Knuckles-Team Slippage Analysis Workflow
Compose the named atomic skills without adding new slippage math here.
Inputs
Provide the strategy definition, asset universe, and execution window.
Steps
Step 0: quant-data-ingest [skill: quant-data-ingest]
Invoke $quant-data-ingest with the workflow inputs to ingest
reference market prices for the universe and window.
Expected: normalized_market_dataset
Step 1: freqtrade-executor [skill: freqtrade-executor] [depends_on: Step 0]
Invoke $freqtrade-executor with normalized_market_dataset and the
strategy definition to paper-trade and capture the fill/slippage report.
Expected: execution_report
Output
Return normalized_market_dataset and execution_report, whose fills carry the
slippage evidence. Only paper-trades; never places live orders.
Execution
- Run first: Step 0 —
$quant-data-ingest. - After level 0: Step 1 —
$freqtrade-executor.
Execution: If graph-os is reachable, offload the whole DAG via graph_orchestrate action=execute_workflow (or the kg-delegate skill) for true parallel/swarm execution. Otherwise execute the steps natively in dependency order: run steps with no unmet depends_on in parallel, then their dependents.