incident-ticket-manager

Create and route ad operations incident tickets for Meta (Facebook/Instagram), Google Ads, TikTok Ads, and multi-platform campaign failures.

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Install skill "incident-ticket-manager" with this command: npx skills add danyangliu-sandwichlab/incident-ticket-manager

Ads Incident Tickets

Purpose

Core mission:

  • incident capture, severity classification, owner routing

This skill is specialized for advertising workflows and should output actionable plans rather than generic advice.

When To Trigger

Use this skill when the user asks for:

  • ad execution guidance tied to business outcomes
  • growth decisions involving revenue, roas, cpa, or budget efficiency
  • platform-level actions for: Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads
  • this specific capability: incident capture, severity classification, owner routing

High-signal keywords:

  • ads, advertising, campaign, growth, revenue, profit
  • roas, cpa, roi, budget, bidding, traffic, conversion, funnel
  • meta, googleads, tiktokads, youtubeads, amazonads, shopifyads, dsp

Input Contract

Required:

  • entity_ids: account, campaign, adset, or ad identifiers
  • incident_or_audit_scope
  • time_window

Optional:

  • logs_or_events
  • policy_flags
  • alert_thresholds
  • owner_contacts

Output Contract

  1. Operational Status Summary
  2. Severity-ranked Findings
  3. Mitigation Actions
  4. Escalation Ticket Payload
  5. Monitoring Checklist

Workflow

  1. Confirm operational scope and impacted entities.
  2. Validate data freshness and event completeness.
  3. Detect anomalies, policy flags, or setup gaps.
  4. Rank fixes by spend risk and recovery speed.
  5. Emit owner-ready action and ticket payload.

Decision Rules

  • If data is stale, block final judgement and request refresh timestamp.
  • If high-severity risk is found, recommend containment action first.
  • If root cause is uncertain, provide top hypotheses with validation order.

Platform Notes

Primary scope:

  • Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads

Platform behavior guidance:

  • Keep recommendations channel-aware; do not collapse all channels into one generic plan.
  • For Meta and TikTok Ads, prioritize creative testing cadence.
  • For Google Ads and Amazon Ads, prioritize demand-capture and query/listing intent.
  • For DSP/programmatic, prioritize audience control and frequency governance.

Constraints And Guardrails

  • Never fabricate metrics or policy outcomes.
  • Separate observed facts from assumptions.
  • Use measurable language for each proposed action.
  • Include at least one rollback or stop-loss condition when spend risk exists.

Failure Handling And Escalation

  • If critical inputs are missing, ask for only the minimum required fields.
  • If platform constraints conflict, show trade-offs and a safe default.
  • If confidence is low, mark it explicitly and provide a validation checklist.
  • If high-risk issues appear (policy, billing, tracking breakage), escalate with a structured handoff payload.

Code Examples

Incident Ticket Example

ticket_id: INC-ads-001
severity: high
impact: spend_waste_risk
owner: media-ops
next_check_at: 2026-03-03T10:00:00Z

Health Rule Example

rule: delivery_drop
condition: impressions_down_pct > 40
action: alert_and_pause_review

Examples

Example 1: Pixel breakage before launch

Input:

  • Purchase event missing
  • Campaign start in 24h

Output focus:

  • severity ranking
  • immediate mitigation
  • relaunch checklist

Example 2: Account health audit

Input:

  • Multiple platform accounts
  • Unknown policy or billing status

Output focus:

  • readiness scorecard
  • blocking risks
  • owner-level actions

Example 3: Live anomaly handling

Input:

  • Spend spikes with no conversion lift
  • Multiple campaigns impacted

Output focus:

  • anomaly triage path
  • containment actions
  • incident ticket payload

Quality Checklist

  • Required sections are complete and non-empty
  • Trigger keywords include at least 3 registry terms
  • Input and output contracts are operationally testable
  • Workflow and decision rules are capability-specific
  • Platform references are explicit and concrete
  • At least 3 practical examples are included

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