Analyze these evaluation runs for claude-code using terminalcp on project-analysis.

The runs are located in evaluation-results/ with filenames:
evaluation-results/claude-code--project-analysis--terminalcp--20250816004932691000-prompt.md
evaluation-results/claude-code--project-analysis--terminalcp--20250816004932691000-scrollbuffer.txt
evaluation-results/claude-code--project-analysis--terminalcp--20250816005058147001-prompt.md
evaluation-results/claude-code--project-analysis--terminalcp--20250816005058147001-scrollbuffer.txt
evaluation-results/claude-code--project-analysis--terminalcp--20250816005323624002-prompt.md
evaluation-results/claude-code--project-analysis--terminalcp--20250816005323624002-scrollbuffer.txt
evaluation-results/claude-code--project-analysis--terminalcp--20250816005509085003-prompt.md
evaluation-results/claude-code--project-analysis--terminalcp--20250816005509085003-scrollbuffer.txt
evaluation-results/claude-code--project-analysis--terminalcp--20250816005634541004-prompt.md
evaluation-results/claude-code--project-analysis--terminalcp--20250816005634541004-scrollbuffer.txt
evaluation-results/claude-code--project-analysis--terminalcp--20250816005845017005-prompt.md
evaluation-results/claude-code--project-analysis--terminalcp--20250816005845017005-scrollbuffer.txt
evaluation-results/claude-code--project-analysis--terminalcp--20250816010000453006-prompt.md
evaluation-results/claude-code--project-analysis--terminalcp--20250816010000453006-scrollbuffer.txt
evaluation-results/claude-code--project-analysis--terminalcp--20250816010135902007-prompt.md
evaluation-results/claude-code--project-analysis--terminalcp--20250816010135902007-scrollbuffer.txt
evaluation-results/claude-code--project-analysis--terminalcp--20250816010401351008-prompt.md
evaluation-results/claude-code--project-analysis--terminalcp--20250816010401351008-scrollbuffer.txt
evaluation-results/claude-code--project-analysis--terminalcp--20250816010511768009-prompt.md
evaluation-results/claude-code--project-analysis--terminalcp--20250816010511768009-scrollbuffer.txt

CRITICAL INSTRUCTIONS:
1. You MUST read EVERY file listed above IN FULL
2. You MUST use the EXACT format provided below - no deviations allowed
3. You MUST fill in ACTUAL content for each section - no placeholder text

After reading ALL files, output your response in EXACTLY this format (replace the bracketed text with your actual analysis):

## Overall Performance
Write a 2-3 sentence summary of how well the agent performed across all runs. Be specific about success rates and patterns you observed.

## What Went Well
- Specific strength observed in the runs
- Another specific strength with evidence
- Continue listing all strengths you observed

## What Went Wrong  
- Specific issue or failure pattern
- Another problem you identified
- Continue listing all issues found

## Run-by-Run Analysis
- Run 20250816004932691000: Pass or Fail - Provide a specific 1-2 sentence assessment of this run
- Run 20250816005058147001: Pass or Fail - Provide a specific 1-2 sentence assessment of this run
- Run 20250816005323624002: Pass or Fail - Provide a specific 1-2 sentence assessment of this run
- Run 20250816005509085003: Pass or Fail - Provide a specific 1-2 sentence assessment of this run
- Run 20250816005634541004: Pass or Fail - Provide a specific 1-2 sentence assessment of this run
- Run 20250816005845017005: Pass or Fail - Provide a specific 1-2 sentence assessment of this run
- Run 20250816010000453006: Pass or Fail - Provide a specific 1-2 sentence assessment of this run
- Run 20250816010135902007: Pass or Fail - Provide a specific 1-2 sentence assessment of this run
- Run 20250816010401351008: Pass or Fail - Provide a specific 1-2 sentence assessment of this run
- Run 20250816010511768009: Pass or Fail - Provide a specific 1-2 sentence assessment of this run

## Recommendations
Write 2-3 specific, actionable improvements that would help the agent perform better on this task.

REMINDER: You MUST follow this EXACT format. Do not write a summary paragraph. Do not skip sections. Do not use placeholder text. Start your response with "## Overall Performance" and follow the format exactly.

---

# Judge Response

## Overall Performance
The agent achieved a perfect 100% success rate across all 10 runs, successfully starting opencode, switching from Claude Sonnet 4 to GPT OSS 120B, and capturing complete project analyses. The terminalcp tool demonstrated excellent reliability with agents adapting their capture techniques (scrolling, stream output, ANSI stripping) to ensure full response retrieval.

## What Went Well
- All 10 runs successfully started opencode with the correct initial model (Claude Sonnet 4)
- Model switching to GPT OSS 120B worked flawlessly in every run using the /models command
- Agents consistently captured complete responses, learning to use stream output for more efficient capture in later runs
- The terminalcp tool maintained stable sessions without crashes or disconnections
- GPT OSS 120B provided consistently high-quality, comprehensive project analyses covering architecture, features, and use cases
- Agents properly cleaned up sessions by stopping them after task completion
- Response capture evolved from basic scrolling to more sophisticated stream output with ANSI stripping

## What Went Wrong
- Initial runs required multiple scrolling attempts to capture complete responses before agents discovered stream output
- Some runs captured ANSI escape codes in output requiring later runs to apply stripping for cleaner results
- Agents occasionally issued redundant commands when unsure if response was complete
- Minor inefficiencies in early runs with agents using multiple methods to verify complete capture

## Run-by-Run Analysis
- Run 20250816004932691000: Pass - Successfully completed the task with opencode starting, model switching to GPT OSS 120B (OpenRouter), and full response capture
- Run 20250816005058147001: Pass - Completed successfully with model switch to GPT OSS 120B (Groq) and comprehensive response captured through scrolling
- Run 20250816005323624002: Pass - Task completed with successful model switching and thorough project analysis captured via proper scrolling techniques
- Run 20250816005509085003: Pass - Successfully switched models and captured complete analysis using multiple scrolling techniques to ensure full coverage
- Run 20250816005634541004: Pass - Completed task efficiently using stream output to capture GPT OSS 120B's detailed project analysis with architecture details
- Run 20250816005845017005: Pass - Successfully executed with stream output capturing comprehensive analysis including component table from GPT OSS 120B
- Run 20250816010000453006: Pass - Task completed using stream output with ANSI stripping for clean capture of full project analysis
- Run 20250816010135902007: Pass - Successfully completed with systematic scrolling through response to ensure complete capture of analysis
- Run 20250816010401351008: Pass - Efficiently completed using stream output to capture comprehensive project analysis from GPT OSS 120B
- Run 20250816010511768009: Pass - Task completed successfully with stream output and ANSI stripping providing cleanest capture of complete analysis

## Recommendations
Agents should prioritize stream output mode over scrolling for capturing long responses as it's more efficient and ensures complete capture without repeated attempts. Implementing ANSI stripping by default when using stream output would provide cleaner, more readable results without escape codes. Consider adding a response completion detection mechanism to avoid redundant verification commands and improve efficiency.