Skill: ui-navigation-trajectory-retrieval

[Case 2]

• Initial Environment: A vector database representing a financial application's navigational flow. The database indexes high-level intents like 'Invest', 'Support', and 'Account Management' alongside their required interaction sequences.
• Real Question: Find online financial customer support.
• Real Trajectory: [{'step': 1, 'observation': 'App Landing Page.', 'action': "Click the 'Financial Management' menu button."}, {'step': 2, 'observation': 'Financial main interface.', 'action': 'Click the search bar at the top.'}, {'step': 3, 'observation': 'Search input activated.', 'action': "Input 'online financial customer support'."}, {'step': 4, 'observation': 'Search results list.', 'action': "Click the 'Online Support' button to enter the chat."}]
• Real Answer: You can find support by clicking 'Financial Management', using the search bar to type 'online financial customer support', and then selecting the 'Online Support' button.
• Why this demonstrates the capability: This case shows intent-guided retrieval where a complex search-and-click sequence is recovered from its vector embedding. Success depends on the RAG agent's ability to match the user's abstract intent to a concrete, multi-modal action sequence (text input + buttons) found in the specialized application corpus.

Pipeline Execution Instructions

To synthesize data for this capability, you must strictly follow a 3-phase pipeline. Do not hallucinate steps. Read the corresponding reference file for each phase sequentially:

1. Phase 1: Environment Exploration Read the exploration guidelines to discover raw knowledge seeds: references/EXPLORATION.md

2. Phase 2: Trajectory Selection Once Phase 1 is complete, read the selection criteria to evaluate the trajectory: references/SELECTION.md

3. Phase 3: Data Synthesis Once a trajectory passes Phase 2, read the synthesis instructions to generate the final data: references/SYNTHESIS.md