Orchestrate discretionary knowledge work using CMMN primitives within SEA-Forge.
npx skills add https://github.com/GodSpeedAI/SEA --skill case-management
Please help me install this Agent Skill. Skill: case-management Source: https://github.com/GodSpeedAI/SEA/tree/main/.claude/skills/case-management Command: npx skills add https://github.com/GodSpeedAI/SEA --skill case-management
The skill provides a structured approach to coordinating discretionary, knowledge-intensive work by applying Case Management Model and Notation (CMMN) primitives—Cases, Stages, Tasks, and Artifacts—within SEA-Forge. It enables teams to manage flexible workflows while preserving governance, provenance, and auditable artifact lifecycles.
Create a starter case: define a Case named "case-2026-01" with Stage "Discretionary Discovery", add a first Task "Interview stakeholders" assigned to an AI specialist, and connect a basic lifecycle using the PM-Agent.
High-intent search queries and answers about installing and using this skill.
CMMN workflow orchestration structures discretionary knowledge work using Cases, Stages, Tasks, and Artifacts. It coordinates flexible research and consulting processes while preserving governance, provenance, and auditable artifact lifecycles across project stages.
To create a case, define a Case identifier, add a Stage such as Discretionary Discovery, insert a Task like Interview stakeholders, and connect the workflow using PM-Agent. This establishes a traceable lifecycle from discovery through recommendations.
Use case management for discretionary, knowledge-intensive work that requires flexible governance rather than rigid process flows. It suits research projects and consulting engagements where stages adapt dynamically and auditable artifact transitions are required.
Yes, the skill supports PM-Agent integration to orchestrate hybrid human-AI teams. It manages lifecycle transitions and applies governance gates across stages, ensuring auditable artifact provenance throughout the workflow.
You track artifact lifecycles by modeling transitions from Cognitive artifacts to Intellectual artifacts using CMMN primitives. This pipeline ensures traceable provenance and sovereign gates across stages from discovery to final recommendations.
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