The workflowCost function had includeCompleted defaulting to true, but
the api-surface.md specifies the default should be false. Fixed the
default and updated test suite to verify the correct default behavior
and add explicit test for includeCompleted: true opt-in case.
All 562 tests passing across 12 test files.
Implement computeEffectiveP internal helper and workflowCost public function
that captures the structural reality that upstream failures multiply downstream
damage, per ADR-004 and the Python research model.
- computeEffectiveP: computes pEffective from intrinsic probability + upstream
propagation using inherited quality factors (parentP + (1-parentP) × qualityRetention)
- workflowCost: processes tasks in topological order, computes per-task EV with
degraded effective probability, includes pIntrinsic/pEffective split
- Supports independent and dag-propagate modes
- Completed tasks excluded from results but propagate p=1.0 when includeCompleted: false
- Per-edge qualityRetention overrides defaultQualityRetention option
- Throws CircularDependencyError for cyclic graphs via topologicalOrder
- 30+ new tests covering chain compounding, diamond graph, mode comparison,
completed task semantics, cycle detection, per-edge qualityRetention
Implement the core EV calculation: EV = p*C_success + (1-p)*C_fail
where C_success = scopeCost*impactWeight, C_fail = scopeCost*impactWeight + fallbackCost + timeLost*expectedRetries.
- expectedRetries = (1-p)/p when p>0, else 0 (geometric series)
- Caps expectedRetries at config.retries when retries > 0
- Multiplies final EV by config.valueRate when non-zero
- 30 unit tests covering formula, edge cases, and Python research model values
