Implementing GDPR‑Compliant Deletion of Rating Data in OpenClaw

1. Introduction

The hype around AI agents is reshaping every layer of modern software, from chat‑bots to autonomous data‑governance tools. AI marketing agents are now being paired with social platforms like Moltbook to deliver hyper‑personalised experiences. In this context, OpenClaw—a community‑driven rating engine—must align with the European Union’s General Data Protection Regulation (GDPR). Deleting rating data on request isn’t just a feature; it’s a legal obligation.

Rating data is considered personal data when it can be linked to an identifiable user. GDPR therefore requires a clear, auditable, and timely deletion process. This guide walks developers and DevOps engineers through a step‑by‑step implementation on the UBOS platform, tying the solution to AI‑agent automation and Moltbook notifications.

2. Architecture Context

OpenClaw Rating Data Model

OpenClaw stores ratings in a relational table called ratings (PostgreSQL) and mirrors them in a NoSQL cache (ratings_cache) for low‑latency reads. Each rating row contains:

• id – UUID primary key
• user_id – foreign key to the users table
• item_id – the product or content being rated
• score – integer 1‑5
• created_at – timestamp

Micro‑service Placement

In UBOS, OpenClaw runs as an isolated micro‑service with its own Docker image. The service communicates with:

• The User Service for identity verification.
• The Analytics Service for aggregated rating statistics.
• The Moltbook Notification Service for social updates.

Adding a GDPR deletion endpoint therefore touches three layers: the API gateway, the OpenClaw service itself, and downstream listeners.

3. Prerequisites

1. A running UBOS instance with admin access. See the UBOS for startups page for quick onboarding.
2. Clone the OpenClaw repository from your internal Git server.
3. Go 1.22+ installed on your development machine.
4. PostgreSQL client tools (psql) and Redis CLI for cache verification.
5. Access to the Moltbook API token (generated in the Moltbook developer console).

4. Step‑by‑Step Guide

a. Identify Rating Data Tables/Collections

Run the following SQL to list the schema:

SELECT column_name, data_type
FROM information_schema.columns
WHERE table_name = 'ratings';

b. Create GDPR‑Compliant Deletion API Endpoint

Add a new route /api/v1/ratings/delete to router.go. The endpoint expects a JSON payload with user_id and an optional item_id for selective deletion.

c. Implement Cascade Delete for Related Entities

Deleting a rating must also purge:

• Cache entries in Redis.
• Aggregated statistics in the Analytics Service.
• Pending Moltbook notifications.

d. Add Audit Logging for Deletions

Use UBOS’s built‑in Workflow automation studio to emit an immutable log entry to the audit_log table. Include:

• Requestor ID
• Timestamp (UTC)
• Deleted record IDs
• Reason code (e.g., “GDPR‑request”)

e. Secure the Endpoint (Auth, Rate‑Limit)

Protect the route with JWT validation against the User Service. Apply a rate‑limit of 5 requests per minute per user to mitigate abuse.

f. Write Unit and Integration Tests

Tests must cover:

• Successful deletion of a single rating.
• Bulk deletion when item_id is omitted.
• Audit log entry creation.
• Rollback on failure (transactional integrity).

5. Code Snippets

Go Handler Example

package handlers

import (
    "database/sql"
    "encoding/json"
    "net/http"
    "time"

    "github.com/gorilla/mux"
    "github.com/yourorg/openclaw/internal/auth"
    "github.com/yourorg/openclaw/internal/logger"
)

type DeleteRequest struct {
    UserID string `json:"user_id"`
    ItemID string `json:"item_id,omitempty"`
}

// DeleteRatings handles GDPR‑compliant rating deletions.
func DeleteRatings(db *sql.DB) http.HandlerFunc {
    return func(w http.ResponseWriter, r *http.Request) {
        // ---- Auth ----
        if err := auth.ValidateJWT(r); err != nil {
            http.Error(w, "unauthorized", http.StatusUnauthorized)
            return
        }

        // ---- Parse payload ----
        var req DeleteRequest
        if err := json.NewDecoder(r.Body).Decode(&req); err != nil {
            http.Error(w, "bad request", http.StatusBadRequest)
            return
        }

        // ---- Transaction ----
        tx, err := db.Begin()
        if err != nil {
            http.Error(w, "internal error", http.StatusInternalServerError)
            return
        }
        defer tx.Rollback()

        // ---- Delete from ratings table ----
        var query string
        var args []interface{}
        if req.ItemID != "" {
            query = "DELETE FROM ratings WHERE user_id=$1 AND item_id=$2 RETURNING id"
            args = []interface{}{req.UserID, req.ItemID}
        } else {
            query = "DELETE FROM ratings WHERE user_id=$1 RETURNING id"
            args = []interface{}{req.UserID}
        }

        rows, err := tx.Query(query, args...)
        if err != nil {
            http.Error(w, "deletion failed", http.StatusInternalServerError)
            return
        }
        defer rows.Close()

        var deletedIDs []string
        for rows.Next() {
            var id string
            if err := rows.Scan(&id); err != nil {
                http.Error(w, "scan error", http.StatusInternalServerError)
                return
            }
            deletedIDs = append(deletedIDs, id)
        }

        // ---- Cache purge (Redis) ----
        // Assume purgeCache is a helper that removes keys from Redis.
        if err := purgeCache(req.UserID, req.ItemID); err != nil {
            http.Error(w, "cache purge failed", http.StatusInternalServerError)
            return
        }

        // ---- Audit log ----
        audit := map[string]interface{}{
            "user_id":    req.UserID,
            "deleted_ids": deletedIDs,
            "reason":     "GDPR‑request",
            "timestamp":  time.Now().UTC(),
        }
        if err := logger.RecordAudit(tx, audit); err != nil {
            http.Error(w, "audit log failed", http.StatusInternalServerError)
            return
        }

        // ---- Commit ----
        if err := tx.Commit(); err != nil {
            http.Error(w, "commit failed", http.StatusInternalServerError)
            return
        }

        // ---- Notify Moltbook ----
        go notifyMoltbook(req.UserID, deletedIDs)

        w.WriteHeader(http.StatusNoContent)
    }
}

// Helper stubs (implementation omitted for brevity)
func purgeCache(userID, itemID string) error { return nil }
func notifyMoltbook(userID string, ids []string) {}

SQL Delete Queries

-- Delete a single rating
DELETE FROM ratings
WHERE user_id = $1 AND item_id = $2
RETURNING id;

-- Bulk delete all ratings for a user
DELETE FROM ratings
WHERE user_id = $1
RETURNING id;

Test Cases (Go)

func TestDeleteRatings_Single(t *testing.T) {
    // Setup in‑memory DB, insert a rating, call handler, assert deletion & audit.
}

func TestDeleteRatings_Bulk(t *testing.T) {
    // Insert multiple rows, omit ItemID, verify all are removed.
}

6. Deployment

After confirming local tests, update the UBOS manifest to include the new endpoint and its environment variables.

services:
  openclaw:
    image: ubos/openclaw:latest
    ports:
      - "8080:8080"
    env:
      - GDPR_AUDIT=true
      - MOLTB0OK_TOKEN=${MOLTBOOK_TOKEN}
    healthcheck:
      test: ["CMD", "curl", "-f", "http://localhost:8080/health"]
      interval: 30s
      timeout: 5s
      retries: 3

Deploy with a rolling restart to avoid downtime:

ubos deploy --manifest ./manifest.yaml --strategy rolling

7. Validation & Monitoring

• Call GET /api/v1/ratings?user_id=XYZ after deletion; expect an empty array.
• Inspect the audit_log table for a new entry with reason='GDPR‑request'.
• Configure UBOS’s built‑in Enterprise AI platform to alert on failed deletions.

8. Linking to Moltbook

Once a rating is removed, the user’s activity feed on Moltbook should be updated to avoid stale “You rated X” posts. The notifyMoltbook goroutine in the handler sends a POST request to Moltbook’s webhook:

{
  "event": "rating_deleted",
  "user_id": "12345",
  "deleted_rating_ids": ["a1b2c3"]
}

Moltbook then removes the corresponding activity entry. This real‑time sync demonstrates how AI‑driven social platforms can respect privacy without manual intervention.

9. Conclusion

Implementing GDPR‑compliant rating deletion in OpenClaw is a multi‑layered task that touches database design, API security, auditability, and cross‑service communication. By following the steps above, you achieve:

• Legal compliance with GDPR’s “right to be forgotten”.
• Transparent audit trails for regulators.
• Seamless integration with AI‑enhanced social platforms like Moltbook.
• Scalable deployment on the UBOS platform overview.

Ready to host your own GDPR‑ready OpenClaw instance? Visit the OpenClaw hosting page for a one‑click deployment on UBOS. If you’re a startup looking for a fast AI‑powered backend, explore UBOS solutions for SMBs or check out the UBOS partner program to collaborate on future AI‑agent integrations.

Stay ahead of the compliance curve—let AI do the heavy lifting while you focus on building great products.