- name:
- arifos-plan-dag
- description:
- Build multi-step execution graphs, dependency-aware subtasks, checkpoints, and rollback points. Load when tasks exceed one-shot prompting and need subagent or staged execution.
- version:
- 1.0.0
arifos-plan-dag (O_Ω Orchestration Layer)
Purpose
Build multi-step execution graphs, coordinate dependency-aware subtasks, establish checkpoints, and define rollback boundaries.
Use When
- A complex user request requires multi-step orchestration that cannot be solved in a single turn.
- Generating a structured task list (
task.md) that requires mapping explicit parent-child task nodes.
- Spawning and coordinating multiple parallel subagent runs (e.g. baseline vs variant evaluations).
- Defining safe execution checkpoints and rollback points for highly sensitive workspace mutations.
- Annotating plan nodes with specific L2 skills required and verification criteria expected.
Do Not Use When
- Executing a minor, simple task that requires less than 3 sequential commands or edits.
- Compiling quantitative traces of past executions (use
arifos-evals or arifos-observability instead).
- The task requires structural changes to a specific tool's internal database code.
Inputs
- Complex Intent: The user's multi-dimensional request payload.
- Skill Registry: Mapping of active L2 skills and their dependencies.
- System Constraints: Active token envelopes, step counts, and timing budgets.
Procedure
- DAG Generation: Breakdown the complex request into discrete task nodes. Map explicit dependencies (edges) between them.
- Node Annotation: For each task node, specify:
- Assigned Substrate: The specific tool, script, or L2 skill that will execute this node.
- Inputs/Outputs: Mapped parameters and expected file schemas.
- Verification Criteria: Observable postconditions required to pass the node.
- Governance Inspection: Query
arifos-governance to scan the planned DAG. Automatically insert 888_HOLD pause blocks at high-risk nodes (e.g., destructive commands or deployments).
- Sequential/Parallel Execution: Coordinate execution of independent nodes in parallel, while forcing dependent nodes to execute in order.
- Checkpoint Management: Before executing a node with a high risk score, create an automatic checkpoint (git branch, database backup, or local directory snapshot).
- Rollback Routing: If a node verification fails, immediately trigger a rollback to the closest parent checkpoint, log the failure, and degrade to safe mode.
Postconditions
- A complete directed acyclic graph (PlanDAG) is mapped and validated.
- High-risk nodes are successfully gated by verified governance approvals.
- State transitions are guaranteed to rollback cleanly if subsequent nodes fail.
Failure Modes & Escalation
- Dependency Loop: The generated DAG contains a circular dependency (e.g. Node A depends on B, which depends on A). Action: Break loop immediately, restructure into linear phases, and log warning.
- State Drift: A rollback fails to restore the workspace to the exact checkpoint state. Action: Refuse to proceed, enter hard
888_HOLD mode, write ERR_DAG_STATE_DRIFT, and alert the Sovereign.
Telemetry per Run
{
"skill_name": "arifos-plan-dag",
"version": "1.0.0",
"trigger_phrase": "{{trigger_phrase}}",
"selected_reason": "{{selected_reason}}",
"latency_ms": 0,
"token_in": 0,
"token_out": 0,
"commands_run": 0,
"artifacts_written": 1,
"postcondition_pass": false,
"human_approval_required": false,
"hold_code": "{{hold_code}}"
}
Recursive Scorecard
- Activation Precision: [0.0 - 1.0] (Target: >0.95)
- Task Completion Rate: [0.0 - 1.0] (Target: >0.98)
- Rollback Safety: [0.0 - 1.0] (Target: 1.00)
- Context Efficiency: [0.0 - 1.0] (Target: >0.90)
- Doc Freshness: [0.0 - 1.0] (Target: 1.00)
- Cross-Skill Collision Rate: [0.0 - 1.0] (Target: <0.02)
- Human Trust Score: [0.0 - 1.0] (Target: >0.98)