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Claude Code agent generation system that creates custom agents and sub-agents with enhanced YAML frontmatter, tool access patterns, and MCP integration support following proven production patterns
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Generate multiple radically different interface designs for a module using parallel sub-agents. Use when user wants to design an API, explore interface options, compare module shapes, or mentions "design it twice".
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Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes — Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/PRD asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".
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Make 100 versions of Claude fight to the death over one task. Spins up N sub-agents (default 100, --quick for 16), gives every one the exact same task plus a different strategy card (reasoning mode, workflow, strategy), then runs a single-elimination bracket: they attack each other's solutions, defend and revise, and a judge scores every match on a written rubric until one solution survives. Use when the user is not satisfied with an answer, calls it a bad answer, says try again or do better, says "arena", or asks to make them compete.
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多视角深度分析。用多个 Sub-agent 分别扮演不同思维框架的顾问，对同一份素材做独立分析，然后交叉汇总共识与分歧，产出结构化诊断报告。当用户说"帮我多视角分析"、"多维分析"、"用多个视角看看"、"帮我诊断一下"时触发。
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Autonomous cold email campaign launcher. Takes one target company domain, scrapes their website, generates an ICP with Claude, pulls matching leads via Prospeo, enriches emails + company descriptions, personalizes each lead with parallel Claude Code Task sub-agents (A/B/C variants), and uploads as a live Smartlead campaign. Uses local JSON files for state (no database required). Use for automated daily campaign launches after you have an initial `client-profile.yaml` from /icp-onboarding. Triggers on "auto-research", "launch an automated campaign", "daily campaign", "run the research loop".
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Interactive loop that builds and tunes an AI prompt for evaluating whether a company fits a client's ICP. Run after any list-building skill (disco-like, blitz-list-builder, google-maps-list-builder, prospeo-full-export) to qualify companies before scaling. Iterates batches of 10 companies with user feedback, stops when 2 consecutive rounds have zero corrections, saves the final prompt for reuse. Always uses Claude Code Task sub-agents — never an external API key.
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Capify an existing project. Scans the repo for already-installed MCP servers, skills, rules, hooks, sub-agents, and plugins (across .claude, .cursor, .codex, .gemini, etc.), consolidates them into shared top-level directories (skills/, rules/, hooks/), and synthesizes a sound capabilities.yaml from the inventory. Use whenever the user says "bootstrap capa", "capify this project", "onboard capa onto an existing repo", "inventory my agent setup", or asks how to turn an ad-hoc Claude/Cursor/Codex configuration into a capabilities file. Use even when the user only mentions one provider — discovery should still sweep all of them.
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Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes — Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/PRD asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".
中文简介正在准备中。当前显示原文说明。
Generate multiple radically different interface designs for a module using parallel sub-agents. Use when user wants to design an API, explore interface options, compare module shapes, or mentions "design it twice".
中文简介正在准备中。当前显示原文说明。
Braintrust tracing for Claude Code - hook architecture, sub-agent correlation, debugging
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Cut token usage across the whole session without losing correctness or substance — concise user replies, lean tests/docs/plans/comments, tight code, disciplined context and tool use, and cheap sub-agent delegation. Load when the user wants less verbosity, lower cost, fewer tokens, or a "token diet" / "lean mode"; also triggered by /token-diet or "token diet on".
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This skill should be used when designing or implementing systems with multiple AI agents that coordinate to accomplish tasks. Triggers on "multi-agent", "orchestrator", "sub-agent", "coordination", "delegation", "parallel agents", "sequential pipeline", "fan-out", "map-reduce", "spawn agents", "agent hierarchy".
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Run the code and documentation simplification passes together over one scope, launching every review sub-agent concurrently before applying a single round of fixes. Use when the user asks to "simplify all", "simplify everything", "simplify code and docs", "clean up code and docs", "run both simplify skills", or "simplify code and docs in parallel".
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Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes: Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/spec asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".
中文简介正在准备中。当前显示原文说明。
Generate multiple radically different interface designs for a module using parallel sub-agents. Use when user wants to design an API, explore interface options, compare module shapes, or mentions "design it twice".
中文简介正在准备中。当前显示原文说明。
This skill should be used when the user wants to file their tax return electronically via the 確定申告書等作成コーナー (NTA Tax Return Preparation Corner) using Claude in Chrome, Antigravity Browser Sub-Agent, or Playwright CLI (fallback). It guides the browser-based input of calculated tax data. Trigger phrases include: "e-Tax提出", "電子申告", "e-Taxで申告", "作成コーナーに入力", "確定申告書等作成コーナー", "作成コーナー", "申告書を提出".
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Manages parent/child agent relationships with task delegation and result aggregation. Supports sequential chains, parallel fans, conditional routing, retry logic, timeout handling, and YAML-based visual workflow definition.
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Deploys swarms of sub-agents for massive parallel data processing tasks. Unlike agent-army (which is for code changes), this is for DATA tasks -- processing 1000 documents, analyzing datasets, bulk content generation. Configurable swarm size, task distribution, result aggregation, progress tracking, and error recovery.
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Deploy a 2-layer parallel agent hierarchy for large, parallelizable work — big refactors, multi-file migrations, codebase-wide audits, bulk generation. A top-tier commander (Fable or Opus) orchestrates the swarms; the user picks a power level (Max Power / Heavy / Balanced / Economy) that sets the Opus/Sonnet/Haiku model mix per layer. Layer 1 is 3-50+ specialist agents, each with its own full context window; Layer 2 is 2+ sub-agents per member. Includes git safety, tiered sizing, a pre-deploy gate, phantom-completion checks, and multi-wave follow-up.
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Use when scanning code for security vulnerabilities. Use when user says "scan security", "kiểm tra bảo mật", "security audit", "review security", or invokes `/vbs-scan-security`. Auto-delegates to sub-agents for large scans (>20 main-language files OR >30 total OR >14 days). Outputs bilingual reports (vi/en). Optional `--auto-fix` (agentic patch + verify loop) and `--sca` (live CVE lookup via OSV.dev).
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Parallel multi-AI cross-validation research workflow (大版本). Dispatch N internal sub-agents + grok + gemini in parallel, automatically cross-validate findings, tier by confidence (strong consensus / partial / conflict / insufficient), generate tiered action items with arbitration. Use when user says "多 AI 调研", "交叉验证", "独立共识", "三脑调研", "multi-ai research", "parallel research", "cross-validate", or needs deep research that benefits from internal data + external 2026 consensus. NOT for quick factual Q&A, pure code reasoning, or tasks needing deep project context.
中文简介正在准备中。当前显示原文说明。
Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes — Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/PRD asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".
中文简介正在准备中。当前显示原文说明。
Review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes: Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/spec asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to "review since X".
中文简介正在准备中。当前显示原文说明。