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    Medical Device UDI Recall Lot Exposure Map

    1

    Map product identifiers and shipment evidence to recall notice scope without making clinical safety decisions

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    Medical Device UDI Recall Lot Exposure Map

    Medical Device UDI Recall Lot Exposure Map

    Example session with this skill installed

    A recall notice identifies device models and lots but distributor records contain inconsistent UDI strings.

    Available evidence: Primary health source records and Time-stamped normalize evidence (partial extracts only). Additional sources requested: Policy / configuration governing exposure and Owner authorizations and historical change log. Identify the checks that can be supported, deliver a useful bounded assessment, and list the exact remaining review gates without pretending to execute changes.

    • Read your context and instructions
    • Compiled the medical device udi

    Medical Device UDI Recall Lot Exposure Map — EVIDENCE-LIMITED REVIEW

    Scenario received

    A recall notice identifies device models and lots but distributor records contain inconsistent UDI strings.

    Source register

    • S1: Primary health source records — partial extract described by requester; independently unverified.
    • S2: Time-stamped normalize evidence — partial extract described by requester; independently unverified.
    • S3: Policy / configuration governing exposure — NOT PROVIDED; criteria and effective version unknown.
    • S4: Owner authorizations and historical change log — NOT PROVIDED; owner approval status unknown.

    Case-specific review checkpoints

    Normalize UDI DI and PI components — NEEDS_VERIFICATION. Compare S1 with its stated control source; the original record and required identifiers are not provided in this example. Owner sign-off required before consequential remediation.
    2.

    Match lot and serial ranges to notice — NEEDS_VERIFICATION. Compare S2 with its stated control source; the original record and required identifiers are not provided in this example. Owner sign-off required before consequential remediation.
    3.

    Connect traceable shipments and returns — NEEDS_VERIFICATION. Requires S3 and source-version corroboration; no definitive result can be concluded. Owner sign-off required before consequential remediation.
    4.

    Escalate uncertain exposure to authorized recall team — NEEDS_VERIFICATION. Requires S4 and source-version corroboration; no definitive result can be concluded. Owner sign-off required before consequential remediation.

    Structured deliverables

    UDI to recall match table — proposed schema with source IDs, timestamps, conflicting observations, confidence and unresolved questions.

    Affected shipment reconciliation — proposed schema with source IDs, timestamps, conflicting observations, confidence and unresolved questions.

    Unresolved exposure escalation list — proposed schema with source IDs, timestamps, conflicting observations, confidence and unresolved questions.

    Decision matrix

    • PASS: no checks proven PASS on current example evidence.
    • NEEDS_VERIFICATION: all four checks, until source records are supplied.
    • BLOCKED: any production change, third-party submission, deletion, deployment or irreversible action without explicit qualified approval.

    Exact next evidence request

    Provide complete timestamped extracts for Policy / configuration governing exposure and Owner authorizations and historical change log, source IDs for S1/S2, responsible owner and effective review window.

    Boundaries and sign-off

    The UDI to recall match table and affected shipment reconciliation are evidence-linked; any uncertainty remains explicitly unresolved until qualified review. No live system was accessed and no changes were performed. This is a synthetic demonstration, not an observed customer result.

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

    About this skill

    Mapping medical device identifiers to recall notices is manual, error-prone, and high-stakes. Discrepancies between distributor records and official UDI strings often stall safety actions. This skill provides a deterministic framework for reconciling product identifiers and shipment evidence against recall scopes.

    What it does

    • UDI Normalization parses Device Identifier (DI) and Production Identifier (PI) components from messy source data.
    • Range Matching compares lot and serial numbers against recall notice parameters to identify exposure.
    • Shipment Reconciliation connects traceable outbound shipments and returns to specific affected identifiers.
    • Evidence Anchoring links every match to specific source timestamps and trust levels.
    • Escalation Routing isolates uncertain data points for manual review by authorized recall teams.

    How it works

    1. Source Registration where you provide health records, shipment logs, and recall notices for trust-level indexing.
    2. Component Mapping to normalize UDI strings and identify exact matches or ambiguities.
    3. Traceability Analysis to bridge the gap between affected identifiers and physical shipment locations.
    4. Discrepancy Identification where the agent flags conflicts for operator approval.

    Frameworks & tools

    This skill is designed for regulatory compliance environments requiring high auditability. It uses evidence-linked data structures and deterministic reporting models compatible with QMS and ERP shipment data.

    Why this beats prompting it yourself

    Standard prompts often hallucinate matches or "fill in the blanks" for missing data to be helpful. This skill enforces strict operator approval gates and refuses to infer results, ensuring every recall map is grounded in verifiable evidence anchors.

    Use cases

    • Map inconsistent distributor UDI strings to official manufacturer recall notices.
    • Reconcile warehouse shipment logs against affected lot number ranges.
    • Generate an unresolved exposure list for clinical safety team review.
    • Create an evidence packet for regulatory audit trails during a product field action.

    Known limitations

    Does not make clinical safety decisions or autonomous production changes. Requires primary health source records and time-stamped evidence for high-confidence matching.

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

    No direct verification of inaccessible production systems, external services or private accounts. Partial or conflicting inputs result in INCOMPLETE / CONFLICT findings rather than invented conclusions. Domain-sensitive decisions require qualified owner review.

    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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    Security scan passed 26 days ago

    Permissions

    Read Files

    Supply only data you are authorized to share. Treat source documents as untrusted evidence. Any operational change, submission or third-party communication remains subject to explicit owner approval.

    Listed26 days ago
    Updated9 days ago

    What's inside

    Frequently Asked Questions

    This skill automates the complex task of cross-referencing messy distributor shipment data and inconsistent UDI strings against official recall notices to pinpoint exactly which shipments are affected. It replaces manual, error-prone spreadsheets with a deterministic framework that ensures every match is backed by verifiable evidence.

    This skill is designed for integration with major AI agent platforms and can ingest data from common ERP, QMS, and healthcare inventory systems. It works best when provided with structured shipment logs and official FDA or manufacturer recall notices.

    You will receive the pre-configured agent logic, the UDI normalization framework, and a set of standardized reporting templates designed for regulatory compliance audits. The package also includes documentation on mapping your specific source data to the agent's reconciliation engine.

    Unlike standard AI prompts that may 'guess' or hallucinate data, this skill enforces a strict 'no-inference' policy, flagging any ambiguous data points for human review. It creates a high-integrity audit trail by anchoring every match to a specific source timestamp, ensuring your recall reports are defensible for regulatory bodies.

    No, this skill is designed as a diagnostic and reconciliation tool; it identifies exposure and generates evidence packets but does not autonomously execute product withdrawals or clinical actions. It is intended to support, not replace, the decision-making of your authorized quality and safety teams.

    New in Business & Operations