graph-engineering

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Use when a workflow has explicit data dependencies, independently executable branches, typed joins, or node-local recovery needs that justify a bounded static dependency graph.

AI & Automation 123 stars 18 forks Updated 3 days ago MIT

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100
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Skill Content

# Graph Engineering <skill_contract> <input>A dependency-heavy objective with candidate nodes, data schemas, owners, effects, verifiers, joins, budgets, and durable state paths.</input> <output>A validated static DAG contract with typed edges, explicit joins, node-local recovery, and graph-level receipts.</output> <done>Static invariants and terminal acceptance checks pass with fresh node, join, budget, permission, and state evidence.</done> <non_goals>Temporal loop design, worker-team command, runtime-kernel implementation, dynamic graphs, or universal parallelism.</non_goals> Use Graph Engineering for dependency width. Use `loop-engineering` for repeated execution through time, `agent-teams-command` for process ownership and IPC, and `harness-engineering` for scheduler, permission, lease, and observability infrastructure. A graph node may contain a bounded Loop or Agent Team. ## Usage Template Provide: objective/non-goals, candidate nodes, real data dependencies, payload schemas, owners and write territories, join semantics, node/terminal verifiers, effects and permissions, artifact/state paths, budgets, stop conditions, and recovery. Load `references/graph-contract.md` for the full schema and boundary; start from `references/diamond-graph-example.json`. ## Workflow <intake> Run the admission gate before drawing a graph: 1. Identify which steps actually consume another step's output. 2. Estimate independent width, critical path, scheduler overhead, and revie...

Details

Author
Mark393295827
Repository
Mark393295827/third-brain-v5-skills
Created
2 months ago
Last Updated
3 days ago
Language
HTML
License
MIT

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