feat(mem0-plugin): add Codex lifecycle hooks via opt-in installer (#4917)
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#!/usr/bin/env bash
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# Hook: Stop (Codex)
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#
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# Fires when Codex finishes a turn. Reminds the agent to persist any
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# important learnings via the mem0 MCP tools before the turn closes.
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#
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# Input: JSON on stdin with session_id, turn_id, stop_hook_active,
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# last_assistant_message, transcript_path, cwd,
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# hook_event_name, model
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# Output: JSON on stdout (Codex rejects plain text on Stop).
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# - stop_hook_active=true -> {"continue": true} (let the turn end)
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# - stop_hook_active=false -> {"decision":"block","reason":"..."}
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# (continue the turn with the reminder as context)
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#
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# We must respect stop_hook_active or we'd loop forever: every "block"
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# reopens the turn, which triggers Stop again when the agent settles.
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set -uo pipefail
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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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printf '{"continue":true}\n'
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exit 0
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fi
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REASON=$(cat <<'EOF'
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Before finishing, check if there are important learnings from this interaction that should be persisted using the mem0 `add_memory` tool:
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1. Were any significant decisions made? -> Store with metadata `{"type": "decision"}`
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2. Were any new patterns or strategies discovered? -> Store with metadata `{"type": "task_learning"}`
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3. Did any approach fail? -> Store with metadata `{"type": "anti_pattern"}`
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4. Did you learn anything about the user's preferences? -> Store with metadata `{"type": "user_preference"}`
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5. Were there environment/setup discoveries? -> Store with metadata `{"type": "environmental"}`
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Memories can be as detailed as needed — include full context, reasoning, code snippets, file paths, and examples. Longer, searchable memories are more valuable than vague one-liners.
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If nothing notable happened in this interaction, it's fine to skip. Only store genuinely useful learnings.
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EOF
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)
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jq -cn --arg reason "$REASON" '{decision:"block", reason:$reason}'
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exit 0
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