gsd-extract-learningslisted

<cursor_skill_adapter> ## A. Skill Invocation - This skill is invoked when the user mentions `gsd-extract-learnings` or describes a task matching this skill. - Treat all user text after the skill mention as `{{GSD_ARGS}}`. - If no arguments are present, treat `{{GSD_ARGS}}` as empty. ## B. User Prompting When the workflow needs user input, prompt the user conversationally: - Present options as a numbered list in your response text - Ask the user to reply with their choice - For multi-select, ask for comma-separated numbers ## C. Tool Usage Use these Cursor tools when executing GSD workflows: - `Shell` for running commands (terminal operations) - `StrReplace` for editing existing files - `Read`, `Write`, `Glob`, `Grep`, `Task`, `WebSearch`, `WebFetch`, `TodoWrite` as needed ## D. Subagent Spawning When the workflow needs to spawn a subagent: - Use `Task(subagent_type="generalPurpose", ...)` - The `model` parameter maps to Cursor's model options (e.g., "fast") </cursor_skill_adapter> <objective> Extract structured learnings from completed phase artifacts (PLAN.md, SUMMARY.md, VERIFICATION.md, UAT.md, STATE.md) into a LEARNINGS.md file that captures decisions, lessons learned, patterns discovered, and surprises encountered. </objective> <execution_context> @/Users/zaneliu/Projects/open-source/friday-ai/.cursor/gsd-core/workflows/extract-learnings.md </execution_context> Execute the extract-learnings workflow from @/Users/zaneliu/Projects/open-source/friday-ai/.cursor/gsd-c