Gabriel Stein
42 lines
1.7 KiB
Bash
Executable File
42 lines
1.7 KiB
Bash
Executable File
#!/usr/bin/env bash
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# Hook: Stop
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#
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# Fires when Claude finishes responding.
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# Reminds Claude to store any unsaved learnings, then spawns a background
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# process to capture transcript state via the Mem0 REST API directly.
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#
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# Input: JSON on stdin with stop_hook_active, transcript_path, cwd
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# Output: Text that becomes Claude's context (exit 0), or nothing
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#
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# IMPORTANT: Check stop_hook_active to avoid infinite loops.
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set -euo pipefail
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SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
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INPUT=$(cat)
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STOP_HOOK_ACTIVE=$(echo "$INPUT" | jq -r '.stop_hook_active // false' 2>/dev/null || echo "false")
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if [ "$STOP_HOOK_ACTIVE" = "true" ]; then
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exit 0
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fi
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cat <<'EOF'
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Before finishing, check if there are important learnings from this interaction that should be persisted using the mem0 `add_memory` tool:
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1. Were any significant decisions made? -> Store with metadata `{"type": "decision"}`
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2. Were any new patterns or strategies discovered? -> Store with metadata `{"type": "task_learning"}`
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3. Did any approach fail? -> Store with metadata `{"type": "anti_pattern"}`
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4. Did you learn anything about the user's preferences? -> Store with metadata `{"type": "user_preference"}`
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5. Were there environment/setup discoveries? -> Store with metadata `{"type": "environmental"}`
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Memories can be as detailed as needed — include full context, reasoning, code snippets, file paths, and examples. Longer, searchable memories are more valuable than vague one-liners.
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If nothing notable happened in this interaction, it's fine to skip. Only store genuinely useful learnings.
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EOF
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# Capture transcript state in the background via Mem0 REST API
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echo "$INPUT" | python3 "$SCRIPT_DIR/on_pre_compact.py" --source=session-end 2>/dev/null &
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exit 0
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