| # Hook: TaskCompleted | |
| # | |
| # Fires when a task is marked as completed. Reminds Claude to extract | |
| # and store learnings via the mem0 MCP tools. | |
| # | |
| # Input: JSON on stdin with task_id, task_subject, task_description | |
| # Output: Text that becomes feedback to the model (exit 0) | |
| set -euo pipefail | |
| INPUT=$(cat) | |
| TASK_SUBJECT=$(echo "$INPUT" | jq -r '.task_subject // "unknown task"' 2>/dev/null || echo "unknown task") | |
| cat <<EOF | |
| Task completed: "$TASK_SUBJECT" | |
| Extract key learnings from this completed task and store them using the mem0 \`add_memory\` tool: | |
| 1. What strategy worked well? -> Store with metadata \`{"type": "task_learning"}\` | |
| 2. Were there failed approaches before finding the solution? -> Store with metadata \`{"type": "anti_pattern"}\` | |
| 3. Were there architectural decisions? -> Store with metadata \`{"type": "decision"}\` | |
| 4. Any new conventions or patterns established? -> Store with metadata \`{"type": "convention"}\` | |
| Memories can be as detailed as needed — include full context, reasoning, code snippets, and examples. | |
| Only store genuinely useful learnings — skip if the task was trivial. | |
| EOF | |
| exit 0 | |