U0598 Observability Training Curriculum Composer

Observability Training Curriculum Composer

Why This Skill Exists

We need this skill because decisions are only as good as the quality and visibility of data. This specific skill converts capability gaps into actionable upskilling programs.

When To Use

Use this skill when the request explicitly needs "Observability Training Curriculum Composer" outcomes in the Data Quality and Observability domain.

Step-by-Step Implementation Guide

1. Define the scope and success metrics for Observability Training Curriculum Composer, including at least three measurable KPIs tied to data drift and blind spots.
2. Design and version the input/output contract for freshness, drift, schema health, and telemetry coverage, then add schema validation and failure-mode handling.
3. Implement the core capability using sequenced learning path design, and produce role-specific curricula with deterministic scoring.
4. Integrate the skill into swarm orchestration: task routing, approval gates, retry strategy, and rollback controls.
5. Add unit, integration, and simulation tests that explicitly cover data drift and blind spots, then run regression baselines.
6. Deploy behind a feature flag, monitor telemetry/alerts for two release cycles, and iterate thresholds based on observed outcomes.

Required Deliverables

• Capability contract: input schema, deterministic scoring, output schema, and failure modes.
• Runtime profile: general-capability using sequenced learning path design to produce role-specific curricula.
• Orchestration integration: data-quality-and-observability:general-capability routing, approval gates, retries, and rollback controls.
• Validation evidence: unit, integration, simulation, regression-baseline suites and rollout telemetry.

Operational Runbook

Preflight

• Confirm the Observability Training Curriculum Composer request scope, source evidence, and measurable success criteria before execution.
• Verify feature flag skill_0598_observability-training-curriculu, approval gates, and rollback owner before autonomous use.

Execution

• Execute sequenced learning path design with deterministic scoring and reproducible trace capture.
• Produce role-specific curricula plus scorecard, assumptions, and unresolved-risk notes.

Recovery

• Fail closed when required signals, evidence, or approval gates are missing.
• Rollback to the last stable baseline when posture is critical or validation fails.

Handoff

• Publish role-specific curricula, validation evidence, and telemetry links to downstream owners.
• Queue follow-up tasks for unresolved risks, threshold tuning, or approval review.

Guardrails

• [quality] Require deterministic scoring and validation evidence before promotion.
• [reliability] Preserve retries, rollback controls, and failure-mode evidence for every run.
• [safety] Route critical posture or missing approval gates to human review before autonomous action.