implementing and maintaining context as a managed artifact alongside code, enabling consistent AI interactions and team alignment through structured project documentation.
Context engineering
Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.
Context fundamentals
Context is the complete state available to a language model at inference time. It includes everything the model can attend to when generating responses: system instructions, tool definitions, retrieved documents, message history, and tool outputs.
Context management context restore
Use when working with context management context restore
Context management context save
Use when working with context management context save
Context manager
Elite AI context engineering specialist mastering dynamic context management, vector databases, knowledge graphs, and intelligent memory systems.
Context optimization
Context optimization extends the effective capacity of limited context windows through strategic compression, masking, caching, and partitioning. The goal is not to magically increase context windows but to make better use of available capacity.
Context window management
Strategies for managing LLM context windows including summarization, trimming, routing, and avoiding context rot
Conversation memory
Persistent memory systems for LLM conversations including short-term, long-term, and entity-based memory
Convertkit automation
Automate ConvertKit (Kit) tasks via Rube MCP (Composio): manage subscribers, tags, broadcasts, and broadcast stats. Always search tools first for current schemas.
Copilot delegate
Delegate coding tasks to the GitHub Copilot CLI (`copilot`) only when the user explicitly requests it, while the orchestrator retains review and landing responsibility.