Code Targeting Overview
Artemis can work with codebases of any size, from small projects to large enterprise applications. Code targeting lets you extract a focused subset of your codebase so Artemis works on the most impactful areas — reducing processing time and keeping AI context tight and relevant.
Navigating to Code Targeting
Step 1: Go to the Optimise tab
From your project, click the Optimise tab in the top navigation.
Step 2: Open the Targets page
You'll land on the Targets page. From here you have two ways to start identifying and creating targets:
- Use the agent — the right-hand panel has a built-in chat agent. Describe your optimisation goals and it will analyse your codebase, suggest targets, and help you create them interactively.
- Use the Add targets button — click + Add targets in the top right to open the Code Targeting panel and choose a targeting method manually.
Step 3: Choose a targeting method
The Code Targeting panel opens with all available methods.
Targeting Methods
File-by-File Targeting (Thorough)
Scans each file in your codebase individually. Apply filters to extract specific code targets. Best for comprehensive coverage when you want full visibility across the entire project.
- Processes each file sequentially
- Filter by criteria (size, complexity, content patterns)
- Extract targets with full coverage
Agent Targeting (Fast)
Uses an AI agent to analyse your code and identify the highest-impact areas for optimisation. Provides quick results by focusing on high-value sections rather than scanning everything.
- Agent-based codebase analysis
- Priority results based on impact
- Focused approach with quick insights
Chat with Agent (Interactive)
Have a conversational session with an AI agent about your codebase. Ask questions, explore optimisation opportunities, and get guidance on where to focus — then extract targets directly from the conversation.
- Ask questions about your codebase
- Set optimisation goals through dialogue
- Explore optimisation opportunities interactively
Tool Integration
Import results from external development tools to use as targeting input. Supports profiling and static analysis tools so you can act on data you've already collected.
- VTune support
- SonarQube support
- Custom tools and profile data import
Pull Request Targeting
Analyse branches and code changes to identify targets for pull request reviews and optimisation suggestions.
- Filter by criteria or branch diff
- Change analysis across PRs
- Code suggestions based on PR context
Contributor Analysis
Analyse code quality scores for each contributor. Filter by time periods and use LLM queries for specific insights.
- Code quality scoring per contributor
- Time-based target filtering
- LLM filters for custom queries
- Historical and comparative analysis
Next Steps
After identifying your targets:
- Score your targets to prioritise where to focus
- Generate new code versions
- Validate the results