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Found 134 Skills
Vertical / parallel implementation planning skill. Creates DAG-structured plan directories where each step is an independent, QA-able vertical slice that sub-agents can pick up and implement in parallel. Use whenever the user wants a plan that fans out (multiple independent features), invokes /v-plan, or asks for a "parallel plan", "DAG plan", "vertical plan", or "plan that can be parallelized" — even if they don't say those exact words. Prefer the linear `planning` skill for strictly sequential work.
Hypothesis-driven deep research swarm. Spawns specialist sub-agents to investigate a task across codebase patterns, web sources, MCP tools, installed skills, and project dependencies — with evidence grading and adversarial challenge. Activates on: research, investigate, discover, deep research, how should I, what's the best way, explore options, analyze approaches, scout, prior art, feasibility.
This skill should be used when the user asks to "design multi-agent system", "implement supervisor pattern", "create swarm architecture", "coordinate multiple agents", or mentions multi-agent patterns, context isolation, agent handoffs, sub-agents, or parallel agent execution. Part of the context engineering skill suite — also activates when the user mentions "context engineering" or "context-engineering" in the context of orchestrating context across multiple agents.
Launch multiple sub-agents in parallel to execute tasks across files or targets with intelligent model selection, quality-focused prompting, and meta-judge → LLM-as-a-judge verification
Execute complex tasks through sequential sub-agent orchestration with intelligent model selection, meta-judge → LLM-as-a-judge verification
Novel outline/worldview/character design, applicable to user requests such as "Help me write a novel outline", "Design the protagonist's character", "Create a worldview setting", "Build a novel plot framework", "Write volume-specific detailed outlines", "Design novel characters for me", "Create a fantasy worldview", "Help me sort out the novel plot", "Novel character setting", "Write chapter-by-chapter outlines for novels", "Plan the arrangement of cool points", "Create novel character cards", "Build a novel world", etc. It generates complete worldviews, character cards, plot outlines, and cool point plans, with automatic compliance checks to avoid infringement risks. **When generating a large number of chapter detailed outlines, sub-Agents are used for parallel processing, and each Agent is responsible for at most 3 chapters' detailed outlines**
Propose and execute rubric or bucket upgrades. Two modes: **Full rubric bump** (highest-risk action, mandatory 5-step process + cross-model audit) and **--bucket-only lightweight recalibration** (only update bucket boundaries, no changes to rubric formulas). **Phase 2 mandates using cheat-score-blind sub-agent to re-score the calibration pool** — self-scored fallback is not accepted. Trigger phrases: "upgrade rubric"/"bump rubric"/"update formula"/"I want to add a dimension"/"adjust weights"/"recalibrate bucket"/"recalibrate bucket".
Only use this when the user requests to configure, check, test, repair, disable, or uninstall the DeepSeek native sub-Agent of Codex; do not trigger it for ordinary DeepSeek API issues or daily coding tasks after configuration.
Claude CLI sub-agent system for persona-based analysis. Use when piping large contexts to Anthropic models for security audits, architecture reviews, QA analysis, or any specialized analysis requiring a fresh model context.
Launch a sub-agent judge to evaluate results produced in the current conversation
Launch multiple sub-agents in parallel to execute tasks across files or targets with intelligent model selection and quality-focused prompting
Execute a task with sub-agent implementation and LLM-as-a-judge verification with automatic retry loop