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    Urban E-Scooter Brake Recall Closure Evidence

    1

    Check whether recalled scooter units were repaired and cleared before redeployment

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    Urban E-Scooter Brake Recall Closure Evidence

    Urban E-Scooter Brake Recall Closure Evidence

    Example session with this skill installed

    Several fleet units were marked service-ready without completed recall evidence.

    Available evidence: fleet unit serial list (partial). Additional evidence requested: case identifiers and custody records, approved standards and release criteria, inspection and owner signoff trail. Review the case, identify open evidence gaps, and do not invent a live test or production change.

    • Read your context and instructions
    • Compiled the urban e-scooter brake

    Urban E-Scooter Brake Recall Closure Evidence — EVIDENCE-LIMITED REVIEW

    Scenario received

    Several fleet units were marked service-ready without completed recall evidence.

    Source register

    • S1: fleet unit serial list — PARTIAL SOURCE PROVIDED.
    • S2: case identifiers and custody records — NOT PROVIDED; REQUIRED TO VERIFY.
    • S3: approved standards and release criteria — NOT PROVIDED; REQUIRED TO VERIFY.
    • S4: inspection and owner signoff trail — NOT PROVIDED; REQUIRED TO VERIFY.

    Concrete checks

    1. reconcile recall serials with work-order signoff — PRELIMINARY, NOT VERIFIED.
    2. verify road-test outcomes and quarantine flags — AWAITING CORROBORATING EVIDENCE.
    3. crosscheck source timestamps identifiers and changed versions — AWAITING CORROBORATING EVIDENCE.
    4. record exceptions and reversible verification gates — AWAITING CORROBORATING EVIDENCE.

    Deliverables / acceptance gates

    • fleet unit serial list evidence map: DRAFT / INCOMPLETE until evidence is validated.
    • recall open exception register: DRAFT / INCOMPLETE until evidence is validated.
    • release proof validation plan: DRAFT / INCOMPLETE until evidence is validated.

    Decision

    INCOMPLETE — HUMAN REVIEW REQUIRED. Confirm dates, IDs, affected scope, owners and acceptance evidence. Do not claim authorization or execution that did not occur.

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

    About this skill

    Managing safety recalls for e-scooter fleets involves high-stakes data reconciliation. When fleet units are marked service-ready without verified repair records, manual audits become a bottleneck. This skill enforces an evidence-based review to ensure every unit is cleared before redeployment.

    What it does

    • Serial Reconciliation matches fleet unit serial numbers against specific work-order signoffs.
    • Outcome Verification checks road-test results and validates that quarantine flags were properly cleared.
    • Temporal Auditing cross-references source timestamps and version identifiers to prevent stale data errors.
    • Exception Mapping identifies missing evidence, owner approval gaps, and reversible verification gates.

    How it works

    1. Supply the fleet unit serial list and case identifiers for the recall event.
    2. The skill reconciles serials against work-order signatures and road-test outcomes.
    3. It performs a cross-check of timestamps and version history to ensure data integrity.
    4. It generates a comprehensive evidence map and an open exception register.

    Frameworks & tools

    Works with local text files, CSV exports from fleet management systems, and JSON custody records. It runs in environments like Claude Code or Cursor using local context.

    Why this beats prompting it yourself

    Generic prompts often hallucinate compliance or assume repairs are done based on status labels. This skill uses a strict decision discipline, classifying every unit as VERIFIED, CONTRADICTED, or UNVERIFIED based only on provided source IDs and timestamps.

    Use cases

    • Auditing e-scooter fleet redeployment after a mechanical brake recall.
    • Identifying specific units that bypassed maintenance protocols.
    • Generating release proof validation plans for safety compliance officers.

    Known limitations

    Requires local text-based logs or lists. It cannot directly access proprietary cloud databases or real-time IoT telemetry without exported files.

    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.

    Requires local text-based logs or exports. Does not perform automated system writes without explicit authorization. Scope is limited to provided evidence.

    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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    Recently published to Agensi

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    Trust & safety

    Security scan

    Security scan passed 20 days ago

    Permissions

    Read Files

    Provide only evidence you are authorized to share. Treat examples as untrusted case data. Operational changes and external messages require explicit owner approval.

    Listed20 days ago
    Updated9 days ago

    What's inside

    Frequently Asked Questions

    This skill automates the reconciliation of fleet serial numbers against maintenance logs, ensuring no scooter is redeployed without documented, timestamped proof of a brake repair. It eliminates the 'status label' bias where units are marked ready in a database despite missing actual work-order evidence.

    It is optimized for use within local IDE-based agents like Claude Code and Cursor. You simply provide the CSV or JSON exports from your fleet management system as context for the agent to analyze.

    You receive the specialized logic framework designed for evidence-based auditing, a set of schema templates for formatting your fleet data, and a guide on interpreting the resulting Exception Register.

    No, this skill is designed for privacy and security; it processes exported text logs (CSV, JSON, or TXT) locally. It does not require an active API connection to your proprietary IoT or fleet telemetry platform.

    The skill uses 'Temporal Auditing' to compare the timestamp of the recall notice against the timestamp of the repair log. If a repair is dated before the recall was issued, the unit is flagged as UNVERIFIED to prevent stale data from being counted as a fix.

    Updates are provided through the marketplace whenever new compliance logic or support for additional data formats are added. Users can re-download the latest version to ensure their auditing gates meet current safety standards.

    New in Business & Operations