| license | BSL-1.1 |
| name | windags-mutator |
| description | Failure diagnosis, DAG mutation, and escalation engine for the WinDAGs meta-DAG. Receives failure information and quality vectors from the Evaluator. Classifies failures on four dimensions. Follows a five-level escalation ladder. Applies seven mutation types with saga compensation. Enforces BC-EXEC-002, BC-EXEC-003, BC-FAIL-002, BC-FAIL-005. Activate when operating as the Mutator role in the meta-DAG, when diagnosing node failures, when restructuring a DAG at runtime, or when deciding escalation level. |
| metadata | {"tags":["windags","mutator"]} |
| category | Agent & Orchestration |
| tags | ["windags","mutation","dag","evolution","dynamic"] |
WinDAGs Mutator
Receive failure information and quality vectors. Diagnose the problem on four dimensions. Follow the escalation ladder. Apply the smallest mutation that fixes the problem. Log everything. Escalate to human when automated approaches are exhausted.
DECISION POINTS
Primary Mutation Selection Matrix
Given failure classification (Cognitive, Decomposition, Temporal), select optimal mutation type:
IF System=omission AND Temporal=transient
→ loop_back (simple retry)
→ Cost: 1x, Latency: +retry_timeout
IF System=omission AND Temporal=persistent
→ replace_node (different model/skill)
→ Cost: 1x, Latency: +model_switch_time
IF System=crash AND Decomposition=node
→ replace_node OR add_node (gap fill)
→ Cost: 1x-2x, Latency: +mutation_time
IF System=crash AND Decomposition=topology
→ restructure (add_node + remove_node sequence)
→ Cost: 2-4x, Latency: +decomposition_time
IF System=byzantine AND Cognitive=confident_incorrect
→ Cross-family ensemble review → replace_node if confirmed
→ Cost: 2x (review cost), Latency: +review_time + model_switch
Escalation Level Decision Tree
L1 (Fix Node): IF first_failure OR system=crash_recovery
→ Try: different prompt, model tier, or alternative skill
→ Threshold: <3 retries on same node
L2 (Diagnose Structure): IF pattern_matches_decomposition_signature
→ Signatures: granularity_mismatch, semantic_gap, method_explosion
→ Classify on all 4 dimensions
L3 (Generate Alternative): IF retry_count >= 3 OR decomposition_cycles >= 2
→ Apply Polya strategies: restate, simplify, specialize, analogize
→ Generate new DAG variant
L4 (Fix Topology): IF coordination_failure OR L3_mutations_failed
→ Conway-informed restructuring, intermediary agents
→ Trade-off: higher complexity for better isolation
L5 (Human Escalate): IF all_automated_exhausted OR budget_exceeded
→ Package: failure_trace + decomposition_history + recommendations
Circuit Breaker Override Logic
IF node_breaker=OPEN
→ route_around: skip this node, use alternative path
→ Cost: potentially 2-3x if no direct alternative
IF skill_breaker=OPEN AND alternative_skill_available
→ skill_substitution: use backup skill for same task
→ Cost: 1.2x (skill switching overhead)
IF model_breaker=OPEN
→ model_failover: use different provider (Claude→GPT→Gemini)
→ Cost: 1x, Latency: +provider_switch_time
IF multiple_breakers=OPEN
→ escalate_immediately: skip lower escalation levels
FAILURE MODES
1. Rubber Stamp Escalation
Symptom: Every failure immediately escalates to L5 without attempting lower levels.
Detection: IF escalation_level=5 AND previous_levels_attempted=0
Fix: Enforce BC-FAIL-002 ordering. Check escalation ladder prerequisites before each jump.
2. Mutation Thrashing
Symptom: Applying contradictory mutations in rapid succession (add_node then remove_node on same position).
Detection: IF mutation_cycle_count > 3 per wave AND mutations_cancel_each_other
Fix: Implement mutation debouncing. Wait for wave completion before applying inverse mutations.
3. Byzantine Blindness
Symptom: Confident-incorrect failures treated as simple crashes instead of Byzantine.
Detection: IF confidence>0.8 AND downstream_failures_cascade AND system_layer≠byzantine
Fix: Add confidence-accuracy calibration check. Route high-confidence wrong answers through cross-family ensemble.
4. Circuit Breaker Cascade
Symptom: Opening one breaker triggers opening others unnecessarily.
Detection: IF multiple_breakers_open_simultaneously AND failures_unrelated
Fix: Verify BC-FAIL-004 independence. Each breaker must track separate failure domains.
5. Saga Compensation Amnesia
Symptom: Failed mutations leave DAG in inconsistent state without compensation.
Detection: IF mutation_failed AND compensating_action=null AND saga_type=COMPENSATABLE
Fix: Execute reverse compensation immediately. Log limitations honestly if full restoration impossible.
WORKED EXAMPLES
Example 1: Transient Crash → L1 Retry Success
Initial State: Text analysis node crashes with "rate limit exceeded"
Classification: System=crash, Temporal=transient, Decomposition=node
Decision: Apply loop_back mutation (L1)
1. Classify: crash + transient → simple retry eligible
2. Check circuit breakers: node=CLOSED, skill=CLOSED, model=HALF_OPEN
3. Apply mutation: loop_back with 30s delay
4. Log MutationEvent: saga_type=RETRIABLE
5. Re-execute: SUCCESS
6. Quality gate: output passes schema validation
Novice miss: Would escalate immediately instead of trying simple retry.
Expert catch: Recognizes rate limit as transient system issue, not skill problem.
Example 2: Persistent Byzantine → L3 Redecomposition
Initial State: Code review node reports "95% confident, looks good" but code has security vulnerability
Classification: System=byzantine, Cognitive=confident_incorrect, Temporal=persistent
Decision: Cross-family ensemble → L3 redecomposition
1. Detect: High confidence + downstream security test failures
2. L1 retry: FAIL (same confident-incorrect response)
3. L2 structure check: FAIL (edge dependencies correct, node skills correct)
4. Trigger cross-family ensemble: Claude→GPT review
5. Ensemble confirms: original output wrong, confidence miscalibrated
6. L3: Decompose security review as separate specialized node
7. Apply: add_node(security_specialist) + add_edge(code→security)
8. Re-execute: PASS (vulnerability caught by specialist)
Novice miss: Would trust high confidence, miss the Byzantine failure pattern.
Expert catch: Calibrates confidence against historical accuracy, uses ensemble validation.
Example 3: Topology Failure → L4 Restructure with Trade-offs
Initial State: Data pipeline has circular dependency causing deadlock
Classification: System=crash, Decomposition=topology, Temporal=persistent
Decision: Conway-informed restructuring (L4)
1. L1-L3 attempts: FAIL (retries, node swaps, alternative decompositions all hit circular dependency)
2. L4 triggered: topology-level problem identified
3. Analyze: Conway's Law suggests communication structure mismatch
4. Trade-off decision: Add intermediary buffer nodes vs. merge conflicting nodes
- Option A: +2 nodes, +communication overhead, -circular dependency
- Option B: -1 node, +complexity, potential skill capability loss
5. Choose Option A: Better failure isolation despite higher cost
6. Apply: add_node(buffer1) + add_node(buffer2) + restructure edges
7. Circuit breaker update: original failing nodes → HALF_OPEN
8. Re-execute: SUCCESS with 2.1x cost increase
Novice miss: Would try to fix nodes individually, miss structural topology issue.
Expert catch: Recognizes deadlock as Conway's Law problem, accepts cost trade-off for reliability.
QUALITY GATES
NOT-FOR BOUNDARIES
Do NOT use this skill for:
- Initial DAG decomposition → Use
windags-decomposer instead
- Quality vector computation → Use
windags-evaluator instead
- Wave execution planning → Use
windags-executor instead
- Learning from mutation patterns → Use
windags-learning-engine instead
Delegate when:
- L5 escalation reached → Present to human with full context
- Mutation requires new skills → Route to
skill-acquisition system
- Circuit breakers indicate systemic issues → Escalate to
infrastructure-monitoring
- Budget constraints violated → Route to
resource-management for approval
