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    Legacy Banking Infrastructure Support Skill

    Legacy Banking Infrastructure Support Skill

    by Shandra

    Creates structured troubleshooting runbooks for legacy banking systems with incident classification, dependency mapping, log review checklists, escalation paths, rollback guidance, and post-incident summaries.

    Updated Jun 2026
    Security scanned
    Compatible with ChatGPT Custom GPTs

    $50

    · or 250 credits

    30-day refund guarantee

    Secure checkout via Stripe

    Included in download

    • Convert legacy engineer notes into structured support runbooks
    • Map complex dependencies between payment gateways and settlement engines
    • file_write, file_read automation included
    • Ready for Compatible with ChatGPT Custom GPTs
    • Instant install

    Sample input

    Create a runbook for a recurring overnight batch job failure in a legacy core banking environment. Include severity classification, dependency mapping, evidence collection, log review checklist, decision tree, escalation path, rollback/rerun guidance, data integrity checks, communication templates, post-resolution checks, and post-incident summary template. Do not include commands or unauthorized production actions.

    Sample output

    === LEGACY BANKING INCIDENT RUNBOOK ===

    Runbook title: Overnight Core Banking Batch Job Failure Runbook

    System/capability: Core banking batch processing

    Purpose: Provide structured triage for recurring overnight batch failures that may affect account updates, downstream reconciliation, reporting, and start-of-day operations.

    Scope: Included:

    • batch failure classification
    • predecessor and successor job review
    • input/output file checks
    • log review checklist
    • escalation path
    • rerun decision support
    • downstream impact checks
    • post-incident summary

    Out of scope:

    • unauthorized reruns
    • direct database edits
    • ledger corrections
    • production changes without approval
    • final decision to rerun or rollback

    Severity model: SEV-1: Batch failure affects core ledger, account balances, settlement, or regulatory deadline.

    SEV-2: Batch failure threatens start-of-day operations or downstream reconciliation deadline.

    SEV-3: Batch failure is isolated and can be corrected within SLA.

    Incident triggers:

    • job fails with non-zero return code
    • job exceeds runtime threshold
    • predecessor job missing
    • input file missing
    • output control totals mismatch
    • downstream reconciliation job blocked
    • repeated failure across multiple nights

    Initial triage:

    1. Confirm job name, job ID, and environment.
    2. Confirm first failure timestamp.
    3. Check predecessor jobs.
    4. Check input file arrival.
    5. Check control totals if applicable.
    6. Check whether downstream settlement/reconciliation/reporting deadlines are at risk.
    7. Check recent changes to batch schedule, job parameters, database, files, or vendor feed.
    8. Preserve logs before retry or rerun.

    Dependency map: Primary job: [Batch job name]

    Upstream dependencies:

    • source transaction files
    • prior posting jobs
    • vendor file transfer
    • scheduler calendar

    Downstream dependencies:

    • reconciliation job
    • general ledger interface
    • regulatory reporting feed
    • customer statement generation
    • start-of-day availability

    Evidence to collect:

    • job ID
    • job start/end time
    • return code
    • scheduler log
    • application log
    • file arrival timestamp
    • input file size/control total
    • rejected records summary with sensitive data masked
    • downstream blocked jobs
    • recent change record
    • prior incident reference

    Log review checklist: Application/batch logs:

    • first error
    • repeated error pattern
    • rejected record count
    • file format errors
    • timeout errors
    • dependency unavailable

    Scheduler logs:

    • predecessor completion
    • job calendar
    • retry attempts
    • resource constraints

    Database metrics:

    • locks
    • connection pool
    • storage
    • deadlocks
    • long-running queries

    Decision tree: IF input file is missing: Check file transfer status. Check vendor delivery confirmation. Escalate to file transfer/vendor owner if not delivered.

    IF input file arrived but job rejected records: Review rejection summary. Mask sensitive data. Identify common rejection pattern. Escalate to application owner or source-system owner.

    IF predecessor job failed: Follow predecessor job runbook. Do not rerun current job until dependency is resolved.

    IF downstream deadline is at risk: Escalate to major incident process and business owner.

    IF rerun is considered: Confirm approval, data integrity impact, duplicate-processing risk, and downstream communication.

    Escalation path: Incident commander: [Major incident lead if SEV-1/SEV-2]

    Batch operations: [Team/contact]

    Application owner: [Team/contact]

    Database owner: [Team/contact]

    File transfer/vendor owner: [Team/contact]

    Business owner: [Operations/reconciliation owner]

    Compliance/regulatory contact: [If deadline or reporting risk exists]

    Rollback/rerun decision guidance: Rollback or rerun must be approved by authorized operations and application owners. Before rerun, confirm duplicate-processing risk, input file integrity, downstream status, and reconciliation impact.

    Workaround assessment: Manual processing may require dual control, audit record, business approval, and reconciliation plan.

    Data integrity checks:

    • duplicate transactions?
    • missing transactions?
    • partial processing?
    • control totals match?
    • ledger affected?
    • downstream reconciliation affected?

    Communication templates: Technical update: Batch job [name] failed at [time] with [return code]. Initial impact assessment: [impact]. Evidence collected: [evidence]. Current owner: [owner]. Next update: [time].

    Business update: Overnight batch processing for [capability] is delayed. Current known impact: [impact]. Reconciliation/settlement deadline risk: [risk]. Next update: [time].

    Post-resolution checks:

    • job completed successfully
    • downstream jobs resumed
    • control totals verified
    • reconciliation checks passed
    • business owner notified
    • incident record updated

    Post-incident summary template: Incident ID: Job: Timeline: Root cause: Impact: Resolution: Approvals: Data integrity checks: Action items: Runbook updates:

    Owner and review cadence: Batch operations owner. Review quarterly or after any SEV-1/SEV-2 batch incident.

    About This Skill

    Legacy Banking Infrastructure Support Skill helps banks, fintech vendors, enterprise IT support teams, SRE teams, operations managers, and legacy-system consultants turn scattered operational knowledge into structured support runbooks. It creates incident classification workflows, dependency maps, log review checklists, escalation paths, rollback and rerun decision guidance, workaround assessments, data integrity checks, post-incident review templates, support readiness audits, knowledge-base articles, and recurring ticket pattern analyses for core banking, payments, cards, ATM, settlement, reconciliation, online banking, batch processing, middleware, file transfer, database, vendor, and regulatory reporting environments. The skill is designed to preserve institutional knowledge, reduce support workload, improve incident response consistency, and produce audit-ready support documentation without executing production actions.

    Use Cases

    • Convert legacy engineer notes into structured support runbooks
    • Map complex dependencies between payment gateways and settlement engines
    • Generate audit-ready post-incident summaries for banking regulators
    • Standardize shift handoffs for core-banking infrastructure teams

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    Security Scanned

    Passed automated security review

    Permissions

    Write Files
    Read Files

    File Scopes

    *.md
    *.txt
    *.docx
    *.pdf
    *.rtf
    *.csv
    *.xlsx
    *.json
    *.yaml
    *.yml
    *.log
    README.md
    runbooks/**
    incidents/**
    tickets/**
    logs/**
    architecture/**
    dependencies/**
    batch/**
    payments/**
    cards/**
    atm/**
    settlement/**
    reconciliation/**
    core-banking/**
    online-banking/**
    vendors/**
    escalations/**
    changes/**
    post-incident/**
    knowledge-base/**
    docs/**

    This skill uses file access to read user-provided runbooks, support tickets, sanitized logs, architecture diagrams, dependency notes, batch schedules, escalation matrices, vendor notes, incident summaries, monitoring summaries, change records, post-incident reviews, and internal documentation. It uses write access to create structured Markdown/text outputs such as legacy banking incident runbooks, triage reports, dependency maps, log review checklists, escalation paths, rollback and rerun decision checklists, workaround assessments, post-incident review summaries, knowledge-base articles, support readiness audits, recurring ticket analyses, and SKILL.md files. Browser access is optional and should only be used for public documentation research when explicitly requested. The default safe setup does not require network access, shell access, environment variable access, direct production access, database access, payment-system access, or secret access.

    Compatible with ChatGPT Custom GPTs, ChatGPT Agents, Claude-style workflows, Cursor, Claude Code, Codex CLI, OpenCode, Replit, enterprise IT support workflows, banking operations documentation, incident management systems, knowledge-base workflows, and other AI agent systems that support structured Markdown instruction files such as SKILL.md. It can also be used manually in any AI chat by pasting the instructions. For real banking operations, use only authorized internal documentation, sanitized logs, approved support procedures, and human approval for production actions.

    Creator

    Shandra is a top-ranked AI prompt creator and premium agent skill builder with an established track record in the AI marketplace. She is recognized as a #1 Top Seller on PromptBase, where she has built a trusted catalog of specialized AI prompts and agent skills for creators, entrepreneurs, educators, marketers, digital product sellers, and business professionals. With over 3,000 AI products published, more than 3,000 sales, and 1,000+ five-star reviews, Shandra has become known for creating practical, polished, and commercially useful AI resources that help users save time, organize complex ideas, generate high-quality content, build digital products, and transform creative concepts into actionable workflows. Her Agensi store focuses on premium, ready-to-use agent skills designed for real-world productivity. Each skill is developed with clear instructions, structured workflows, professional formatting, practical use cases, setup guidance, examples, edge-case handling, and a strong emphasis on usability. Her work combines creative strategy, prompt engineering, documentation design, business thinking, and practical automation into reliable tools that users can apply immediately. Shandra’s mission is to create AI skills that feel professional, useful, and complete from the first use — not generic templates, but carefully built workflow systems that help users think better, work faster, and produce stronger results.

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