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    Data Restore Readiness Review

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    This skill provides a rigorous review of data restore plans to ensure they are safe, scoped, and reversible.

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    Data Restore Readiness Review

    Data Restore Readiness Review

    Example session with this skill installed

    A customer asks to restore records from last Friday after an accidental deletion. Backups exist, but the team has not confirmed whether the restore will overwrite newer edits, which tenant partitions are affected, or how billing exports will be reconciled afterward.

    • Read your context and instructions
    • Compiled the data restore readiness

    DATA RESTORE READINESS REVIEW

    Case analyzed

    A customer asks to restore records from last Friday after an accidental deletion. Backups exist, but the team has not confirmed whether the restore will overwrite newer edits, which tenant partitions are affected, or how billing exports will be reconciled afterward.

    This review uses only the supplied facts. It does not assume access to production systems, private records, customer systems, vendor portals, or approvals that were not provided.

    Verdict

    NOT READY TO CLOSE. The case contains a material control or evidence gap that must be resolved before the workflow can be treated as complete.

    Verified evidence

    • VERIFIED: The scenario and constraints above were explicitly supplied.
    • VERIFIED: At least one required ownership, sequencing, evidence, or validation condition is missing or inconsistent.
    • VERIFIED: No additional approval or successful execution was supplied.
    • UNKNOWN: Any fact not present in the case remains unknown and must not be invented.

    Concrete findings

    1. The supplied case contains enough evidence to identify a material control or readiness gap, but not enough to claim the workflow is safe or complete.
    2. The highest risk is the mismatch between the stated operating intent and the evidence or state described in the case.
    3. Any remediation must preserve the historical record and keep verified facts separate from assumptions introduced during repair.
    4. Closure must depend on deterministic evidence tied to this exact case rather than a status field, optimistic label, or verbal confirmation.

    The controlling rule for this case is

    A data restore is ready only when the restore point, affected scope, overwrite behavior, owners, downstream impact, validation, and rollback path are explicit and testable.

    Required actions

    1. Capture the current state for restore point and source and identify the accountable owner.
    2. Reconcile affected records and overwrite scope against the intended rule and document every material mismatch.
    3. Create a bounded correction for owners and authorization without rewriting or inventing historical evidence.
    4. Validate downstream dependencies using a repeatable check tied to the supplied scenario.
    5. Do not close the case until validation and rollback evidence has explicit evidence and any remaining exception is named.

    Deterministic validation

    • A reviewer can reproduce the conclusion from the supplied evidence without relying on private context.
    • Every material mismatch has an owner and a specific corrective action.
    • Unknown facts remain labeled UNKNOWN rather than being inferred as completed work.
    • The final state can be checked independently against the stated acceptance condition.
    • No production verification, approval, customer acceptance, or execution result is claimed unless it was actually supplied.

    Evidence boundaries

    • UNKNOWN: Details not explicitly present in the supplied case.
    • UNKNOWN: Whether proposed corrections have been executed.
    • UNKNOWN: Whether downstream owners have accepted the repaired state.
    • UNKNOWN: Whether production behavior matches the intended control.

    These unknowns define the exact evidence required before closure without guessing.

    Decision and handoff

    Keep the case open until the required evidence is attached, the responsible owner is identifiable, and the acceptance condition is demonstrably satisfied. Preserve the original record and append corrections rather than silently rewriting history.

    If the workflow changes later, retain the superseded reasoning and link the new decision to the evidence that caused the change. A later reviewer should be able to reconstruct the chain from request to evidence, decision, action, and verification.

    Closure rule

    Close only when the requested result is supported by evidence. A completed status, saved form, successful navigation, or verbal assurance is not sufficient on its own. The closure record must show what was checked, what changed, who owns the result, and which condition was actually satisfied.

    Acceptance detail

    The final review should explicitly revisit these dimensions: restore point and source, affected records and overwrite scope, owners and authorization, downstream dependencies, validation and rollback evidence. For each one, record the source evidence, current state, expected state, difference, owner, and validation result. If any dimension remains unknown, keep it open or record a bounded exception with an expiry and owner.

    Final conclusion

    The correct disposition for this supplied case is to continue remediation, not to declare success. The evidence is sufficient to identify the gap and define the next actions, but it is not sufficient to claim the repaired state already exists.

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

    About this skill

    Restoring data without a clear plan leads to production drift, broken dependencies, and irreversible data loss. This skill provides a rigorous review of data restore plans to ensure they are safe, scoped, and reversible.

    What it does

    • Scope Verification identifies exactly which records and sources are targeted to prevent accidental overwrites.
    • Dependency Mapping analyzes downstream impacts on linked systems and services.
    • Rollback Planning defines explicit paths for recovery if the restore fails or introduces corruption.
    • Authorization Review confirms ownership and policy boundaries are respected before execution.
    • Validation Design generates deterministic tests to prove the restore succeeded.

    How it works

    1. Fact Extraction pulls concrete facts, constraints, and unknowns from your restore proposal or logs.
    2. Readiness Analysis evaluates the restore point source against affected records and overwrite behavior.
    3. Risk Assessment identifies hypotheses and labels evidence to separate facts from assumptions.
    4. Action Assignment produces a list of corrective actions tied to specific accountable owners.

    Frameworks & tools

    This skill is tool-agnostic and works with SQL backups, NoSQL snapshots, cloud storage versioning, and volume-level recovery plans. It integrates with workspace documentation or logs to provide context-aware reviews.

    Why this beats prompting it yourself

    Generic prompts often miss downstream technical debt or fail to demand a testable rollback path. This skill enforces a canonical invariant that requires every restore to be explicitly scoped and validated before it is deemed ready.

    Use cases

    • Auditing a production database rollback after a failed migration.
    • Reviewing a point-in-time recovery plan for a specific customer tenant.
    • Validating the safety of restoring deleted S3 objects or cloud volumes.
    • Verifying data integrity after a bulk record import from a backup source.

    Known limitations

    Does not perform the actual data movement or execute database commands. Requires the user to provide the context or access to the relevant restore logs and plans.

    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.

    Cannot verify external systems or facts not present in supplied evidence. With partial context it returns explicit evidence gaps instead of fabricated outcomes.

    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.

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    Permissions

    Terminal / Shell
    Read Files
    Write Files

    Use a controlled workspace or supplied evidence. Review owner decisions and proposed changes before operational action.

    Listed1 month ago
    Updated9 days ago

    What's inside

    Frequently Asked Questions

    This skill acts as a safety gate by auditing your restore plans for scope errors, hidden dependencies, and lack of rollback paths, ensuring you don't trade one data crisis for another.

    The skill is tool-agnostic and supports SQL backups, NoSQL snapshots, cloud storage versioning, and volume-level recovery plans across all major cloud providers.

    You receive the core logic for the Readiness Review, a structured template for submitting restore proposals, and a guide for integrating it with your existing AI agent workspace.

    No, for security and safety, this skill provides a rigorous analysis and risk assessment only; it does not have the permissions to execute data movements or database commands.

    Setup involves importing the skill into your preferred AI agent platform and providing it with access to your restore logs or planning documentation for context-aware auditing.

    Updates are released periodically to address new data recovery patterns and are available for download through your marketplace library at no additional cost.

    New in Data & Databases