diff --git a/test_workspace.jsonl b/test_workspace.jsonl
deleted file mode 100644
index 668c5b27..00000000
--- a/test_workspace.jsonl
+++ /dev/null
@@ -1,3 +0,0 @@
-{"workspace_id": "test_workspace", "memory_id": "4ff6a7a783a84940a046e557de7542f0", "memory_type": "task", "when_to_use": "When analyzing a complex organization with multiple dimensions (history, products, finances, leadership), especially when the query is open-ended or broad like 'analyze [company]'", "content": "The agent successfully decomposed the task into four targeted web searches: company overview/history, products/services, financial performance, and leadership impact. This multi-angle approach ensured comprehensive coverage of key domains. Each search was designed to extract distinct, high-value information layers, enabling synthesis into a structured, well-rounded analysis. The use of varied queries prevented redundancy and maximized information diversity.", "score": 0.0, "time_created": "2025-08-31 15:42:44", "time_modified": "2025-08-31 15:42:44", "author": "qwen3-30b-a3b-instruct-2507", "metadata": {"when_to_use": "When analyzing a complex organization with multiple dimensions (history, products, finances, leadership), especially when the query is open-ended or broad like 'analyze [company]'", "experience": "The agent successfully decomposed the task into four targeted web searches: company overview/history, products/services, financial performance, and leadership impact. This multi-angle approach ensured comprehensive coverage of key domains. Each search was designed to extract distinct, high-value information layers, enabling synthesis into a structured, well-rounded analysis. The use of varied queries prevented redundancy and maximized information diversity.", "tags": ["multi-faceted analysis", "information decomposition", "web_search strategy", "comprehensive coverage"], "confidence": 0.9, "step_type": "reasoning", "tools_used": ["web_search"]}}
-{"workspace_id": "test_workspace", "memory_id": "2ad5b6aae8724e87944e69ea4476a97c", "memory_type": "task", "when_to_use": "When initial results from a general search are insufficient or too broad, and deeper insights are needed on specific subtopics such as financial trends, product portfolios, or leadership dynamics", "content": "The agent proactively called the same tool (web_search) multiple times with different, focused queries to gather information from various perspectives. This iterative technique allowed for layered understanding—e.g., separating historical milestones from current financial challenges and leadership influence. It demonstrated strategic use of repetition not as redundancy but as a method to triangulate data across domains, significantly improving depth and accuracy.", "score": 0.0, "time_created": "2025-08-31 15:42:44", "time_modified": "2025-08-31 15:42:44", "author": "qwen3-30b-a3b-instruct-2507", "metadata": {"when_to_use": "When initial results from a general search are insufficient or too broad, and deeper insights are needed on specific subtopics such as financial trends, product portfolios, or leadership dynamics", "experience": "The agent proactively called the same tool (web_search) multiple times with different, focused queries to gather information from various perspectives. This iterative technique allowed for layered understanding—e.g., separating historical milestones from current financial challenges and leadership influence. It demonstrated strategic use of repetition not as redundancy but as a method to triangulate data across domains, significantly improving depth and accuracy.", "tags": ["iterative querying", "perspective diversification", "information triangulation", "search optimization"], "confidence": 0.85, "step_type": "action", "tools_used": ["web_search"]}}
-{"workspace_id": "test_workspace", "memory_id": "87afc1367c6c4b739bbe191e1f47c875", "memory_type": "task", "when_to_use": "After gathering raw data from external sources, when synthesizing findings into a coherent, structured response that balances factual reporting with critical insight", "content": "The agent effectively integrated results from multiple searches into a unified summary with clear sectioning: history, products, finance, and leadership. It highlighted both strengths (innovation, mission-driven vision) and risks (financial decline, leadership dependency). This synthesis transformed fragmented data into actionable intelligence, demonstrating how structured summarization enhances usability and decision-making value in agent outputs.", "score": 0.0, "time_created": "2025-08-31 15:42:44", "time_modified": "2025-08-31 15:42:44", "author": "qwen3-30b-a3b-instruct-2507", "metadata": {"when_to_use": "After gathering raw data from external sources, when synthesizing findings into a coherent, structured response that balances factual reporting with critical insight", "experience": "The agent effectively integrated results from multiple searches into a unified summary with clear sectioning: history, products, finance, and leadership. It highlighted both strengths (innovation, mission-driven vision) and risks (financial decline, leadership dependency). This synthesis transformed fragmented data into actionable intelligence, demonstrating how structured summarization enhances usability and decision-making value in agent outputs.", "tags": ["synthesis", "structured summarization", "critical insight", "data integration"], "confidence": 0.9, "step_type": "observation", "tools_used": []}}