What problem does it solve? When conducting structured deep research, new research objects often emerge after the initial outline is created. Manually editing the outline.yaml file risks duplicates, formatting errors, and losing track of confirmed additions. ## Core Features & Use Cases - Automatic Outline Location: Finds and reads the outline.yaml file in the current working directory without manual path specification. - Parallel Source Gathering: Simultaneously asks the user for specific item names and optionally launches a web search agent to discover additional research objects. - Deduplication and Confirmation: Merges new items into the outline, avoids duplicates, and presents the result for user confirmation before saving. - Use Case: During a market research project on competitor analysis, you realize three new competitors should be investigated. Run this skill to add them to the existing outline without rebuilding the entire research plan. ## Quick Start Ask the AI to run /research-add-items and specify the new research items you want added to the current outline.