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Found 422 Skills
Parallel DAG-plan implementation skill. Reads a v-planning plan directory (root.md + step-<n>.md files), topologically schedules ready steps, and fans them out as parallel sub-agents. Use whenever the user invokes /v-implement, points at a plan directory produced by /v-plan, or asks to "run the parallel plan", "implement the DAG", or "fan out the steps" — even without those exact words. For linear plans (single .md file), use `implementing` instead.
Generate interactive TiddlyWiki-style HTML software manuals with screenshots, API docs, and multi-level code examples. Use when creating user guides, software documentation, or API references. Triggers on "software manual", "user guide", "generate manual", "create docs".
Spawn and manage multiple Codex CLI agents via tmux to work on tasks in parallel. Use whenever a task can be decomposed into independent subtasks (e.g. batch triage, parallel fixes, multi-file refactors). When codex and tmux are available, prefer this over the built-in Task tool for parallelism.
LangGraph state-machine design and debugging for `StateGraph`, node/edge routing, checkpoints, `interrupt`, and HITL flows. Use when building or troubleshooting graph-based agents with conditional edges and thread state.
Implementation agent that executes a single task and creates handoff on completion
Multi-agent orchestration workflow for deep research: Split a research objective into parallel sub-objectives, run sub-processes using Claude Code non-interactive mode (`claude -p`); prioritize installed skills for network access and data collection, followed by MCP tools; aggregate sub-results with scripts and refine them chapter by chapter, and finally deliver "finished report file path + summary of key conclusions/recommendations". Applicable scenarios: systematic web/data research, competitor/industry analysis, batch link/dataset shard retrieval, long-form writing and evidence integration, or scenarios where users mention "deep research/Deep Research/Wide Research/multi-agent parallel research/multi-process research".
Assess whether your product work is AI-first or AI-shaped. Score 5 competencies and recommend the next capability to build.
Collaborative multi-agent planning with iterative deliberation. Use when creating complex plans that benefit from multiple specialist perspectives, cross-review, and consensus-building through discussion rounds.
Agent skill for migration-plan - invoke with $agent-migration-plan
Agentic Workflow Pattern
Search conversation history and semantic memory to recall previous discussions, decisions, and context. Use when the user asks to "search memory", "what did we discuss", "remember when", "find previous conversation", "check history", or before starting work to recall prior decisions.
Enhance a plan with parallel research agents for each section to add depth, best practices, and implementation details