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Found 480 Skills
Execute Python code in isolated rootless containers with MCP server proxying for token-efficient agent workflows
poteto's agent style for concise, detailed responses, deliberate subagents, unslopped prose, simple code, and verified work. Use for poteto, /poteto-mode, or requests to work in this style.
Shared orchestration engine for the orch-* skill family. Defines the gated Research-Plan-TDD-Review-Commit pipeline, the size classifier, the agent map, and the two human gates that the orch-* operation skills delegate to. Not usually invoked directly.
Task management for session continuity. Use when coordinating multi-step work, managing subagent assignments, or preserving intent across compaction. Triggers on "track tasks", "manage work", "coordinate agents", or when complex work requires sequencing.
Choose and combine Eve storage primitives to give agents persistent memory — short-term workspace, medium-term attachments and threads, long-term org docs and filesystem. Use when designing how agents remember, retrieve, and share knowledge.
Identifies and manages execution dependencies between agent skills by analyzing their inputs and outputs. Use when building multi-step agent workflows to ensure skills are executed in the correct order and that all required data is available.
Break down a change into an implementation task checklist. Trigger: When the orchestrator launches you to create or update the task breakdown for a change.
Execute complete FPF cycle from hypothesis generation to decision
Curates insights from reflections and critiques into CLAUDE.md using Agentic Context Engineering
Turn any record into a shared workspace where agents and humans collaborate. Attach a simple workspace schema to any entity — contacts, companies, deals, projects, tickets — and let any participant contribute updates, tasks, notes, and issues. The record becomes the coordination. No orchestrator, no message bus — just read the workspace, do your work, record what you did. Intelligence accumulates. Use when multiple agents, humans, or systems need to work on the same entity together.
Ming Court Code —— Standardize Claude Code development processes using the institutional framework of the Ming Dynasty court. Three-level adaptive modes: Oral Edict (rapid execution), Court Debate (structured solution), Morning Court (multi-agent parallel processing).
Use this when you are exploring the codebase. It lets you ask the AI who wrote code questions about how things work and why they chose to build things the way they did. Think of it as asking the engineer who wrote the code for help understanding it.