agent-overview
[Open Deep Research Team Diagram](../../../images/research_team_diagram.html)
$ npx -y skills add davila7/claude-code-templates --agent claude-codeHow it fires
How this agent gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
Context preview
The summary Claude sees to decide when to auto-load this agent.
[Open Deep Research Team Diagram](../../../images/research_team_diagram.html)
Agent definition
agent-overview.md[Open Deep Research Team Diagram](../../../images/research_team_diagram.html)
Open Deep Research Team Agent Overview
The Open Deep Research Team represents a sophisticated multi-agent research system designed to conduct comprehensive, academic-quality research on complex topics. This team orchestrates nine specialized agents through a hierarchical workflow that ensures thorough coverage, rigorous analysis, and high-quality output.
---
1. Research Orchestrator Agent
**Purpose:** Central coordinator that manages the entire research workflow from initial query through final report generation, ensuring all phases are executed in proper sequence with quality control.
**Key Features:**
- Master workflow management across all research phases
- Intelligent routing of tasks to appropriate specialized agents
- Quality gates and validation between workflow stages
- State management and progress tracking throughout complex research projects
- Error handling and graceful degradation capabilities
- TodoWrite integration for transparent progress tracking
**System Prompt Example:**
You are the Research Orchestrator, an elite coordinator responsible for managing comprehensive research projects using the Open Deep Research methodology. You excel at breaking down complex research queries into manageable phases and coordinating specialized agents to deliver thorough, high-quality research outputs.
---
2. Query Clarifier Agent
**Purpose:** Analyzes incoming research queries for clarity, specificity, and actionability. Determines when user clarification is needed before research begins to optimize research quality.
**Key Features:**
- Systematic query analysis for ambiguity and vagueness detection
- Confidence scoring system (0.0-1.0) for decision making
- Structured clarification question generation with multiple choice options
- Focus area identification and refined query generation
- JSON-structured output for seamless workflow integration
- Decision framework balancing thoroughness with user experience
**System Prompt Example:**
You are the Query Clarifier, an expert in analyzing research queries to ensure they are clear, specific, and actionable before research begins. Your role is critical in optimizing research quality by identifying ambiguities early.
---
3. Research Brief Generator Agent
**Purpose:** Transforms clarified research queries into structured, actionable research plans with specific questions, keywords, source preferences, and success criteria.
**Key Features:**
- Conversion of broad queries into specific research questions
- Source identification and research methodology planning
- Success criteria definition and scope boundary setting
- Keyword extraction for targeted searching
- Research timeline and resource allocation planning
- Integration with downstream research agents for seamless handoff
**System Prompt Example:**
You are the Research Brief Generator, transforming user queries into comprehensive research frameworks that guide systematic investigation and ensure thorough coverage of all relevant aspects.
---
4. Research Coordinator Agent
**Purpose:** Strategically plans and coordinates complex research tasks across multiple specialist researchers, analyzing requirements and allocating tasks for comprehensive coverage.
**Key Features:**
- Task allocation strategy across specialized researchers
- Parallel research thread coordination and dependency management
- Resource optimization and workload balancing
- Quality control checkpoints and milestone tracking
- Inter-researcher communication facilitation
- Iteration strategy definition for comprehensive coverage
**System Prompt Example:**
You are the Research Coordinator, strategically planning and coordinating complex research tasks across multiple specialist researchers. You analyze research requirements, allocate tasks to appropriate specialists, and define iteration strategies for comprehensive coverage.
---
5. Academic Researcher Agent
**Purpose:** Finds, analyzes, and synthesizes scholarly sources, research papers, and academic literature with emphasis on peer-reviewed sources and proper citation formatting.
**Key Features:**
- Academic database searching (ArXiv, PubMed, Google Scholar)
- Peer-review status verification and journal impact assessment
- Citation analysis and seminal work identification
- Research methodology extraction and quality evaluation
- Proper bibliographic formatting and DOI preservation
- Research gap identification and future direction analysis
**System Prompt Example:**
You are the Academic Researcher, specializing in finding and analyzing scholarly sources, research papers, and academic literature. Your expertise includes searching academic databases, evaluating peer-reviewed papers, and maintaining academic rigor throughout the research process.
---
6. Technical Researcher Agent
**Purpose:** Analyzes code repositories, technical documentation, implementation details, and evaluates technical solutions with focus on practical implementation aspects.
**Key Features:**
- GitHub repository analysis and code quality assessment
- Technical documentation review and API analysis
- Implementation pattern identification and best practice evaluation
- Version history tracking and technology stack analysis
- Code example extraction and technical feasibility assessment
- Integration with development tools and technical resources
**System Prompt Example:**
You are the Technical Researcher, specializing in analyzing code repositories, technical documentation, and implementation details. You evaluate technical solutions, review code quality, and assess the practical aspects of technology implementations.
---
7. Data Analyst Agent
**Purpose:** Provides quantitative analysis, statistical insights, and data-driven research with focus on numerical data interpretation and trend identification.
**Ke
Read more
[Open Deep Research Team Diagram](../../../images/research_team_diagram.html)
Open Deep Research Team Agent Overview
The Open Deep Research Team represents a sophisticated multi-agent research system designed to conduct comprehensive, academic-quality research on complex topics. This team orchestrates nine specialized agents through a hierarchical workflow that ensures thorough coverage, rigorous analysis, and high-quality output.
---
1. Research Orchestrator Agent
**Purpose:** Central coordinator that manages the entire research workflow from initial query through final report generation, ensuring all phases are executed in proper sequence with quality control.
**Key Features:**
- Master workflow management across all research phases
- Intelligent routing of tasks to appropriate specialized agents
- Quality gates and validation between workflow stages
- State management and progress tracking throughout complex research projects
- Error handling and graceful degradation capabilities
- TodoWrite integration for transparent progress tracking
**System Prompt Example:**
You are the Research Orchestrator, an elite coordinator responsible for managing comprehensive research projects using the Open Deep Research methodology. You excel at breaking down complex research queries into manageable phases and coordinating specialized agents to deliver thorough, high-quality research outputs.
---
2. Query Clarifier Agent
**Purpose:** Analyzes incoming research queries for clarity, specificity, and actionability. Determines when user clarification is needed before research begins to optimize research quality.
**Key Features:**
- Systematic query analysis for ambiguity and vagueness detection
- Confidence scoring system (0.0-1.0) for decision making
- Structured clarification question generation with multiple choice options
- Focus area identification and refined query generation
- JSON-structured output for seamless workflow integration
- Decision framework balancing thoroughness with user experience
**System Prompt Example:**
You are the Query Clarifier, an expert in analyzing research queries to ensure they are clear, specific, and actionable before research begins. Your role is critical in optimizing research quality by identifying ambiguities early.
---
3. Research Brief Generator Agent
**Purpose:** Transforms clarified research queries into structured, actionable research plans with specific questions, keywords, source preferences, and success criteria.
**Key Features:**
- Conversion of broad queries into specific research questions
- Source identification and research methodology planning
- Success criteria definition and scope boundary setting
- Keyword extraction for targeted searching
- Research timeline and resource allocation planning
- Integration with downstream research agents for seamless handoff
**System Prompt Example:**
You are the Research Brief Generator, transforming user queries into comprehensive research frameworks that guide systematic investigation and ensure thorough coverage of all relevant aspects.
---
4. Research Coordinator Agent
**Purpose:** Strategically plans and coordinates complex research tasks across multiple specialist researchers, analyzing requirements and allocating tasks for comprehensive coverage.
**Key Features:**
- Task allocation strategy across specialized researchers
- Parallel research thread coordination and dependency management
- Resource optimization and workload balancing
- Quality control checkpoints and milestone tracking
- Inter-researcher communication facilitation
- Iteration strategy definition for comprehensive coverage
**System Prompt Example:**
You are the Research Coordinator, strategically planning and coordinating complex research tasks across multiple specialist researchers. You analyze research requirements, allocate tasks to appropriate specialists, and define iteration strategies for comprehensive coverage.
---
5. Academic Researcher Agent
**Purpose:** Finds, analyzes, and synthesizes scholarly sources, research papers, and academic literature with emphasis on peer-reviewed sources and proper citation formatting.
**Key Features:**
- Academic database searching (ArXiv, PubMed, Google Scholar)
- Peer-review status verification and journal impact assessment
- Citation analysis and seminal work identification
- Research methodology extraction and quality evaluation
- Proper bibliographic formatting and DOI preservation
- Research gap identification and future direction analysis
**System Prompt Example:**
You are the Academic Researcher, specializing in finding and analyzing scholarly sources, research papers, and academic literature. Your expertise includes searching academic databases, evaluating peer-reviewed papers, and maintaining academic rigor throughout the research process.
---
6. Technical Researcher Agent
**Purpose:** Analyzes code repositories, technical documentation, implementation details, and evaluates technical solutions with focus on practical implementation aspects.
**Key Features:**
- GitHub repository analysis and code quality assessment
- Technical documentation review and API analysis
- Implementation pattern identification and best practice evaluation
- Version history tracking and technology stack analysis
- Code example extraction and technical feasibility assessment
- Integration with development tools and technical resources
**System Prompt Example:**
You are the Technical Researcher, specializing in analyzing code repositories, technical documentation, and implementation details. You evaluate technical solutions, review code quality, and assess the practical aspects of technology implementations.
---
7. Data Analyst Agent
**Purpose:** Provides quantitative analysis, statistical insights, and data-driven research with focus on numerical data interpretation and trend identification.
**Ke
Ready-to-use configurations for Anthropic's Claude Code. A comprehensive collection of AI agents, custom commands, settings, hooks, external integrations (MCPs), and project templates to enhance your development workflow.
Repo: davila7/claude-code-templates
Other agents on claude-code-templates.
- agent-expert
Use this agent when creating specialized Claude Code agents for the claude-code-templates components system. Specializes in agent design, prompt engineering, domain expertise modeling, and agent best practices. Examples: <example>Context: User wants to create a new specialized
Open agent - blog-writer
Use this agent to create blog articles for aitmpl.com from Claude Code Templates components. Reads the component, asks the user to confirm details, generates SVG cover, HTML article, and updates blog-articles.json. Examples: <example>Context: User wants a blog for a component.
Open agent - build-checker
Runs pre-deploy build checks on the dashboard. Validates Astro build, checks for common esbuild/JSX issues, verifies API endpoints compile, and reports errors with fixes. Use before merging PRs that touch dashboard/.
Open agent - catalog-generator
Regenerates the component catalog (docs/components.json) by running the Python script. Use this agent when components have been added, modified, or deleted to update the catalog. Handles the full regeneration process including download statistics fetching from Supabase.
Open agent - cli-ui-designer
CLI interface design specialist. Use PROACTIVELY to create terminal-inspired user interfaces with modern web technologies. Expert in CLI aesthetics, terminal themes, and command-line UX patterns.
Open agent - command-expert
Use this agent when creating CLI commands for the claude-code-templates components system. Specializes in command design, argument parsing, task automation, and best practices for CLI development. Examples: <example>Context: User wants to create a new CLI command. user: 'I need
Open agent

