| name | parallel-infrastructure |
| description | Shared parallel execution infrastructure: DAG scheduling, review dispatch, consensus synthesis, scope checking |
| category | Infrastructure |
| tags | ["parallel","infrastructure","dag","review","consensus"] |
| user_invocable | false |
Parallel Infrastructure
Non-user-invocable infrastructure skill providing shared scripts for parallel execution workflows. Used by implement-feature, autopilot, fix-scrub, merge-pull-requests, and other skills that need DAG scheduling, multi-vendor review dispatch, or consensus synthesis.
Scripts
scripts/dag_scheduler.py
DAG computation and topological sort for work-packages.yaml.
scripts/scope_checker.py
Post-execution scope verification — checks that agent changes stayed within declared write_allow / deny boundaries.
scripts/package_executor.py
Work package execution protocol for coordinated-tier worker agents.
scripts/review_dispatcher.py
Multi-vendor review dispatch — sends review prompts to configured vendor CLIs and collects findings.
scripts/consensus_synthesizer.py
Synthesizes review findings from multiple vendors into a consensus report with confirmed/unconfirmed/disagreement classifications.
scripts/integration_orchestrator.py
Cross-package integration management — tracks package completion, consensus recording, and integration gating.
scripts/result_validator.py
Validates work-queue results against work-queue-result.schema.json.
scripts/circuit_breaker.py
Fault tolerance for external service calls with configurable thresholds.
scripts/escalation_handler.py
Escalation protocol for scope violations, resource conflicts, and review disagreements.
Usage
Other skills reference these scripts via relative path:
python3 "<skill-base-dir>/../parallel-infrastructure/scripts/review_dispatcher.py" [args]
Or import programmatically:
import sys, os
scripts_dir = os.path.join(os.path.dirname(__file__), "..", "..", "parallel-infrastructure", "scripts")
sys.path.insert(0, scripts_dir)
from review_dispatcher import ReviewOrchestrator
from consensus_synthesizer import ConsensusSynthesizer
