sla plugins

by Claude Code Plugins

Track SLAs, SLIs, and SLOs for service reliability

by Claude Code Plugins

Track SLAs, SLIs, and SLOs for service reliability

by Claude Code Plugins

Track SLAs, SLIs, and SLOs for service reliability

by Matt Corbett

Field-service management & dispatch operations specialist team — agents covering the service operating model (SLAs, contracts, dispatch-to-cash), dispatch & scheduling (skill/SLA/geo optimization, emergency vs planned), technician productivity (utilization, first-time-fix, MTTR, callbacks), and parts & inventory (truck stock, service-level tradeoffs, returns). Ships skills (dispatch-and-scheduling, technician-productivity-and-first-time-fix, truck-stock-and-parts), commands, templates, best-practices, a decision-tree knowledge bank, and an advisory hook flagging FSM anti-patterns. Domain: HVAC, plumbing, elevator, medical-device service. Inherits ravenclaude-core protocols.

by Matt Corbett

IT Service Management (ITIL 4) team — agents (service-management-lead, incident-and-problem-manager, change-and-release-manager, service-desk-and-request-manager) for running IT as a service: the ITIL 4 service value system and practice selection, incident vs problem vs major-incident handling, change enablement (standard/normal/emergency + the CAB) and release management, and the service desk — request fulfillment, SLAs/OLAs, knowledge management, the service catalog, and the CMDB/configuration management. skills, a knowledge bank with Mermaid decision trees + a dated 2026 ITSM tooling map + an ITIL 4 practice reference, best-practices, templates, commands, an advisory hook. Seams: engineering incident response/SRE/observability -> observability-sre, CI/CD release automation -> devops-cicd, security incidents/GRC -> cybersecurity-grc, cloud cost/asset -> finops-cloud-cost. Inherits ravenclaude-core protocols.

by Matt Corbett

Trust & Safety team — agents for content-moderation and abuse-detection work. The trust-safety-policy-lead designs the policy taxonomy + enforcement ladder, the human-review operations layer (queue prioritization, reviewer wellness, escalation, appeals/due-process), and the measurement frame (prevalence, enforcement precision/recall, time-to-action SLA, appeal-overturn rate). The abuse-detection-engineer builds the detection stack: signals, rules-vs-ML classifiers, reviewer queues, thresholds tied to precision/recall. skills, a knowledge bank (a Mermaid enforcement decision tree + a T&S metrics catalogue with formulas), templates, best-practice rules, and an advisory hook. Seams: classifier-eval validity → applied-statistics; PII → data-governance-privacy; account-takeover → security-engineering; LLM-classifier build → claude-app-engineering. Enforcement is proportional; appeals are due process; measure prevalence, not just volume. Requires ravenclaude-core@>=0.7.0.