ceap-enterprise-context

name	ceap-enterprise-context
description	Use for CEAP enterprise context aggregation, engineering memory, knowledge graphs, cross-system analysis, integrations, D365 or ERP context, documentation intelligence, and workflow observation.

CEAP Enterprise Context

Use this skill when the task depends on organizational context across repositories, tickets, documents, communication, logs, or enterprise systems.

Workflow

1. Define context boundaries.

   • Identify which systems matter: repositories, tickets, PRs, docs, logs, Teams, SharePoint, Confluence, Jira, Azure DevOps, GitHub, ServiceNow, ERP, D365, observability, cloud, or CI/CD.
   • Capture privacy, governance, tenant, and retention constraints before using sensitive sources.

2. Build a context graph.

   • Connect tickets, code, APIs, services, data flows, incidents, deployments, architectural decisions, and historical reviews.
   • Reuse existing engineering memory, playbooks, team conventions, and recurring solution patterns.
   • Distinguish verified facts from inferred relationships.

3. Analyze cross-system impact.

   • Look for dependency chains, integration contracts, critical paths, hidden process coupling, recurring failure patterns, and operational risk.
   • Correlate tickets, logs, incidents, PRs, and documentation.
   • Surface gaps where missing data prevents a confident recommendation.

4. Produce reusable memory.

   • Summarize durable decisions, patterns, root causes, and playbooks in a form that can be reused.
   • Avoid storing secrets, unnecessary personal data, or unapproved sensitive details.

Feature Coverage

• Engineering memory, long-term context, knowledge graphs, semantic search, document analysis, and context compression
• Historical PR and review analysis, team-convention learning, architecture decision history, incident correlation, and reusable playbooks
• GitHub, Azure DevOps, Jira, ServiceNow, Teams, SharePoint, Confluence, D365, ERP, SIEM, CI/CD, MCP, GitLab, Kubernetes, Docker, cloud, observability, SAP, REST, GraphQL, event streaming, OpenTelemetry, LangGraph, and LangChain integrations
• Workflow observation, IDE activity analysis, build and debugging detection, browser-context analysis, OCR-based screen analysis, pattern extraction, process mining, and productivity analysis

Output Shape

Return:

• Context sources used
• Verified facts
• Inferred relationships
• Impact map
• Missing context
• Reusable memory entries