224 lines
6.7 KiB
Markdown
224 lines
6.7 KiB
Markdown
## Task
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Launches a smart agent to handle complex searches and investigations. Great for large-scale work without eating up context.
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### Usage
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```bash
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# Request Task from Claude
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"Investigate [task] using Task"
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```
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### What Task Does
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**Works Independently**
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- Combines multiple tools automatically
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- Gathers and analyzes step by step
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- Puts results together in clear reports
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**Saves Context**
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- Uses less memory than manual searching
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- Searches lots of files efficiently
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- Pulls data from outside sources
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**Ensures Quality**
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- Checks if sources are reliable
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- Verifies from different angles
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- Fills in missing pieces
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### Basic Examples
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```bash
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# Complex codebase investigation
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"Investigate which files implement this feature using Task"
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# Large-scale file search
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"Identify configuration file inconsistencies using Task"
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# External information collection
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"Investigate the latest AI technology trends using Task"
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```
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### Collaboration with Claude
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```bash
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# Complex problem analysis
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"Analyze the cause of memory leaks using Task, including profiling results and logs"
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# Dependency investigation
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"Investigate vulnerabilities of this npm package using Task"
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# Competitor analysis
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"Investigate API specifications of competing services using Task"
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# Architecture analysis
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"Analyze dependencies of this microservice using Task"
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```
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### Task vs Other Commands
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#### When to Use What
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| Command | Main Use Case | Execution Method | Information Collection |
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| ------------------- | ------------------------------- | --------------------- | -------------------------- |
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| **Task** | Investigation, analysis, search | Autonomous execution | Multiple sources |
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| ultrathink | Deep thinking, judgment | Structured thinking | Existing knowledge-focused |
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| sequential-thinking | Problem-solving, design | Step-by-step thinking | As needed |
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| plan | Implementation planning | Approval process | Requirement analysis |
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#### Quick Decision Guide
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```text
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Need to gather info?
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├─ Yes → From many places or lots of files?
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│ ├─ Yes → **Use Task**
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│ └─ No → Just ask normally
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└─ No → Need deep thinking?
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├─ Yes → Use ultrathink/sequential-thinking
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└─ No → Just ask normally
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```
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### When Task Works Best
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**Great For**
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- Exploring complex codebases (dependencies, architecture)
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- Searching many files (patterns, configs)
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- Gathering external info (tech trends, libraries)
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- Combining data from multiple places (logs, metrics)
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- Repetitive investigations (audits, debt checks)
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- Big searches that would eat too much context
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**Not Great For**
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- Simple questions I already know
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- Quick one-time tasks
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- Things needing back-and-forth discussion
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- Design decisions (use plan or thinking commands instead)
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### Detailed Examples by Category
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#### System Analysis and Investigation
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```bash
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# Complex system analysis
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"Identify bottlenecks in the EC site using Task, investigating database, API, and frontend"
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# Architecture analysis
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"Analyze dependencies of this microservice using Task, including API communication and data flow"
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# Technical debt investigation
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"Analyze technical debt in legacy code using Task, including refactoring priorities"
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```
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#### Security and Compliance
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```bash
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# Security audit
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"Investigate vulnerabilities in this application using Task, based on OWASP Top 10"
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# License investigation
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"Investigate license issues in project dependencies using Task"
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# Configuration file audit
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"Identify security configuration inconsistencies using Task, including environment differences"
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```
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#### Performance and Optimization
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```bash
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# Performance analysis
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"Identify heavy queries in the application using Task, including execution plans and optimization proposals"
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# Resource usage investigation
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"Investigate causes of memory leaks using Task, including profiling results and code analysis"
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# Bundle size analysis
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"Investigate frontend bundle size issues using Task, including optimization suggestions"
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```
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#### External Information Collection
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```bash
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# Technology trend investigation
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"Investigate 2024 JavaScript framework trends using Task"
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# Competitor analysis
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"Investigate API specifications of competing services using Task, including feature comparison table"
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# Library evaluation
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"Compare state management libraries using Task, including performance and learning costs"
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```
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### Execution Flow and Quality Assurance
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#### Task Execution Flow
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```text
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1. Initial Analysis
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├─ Decomposition of task and identification of investigation scope
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├─ Selection of necessary tools and information sources
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└─ Development of execution plan
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2. Information Collection
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├─ File search and code analysis
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├─ Collection of external information
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└─ Data structuring
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3. Analysis and Integration
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├─ Relevance analysis of collected information
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├─ Identification of patterns and issues
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└─ Verification of hypotheses
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4. Reporting and Proposal
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├─ Structuring of results
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├─ Creation of improvement proposals
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└─ Presentation of next actions
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```
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#### Quality Assurance
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- **Reliability check of information sources**: Fact confirmation from multiple sources
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- **Completeness check**: Verification of no gaps in investigation targets
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- **Consistency verification**: Confirmation of consistency in conflicting information
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- **Practicality evaluation**: Assessment of feasibility and effectiveness of proposals
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### Error Handling and Constraints
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#### Common Constraints
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- **External API usage limits**: Rate limits and authentication errors
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- **Large file processing limits**: Memory and timeout constraints
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- **Access permission issues**: Restrictions on file and directory access
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#### Error Handling
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- **Partial result reporting**: Analysis with only obtainable information
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- **Alternative proposals**: Suggestion of alternative investigation methods under constraints
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- **Stepwise execution**: Division of large-scale tasks for execution
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### Notes
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- Task is optimal for complex, autonomous investigation and analysis tasks
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- For simple questions or when immediate answers are needed, use normal question format
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- Treat investigation results as reference information and always verify important decisions
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- When collecting external information, pay attention to the freshness and accuracy of information
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### Execution Example
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```bash
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# Usage example
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"Investigate issues in GraphQL schema using Task"
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# Expected behavior
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# 1. Dedicated agent starts
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# 2. Search for GraphQL-related files
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# 3. Analyze schema definitions
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# 4. Compare with best practices
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# 5. Identify issues and propose improvements
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# 6. Create structured report
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```
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