More screenshots

    Works with the AI Agents you already use

    Claude CodeClaude CodeCursorCursorCodex CLICodex CLIDeepSeekDeepSeekMuseMuse+22 more

    Repair Kafka Connect Offset Topic Partition Drift

    1

    Diagnose connector restarts and skipped partitions after offset topic repartitioning

    $1

    Secure checkout via Stripe

    Money-back guarantee

    Converts to your local currency at checkout

    Security scanned
    Repair Kafka Connect Offset Topic Partition Drift

    Repair Kafka Connect Offset Topic Partition Drift

    Example session with this skill installed

    A Kafka Connect upgrade changed internal topic settings and tasks restart without stable progress.

    Available evidence: Primary network source records and Time-stamped review evidence (partial extracts only). Additional sources requested: Policy / configuration governing partition 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 repair kafka connect

    Repair Kafka Connect Offset Topic Partition Drift — EVIDENCE-LIMITED REVIEW

    Scenario received

    A Kafka Connect upgrade changed internal topic settings and tasks restart without stable progress.

    Source register

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

    Case-specific review checkpoints

    Review internal topic replication and partition counts — 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.

    Compare connector offsets and task IDs — 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.

    Trace rebalance and commit failures — NEEDS_VERIFICATION. Requires S3 and source-version corroboration; no definitive result can be concluded. Owner sign-off required before consequential remediation.
    4.

    Plan reversible migration safeguards — NEEDS_VERIFICATION. Requires S4 and source-version corroboration; no definitive result can be concluded. Owner sign-off required before consequential remediation.

    Structured deliverables

    Offset continuity map — proposed schema with source IDs, timestamps, conflicting observations, confidence and unresolved questions.

    Connector failure timeline — proposed schema with source IDs, timestamps, conflicting observations, confidence and unresolved questions.

    Rollback or rebootstrap gate — 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 partition and Owner authorizations and historical change log, source IDs for S1/S2, responsible owner and effective review window.

    Boundaries and sign-off

    The offset continuity map and connector failure timeline 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

    Kafka Connect clusters often fail silently or enter restart loops after internal topic repartitioning. This skill provides a structured diagnostic framework to identify offset drift, task ID mismatches, and rebalance failures without risking production stability. It moves beyond generic log tailing by enforcing a rigorous evidence-based analysis of internal topic states.

    What it does

    • Map offset continuity by tracing records across old and new partition counts to identify gaps.
    • Analyze task ID mismatches to detect when connectors fail to claim specific partitions.
    • Trace rebalance failures by auditing commit logs for group coordinator timeouts.
    • Evaluate replication health between internal offset, config, and status topics.
    • Generate migration safeguards including specific rollback gates and re-bootstrapping plans.

    How it works

    1. Source Registration where the operator provides time-stamped log evidence and partition configurations.
    2. Fact Checkpointing to compare observed task IDs against internal offset topic records.
    3. Discrepancy Identification where the agent calculates confidence levels for specific failure modes.
    4. Deliverable Synthesis to output a structured continuity map and failure timeline.

    Frameworks & tools

    This skill is designed for Kafka Connect, Apache Kafka internal topics, and distributed stream processing architectures. It requires access to connector logs and topic metadata outputs.

    Why this beats prompting it yourself

    Generic prompts often hallucinate the cause of partition drift or miss subtle task ID overlaps. This skill enforces a deterministic report structure that requires evidence anchors for every finding, preventing false positives in complex distributed systems.

    Use cases

    • Diagnose why connectors restart continuously after an offset topic change.
    • Identify skipped partitions during a cluster migration or upgrade.
    • Audit offset topic health before a high-stakes production repartitioning.
    • Create a reversible migration plan for Kafka internal topic maintenance.

    Known limitations

    This skill provides analysis and technical evidence only. It cannot execute production changes, modify Kafka configurations, or access live clusters directly.

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

    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.

    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 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 provides a diagnostic framework to identify the root cause of connector restart loops and partition gaps that occur specifically when internal offset topics are resized or migrated.

    The skill is compatible with major AI agents and LLMs; it functions by analyzing your provided log exports, topic metadata, and partition configurations rather than requiring a direct plugin.

    You receive a structured diagnostic logic set, evidence-based reporting templates, and a step-by-step framework for mapping offset continuity and task ID mismatches.

    No, this is a read-only diagnostic tool designed for safety; it analyzes your logs and metadata to provide a recovery plan without ever accessing or modifying your live production cluster.

    Standard LLM prompting often misses subtle task ID overlaps in distributed systems; this skill uses a deterministic reporting structure that requires evidence anchors, preventing dangerous false positives.

    New in APIs & Backend