mark393295827/third-brain-v5-skills/graph-engineering
Claude Code and agent skill by mark393295827/third-brain-v5-skills
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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.
Install
npx vskill@latest install mark393295827/third-brain-v5-skills/graph-engineeringSKILL.md
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:
- Identify which steps actually consume another step's output.
- Estimate independent width, critical path, scheduler overhead, and review
load. Require measurable payback or stronger independent evaluation.
- Keep one-shot or Loop execution when work is mainly sequential, small, or
cheaper to review serially.
- Limit V8.1 to a static DAG: sequence, pipeline, diamond, maker-checker, or
bounded subgraph. Put repetition inside a loop node; reject graph cycles and dynamic expansion.
</intake>
<unknowns_gate>
Return NEEDS_INPUT when objective, graph owner, dependency direction, payload schema, writer, verifier, permission boundary, budget, join, or recovery is missing and cannot be discovered safely. Probe candidate independence with a small dry run. Do not invent an edge merely because two steps are adjacent.
</unknowns_gate>
<execute>
- Write the JSON contract and run
scripts/validate_graph_contract.py <contract.json> --strict.
- Give every node one owner, typed inputs/outputs, explicit reads/writes,
verifier, timeout, attempt/tool caps, effect class, idempotency, and compensation.
- Add only data, control, verification, failure, or compensation edges.
Schema-bearing edges must match both endpoint contracts.
- Enforce one writer per target. Agent workers use isolated artifacts or
worktrees; the integration owner controls shared schemas and final writes.
- Declare a join for every multi-input node. Choose
all,reduce,
first-success, quorum, barrier-verifier, or human-gate; name the exact input set and verifier.
- Schedule only
READYnodes whose dependencies are verified. Persist every
transition and edge payload reference before releasing successors.
- Retry the failed node or smallest invalid subgraph after a changed
diagnosis. Preserve verified branches; never replay the whole graph merely for convenience.
- Require human approval, a compensation route, and verified rollback before
any external, shared, destructive, published, credentialed, or financial effect. In strict contracts, name the external node ID in approval_required, feed it a typed approval receipt directly from a human-gate, and list each exact write target as allowed and not denied.
- At terminal nodes, verify the end-to-end objective and graph guardrails;
node success alone cannot certify graph success.
</execute>
<evaluate>
Check static integrity: known endpoints, compatible schemas, reachability, acyclicity, single writers, complete joins, finite budgets, and compensated effects. Check runtime integrity: deterministic readiness, duplicate-delivery idempotency, checkpoint replay, permission denial without mutation, smallest-unit recovery, terminal evidence, and cleanup. Use an independent reviewer for consequential graph behavior.
</evaluate>
<retry_policy>
max_attempts comes from each node and never exceeds the graph cap. Retry only after changing diagnosis, input, owner, tool, or strategy. Stop on a repeated signature, incompatible edge, permission denial, invalid checkpoint, exhausted review budget, or NO_PROGRESS. Whole-graph retry is forbidden in strict V8.1.
</retry_policy>
<state_contract>
Persist {run_id, graph_id, status, attempt, budget, evidence, unknowns, last_error, next_action} plus contract/implementation hashes, node states, edge payload locators, join decisions, writer leases, approvals, checkpoints, compensations, terminal receipts, and cleanup. Use append-only events and an atomic current checkpoint; chat history is not graph state.
</state_contract>
Failure Protocol
NEEDS_INPUT: a mandatory graph contract or authority field is unresolved.BLOCKED_DEPENDENCY: keep affected nodesWAITING; run only independent
ready nodes.
BLOCKED_PERMISSION: deny the effect, preserve state, and request approval.VERIFY_FAILED: reject the node/join artifact and recover the smallest unit.NO_PROGRESS: the same failure repeats after a changed attempt.
max_attempts: 2 by default and always finite.
BUDGET_STOP: stop scheduling, checkpoint, compensate active effects, and
return a partial graph receipt.
Output Contract
Return status, result (terminal decision and accepted artifacts), evidence (validator, node, join, terminal, budget, approval, and cleanup receipts), unknowns, and next_action (stop, retry node, compensate, approval, or handoff).
Edge Cases
- Two workers both write
report.md: strict validation fails the single-writer
invariant; isolate worker artifacts and let one reduce node own the report.
- A branch passes but its sibling times out: preserve the verified branch,
retry only the failed node within cap, and do not release the join until its declared mode and verifier pass.
Success Metrics
- The strict graph validator passes before execution.
- Graph admission shows bounded value beyond orchestration and review cost.
- Every node, edge, join, effect, and terminal claim has fresh evidence.
- Recovery replays the smallest failed unit from durable state.
Quality Gates
- [ ] Static DAG scope and Loop/Teams/Harness boundaries are explicit.
- [ ] Owners, payload schemas, writers, joins, verifiers, and budgets are exact.
- [ ] State replay and duplicate delivery preserve graph invariants.
- [ ] External effects have independent review, approval, compensation, and rollback.
- [ ] Terminal verification supports the end-to-end claim.
</skill_contract>
Security
- Security scanPassed, 95 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/graph-engineering/SKILL.md
Popularity
- Repository stars
- 133
- Repository forks
- 19
- 7-day trend score
- 24
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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