| name | gsd-extract-learnings |
| description | Extract decisions, lessons, patterns, and surprises from completed phase artifacts |
<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>
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.
<execution_context>
@/Users/zaneliu/Projects/open-source/cloud-cli-proxy/.cursor/get-shit-done/workflows/extract-learnings.md
</execution_context>
Execute the extract-learnings workflow from @/Users/zaneliu/Projects/open-source/cloud-cli-proxy/.cursor/get-shit-done/workflows/extract-learnings.md end-to-end.