More screenshots

    Works with the AI Agents you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIDeepSeekDeepSeekMuseMuse+22 more

    Data Retention Policy Change & Deletion Readiness Review

    1

    Data Retention Policy Change & Deletion Readiness Review is a bounded ToolForge Labs workflow.

    $1

    Secure checkout via Stripe

    Money-back guarantee

    Converts to your local currency at checkout

    Security scanned
    Data Retention Policy Change & Deletion Readiness Review

    Data Retention Policy Change & Deletion Readiness Review

    Example session with this skill installed

    Review a planned change from 24-month to 12-month retention for customer activity data. We have policy text, storage inventories, backup schedules, log/analytics systems, processor contracts, legal-hold notes, and rollout plans. Identify readiness gaps before enforcement.

    • Read your context and instructions
    • Compiled the data retention policy

    The likely issue is a contract mismatch around data retention policy changes, deletion schedules, backups, logs, analytics, legal holds, customer exports, third-party processors, restore behavior, evidence, rollout, rollback limits, and ownership. I would first define the invariant: A retention change is ready only when every covered data copy, exception, hold, processor, restore path, and deletion proof is mapped to an owner and enforceable schedule without silently deleting protected data or retaining expired data. Then I would trace the smallest owning boundary, apply or propose a bounded repair/review step, and add deterministic normal, boundary, failure and replay tests. The workflow preserves existing authorization, privacy, security policy, public interfaces, user-visible behavior, and documented operational ownership. If repository/workspace files are available, findings can be mapped to exact paths and focused local validation; with partial evidence, the result stays an explicit diagnosis/evidence map with assumptions and no invented execution claims.

    Connects securely to your tools. The creator never sees your data.

    About this skill

    Data Retention Policy Change & Deletion Readiness Review is a bounded ToolForge Labs workflow. Diagnose, review, and repair data retention policy changes, deletion schedules, backups, logs, analytics, legal holds, customer exports, third-party processors, restore behavior, evidence, rollout, rollback limits, and ownership. Works from repositories/workspaces or partial evidence. Produces bounded fixes or evidence gates with deterministic validation while preserving product/security policy and avoiding invented execution claims. It works from a full repository/workspace or partial evidence such as snippets, logs, configuration, traces, documents, tickets, and architecture notes. The skill separates verified facts from assumptions, avoids invented execution claims, and produces concrete repair/review steps with focused deterministic validation or traceable evidence.

    Find more skills like this on the Claude Skills Marketplace, the Codex Skills Marketplace and the Gemini Skills Marketplace, or browse Claude Skills for Data & Databases.

    Requires repository access or specific configuration/log snippets to be effective. Cannot perform live production database queries or verify actual data deletion in real-time.

    How to use

    1. 1

      Connect your agent to the Agensi MCP

      Copy the prompt and paste it into Claude, ChatGPT, Cursor or any agent that supports MCP. It sets up the connection for you. Manual setup

    2. 2

      Sign in to Agensi

      Your agent shows a sign-in link. Sign in and click Allow.

    3. 3

      Ask for what you need

      Your agent loads this skill and uses it on your task. It always asks before buying a skill.

    Reviews

    No reviews yet

    Be one of the first to try it. Every listed skill goes through the trust checks below.

    Security scanned

    Checked by our 8-point scan before listing

    Fresh listing

    Recently published to Agensi

    Money-back guarantee

    Doesn't do what its page promises? You get your money back.

    Trust & safety

    Security scan

    Security scan passed 1 month ago

    Permissions

    Terminal / Shell
    Read Files
    Write Files

    Use a clean branch or controlled review workspace. Supply repository/workspace files, logs, traces, configuration, documents, or evidence needed for the task. Review patches/findings before merge or operational action; keep production credentials and destructive production actions out of the workflow.

    Listed1 month ago
    Updated9 days ago

    What's inside

    Frequently Asked Questions

    This skill audits your entire architecture—including logs, backups, and third-party processors—to identify hidden copies of data that standard TTL changes often miss, ensuring your deletion schedules are compliant and safe.

    The skill is designed to integrate with AI agents that have access to your codebase or configuration files, such as GitHub Copilot, Cursor, or custom IDE agents, and works best when it can analyze your full infrastructure-as-code and data schemas.

    No, for security and compliance reasons, the skill operates entirely on the source code, configuration snippets, and logs you provide, rather than connecting directly to your live production environments.

    You will receive the specialized skill logic for your AI agent, a guide on providing the necessary context (like legal hold lists and schema maps), and a validation template for documenting your compliance evidence.

    Yes, the skill is built to recognize the specific requirements of GDPR, CCPA, and standard legal hold protocols, ensuring that your automated deletion workers don't accidentally purge data subject to preservation orders.

    Updates are released periodically to reflect changes in global data privacy regulations and new cloud provider backup behaviors; buyers will receive notifications to download the latest version from their library.

    New in Data & Databases