882 lines
21 KiB
Markdown
882 lines
21 KiB
Markdown
# Agent Task Assignments
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## Overview
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Task breakdown for 15-agent swarm implementing the Neural DAG Learning system. Each agent has specific responsibilities, dependencies, and deliverables.
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## Swarm Topology
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```
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┌─────────────────────┐
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│ QUEEN AGENT │
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│ (Coordinator) │
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│ Agent #0 │
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└──────────┬──────────┘
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│
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┌──────────────────────┼──────────────────────┐
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│ │ │
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▼ ▼ ▼
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┌───────────────┐ ┌───────────────┐ ┌───────────────┐
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│ CORE TEAM │ │ POSTGRES TEAM │ │ QUDAG TEAM │
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│ Agents 1-5 │ │ Agents 6-9 │ │ Agents 10-12 │
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└───────────────┘ └───────────────┘ └───────────────┘
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│
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┌──────────┴──────────┐
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▼ ▼
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┌───────────────┐ ┌───────────────┐
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│ TESTING TEAM │ │ DOCS TEAM │
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│ Agents 13-14 │ │ Agent 15 │
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└───────────────┘ └───────────────┘
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```
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## Agent Assignments
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---
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### Agent #0: Queen Coordinator
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**Type**: `queen-coordinator`
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**Role**: Central orchestration, dependency management, conflict resolution
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**Responsibilities**:
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- Monitor all agent progress via memory coordination
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- Resolve cross-team dependencies and conflicts
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- Manage swarm-wide configuration
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- Aggregate status reports
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- Make strategic decisions on implementation order
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- Coordinate code reviews between teams
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**Deliverables**:
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- Swarm coordination logs
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- Dependency resolution decisions
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- Final integration verification
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**Memory Keys**:
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- `swarm/queen/status` - Overall swarm status
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- `swarm/queen/decisions` - Strategic decisions log
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- `swarm/queen/dependencies` - Cross-agent dependency tracking
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**No direct code output** - Coordination only
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---
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### Agent #1: Core DAG Engine
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**Type**: `coder`
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**Role**: Core DAG data structures and algorithms
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**Responsibilities**:
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1. Implement `QueryDag` structure
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2. Implement `OperatorNode` and `OperatorType`
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3. Implement DAG traversal algorithms (topological sort, DFS, BFS)
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4. Implement edge/node management
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5. Implement DAG serialization/deserialization
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**Files to Create/Modify**:
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```
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ruvector-dag/src/
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├── lib.rs
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├── dag/
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│ ├── mod.rs
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│ ├── query_dag.rs
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│ ├── operator_node.rs
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│ ├── traversal.rs
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│ └── serialization.rs
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```
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**Dependencies**: None (foundational)
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**Blocked By**: None
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**Blocks**: Agents 2, 3, 4, 6
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**Deliverables**:
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- [ ] `QueryDag` struct with node/edge management
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- [ ] `OperatorNode` with all operator types
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- [ ] Topological sort implementation
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- [ ] Cycle detection
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- [ ] JSON/binary serialization
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**Estimated Complexity**: Medium
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---
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### Agent #2: Attention Mechanisms (Basic)
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**Type**: `coder`
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**Role**: Implement first 4 attention mechanisms
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**Responsibilities**:
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1. Implement `DagAttention` trait
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2. Implement `TopologicalAttention`
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3. Implement `CausalConeAttention`
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4. Implement `CriticalPathAttention`
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5. Implement `MinCutGatedAttention`
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**Files to Create/Modify**:
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```
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ruvector-dag/src/attention/
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├── mod.rs
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├── traits.rs
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├── topological.rs
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├── causal_cone.rs
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├── critical_path.rs
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└── mincut_gated.rs
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```
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**Dependencies**: Agent #1 (QueryDag)
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**Blocked By**: Agent #1
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**Blocks**: Agents 6, 13
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**Deliverables**:
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- [ ] `DagAttention` trait definition
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- [ ] `TopologicalAttention` with decay
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- [ ] `CausalConeAttention` with temporal awareness
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- [ ] `CriticalPathAttention` with path computation
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- [ ] `MinCutGatedAttention` with flow-based gating
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**Estimated Complexity**: High
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---
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### Agent #3: Attention Mechanisms (Advanced)
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**Type**: `coder`
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**Role**: Implement advanced attention mechanisms
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**Responsibilities**:
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1. Implement `HierarchicalLorentzAttention`
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2. Implement `ParallelBranchAttention`
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3. Implement `TemporalBTSPAttention`
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4. Implement `AttentionSelector` (UCB bandit)
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5. Implement attention caching
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**Files to Create/Modify**:
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```
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ruvector-dag/src/attention/
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├── hierarchical_lorentz.rs
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├── parallel_branch.rs
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├── temporal_btsp.rs
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├── selector.rs
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└── cache.rs
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```
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**Dependencies**: Agent #1 (QueryDag), Agent #2 (DagAttention trait)
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**Blocked By**: Agents #1, #2
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**Blocks**: Agents 6, 13
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**Deliverables**:
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- [ ] `HierarchicalLorentzAttention` with hyperbolic ops
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- [ ] `ParallelBranchAttention` with branch detection
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- [ ] `TemporalBTSPAttention` with eligibility traces
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- [ ] `AttentionSelector` with UCB selection
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- [ ] LRU attention cache
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**Estimated Complexity**: Very High
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---
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### Agent #4: SONA Integration
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**Type**: `coder`
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**Role**: Self-Optimizing Neural Architecture integration
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**Responsibilities**:
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1. Implement `DagSonaEngine`
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2. Implement `MicroLoRA` adaptation
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3. Implement `DagTrajectoryBuffer`
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4. Implement `DagReasoningBank`
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5. Implement `EwcPlusPlus` constraints
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**Files to Create/Modify**:
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```
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ruvector-dag/src/sona/
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├── mod.rs
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├── engine.rs
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├── micro_lora.rs
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├── trajectory.rs
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├── reasoning_bank.rs
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└── ewc.rs
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```
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**Dependencies**: Agent #1 (QueryDag)
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**Blocked By**: Agent #1
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**Blocks**: Agents 6, 7, 13
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**Deliverables**:
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- [ ] `DagSonaEngine` orchestration
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- [ ] `MicroLoRA` rank-2 adaptation (<100μs)
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- [ ] Lock-free trajectory buffer
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- [ ] K-means++ clustering for patterns
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- [ ] EWC++ with Fisher information
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**Estimated Complexity**: Very High
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---
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### Agent #5: MinCut Optimization
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**Type**: `coder`
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**Role**: Subpolynomial min-cut algorithms
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**Responsibilities**:
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1. Implement `DagMinCutEngine`
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2. Implement `LocalKCut` oracle
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3. Implement dynamic update algorithms
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4. Implement bottleneck detection
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5. Implement redundancy suggestions
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**Files to Create/Modify**:
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```
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ruvector-dag/src/mincut/
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├── mod.rs
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├── engine.rs
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├── local_kcut.rs
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├── dynamic_updates.rs
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├── bottleneck.rs
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└── redundancy.rs
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```
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**Dependencies**: Agent #1 (QueryDag)
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**Blocked By**: Agent #1
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**Blocks**: Agent #2 (MinCutGatedAttention), Agent #6
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**Deliverables**:
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- [ ] `DagMinCutEngine` with O(n^0.12) updates
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- [ ] `LocalKCut` oracle implementation
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- [ ] Hierarchical decomposition
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- [ ] Bottleneck scoring algorithm
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- [ ] Redundancy recommendation engine
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**Estimated Complexity**: Very High
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---
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### Agent #6: PostgreSQL Core Integration
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**Type**: `backend-dev`
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**Role**: Core PostgreSQL extension integration
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**Responsibilities**:
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1. Set up pgrx extension structure
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2. Implement GUC variables
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3. Implement global state management
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4. Implement query hooks (planner, executor)
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5. Implement background worker registration
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**Files to Create/Modify**:
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```
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ruvector-postgres/src/dag/
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├── mod.rs
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├── extension.rs
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├── guc.rs
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├── state.rs
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├── hooks.rs
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└── worker.rs
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```
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**Dependencies**: Agents #1-5 (all core components)
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**Blocked By**: Agents #1, #2, #3, #4, #5
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**Blocks**: Agents #7, #8, #9
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**Deliverables**:
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- [ ] Extension scaffolding with pgrx
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- [ ] All GUC variables from spec
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- [ ] Thread-safe global state (DashMap)
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- [ ] Planner hook for DAG analysis
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- [ ] Executor hooks for trajectory capture
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- [ ] Background worker main loop
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**Estimated Complexity**: High
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---
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### Agent #7: PostgreSQL SQL Functions (Part 1)
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**Type**: `backend-dev`
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**Role**: Core SQL function implementations
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**Responsibilities**:
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1. Configuration functions
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2. Query analysis functions
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3. Attention functions
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4. Basic status/health functions
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**Files to Create/Modify**:
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```
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ruvector-postgres/src/dag/
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├── functions/
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│ ├── mod.rs
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│ ├── config.rs
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│ ├── analysis.rs
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│ ├── attention.rs
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│ └── status.rs
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```
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**SQL Functions**:
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- `dag_set_enabled`
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- `dag_set_learning_rate`
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- `dag_set_attention`
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- `dag_configure_sona`
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- `dag_config`
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- `dag_status`
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- `dag_analyze_plan`
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- `dag_critical_path`
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- `dag_bottlenecks`
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- `dag_attention_scores`
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- `dag_attention_matrix`
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**Dependencies**: Agent #6 (PostgreSQL core)
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**Blocked By**: Agent #6
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**Blocks**: Agent #13
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**Deliverables**:
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- [ ] All configuration SQL functions
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- [ ] Query analysis functions
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- [ ] Attention computation functions
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- [ ] Status reporting functions
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**Estimated Complexity**: Medium
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---
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### Agent #8: PostgreSQL SQL Functions (Part 2)
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**Type**: `backend-dev`
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**Role**: Learning and pattern SQL functions
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**Responsibilities**:
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1. Pattern management functions
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2. Trajectory functions
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3. Learning control functions
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4. Self-healing functions
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**Files to Create/Modify**:
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```
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ruvector-postgres/src/dag/
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├── functions/
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│ ├── patterns.rs
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│ ├── trajectories.rs
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│ ├── learning.rs
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│ └── healing.rs
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```
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**SQL Functions**:
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- `dag_store_pattern`
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- `dag_query_patterns`
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- `dag_pattern_clusters`
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- `dag_consolidate_patterns`
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- `dag_record_trajectory`
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- `dag_trajectory_history`
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- `dag_learn_now`
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- `dag_reset_learning`
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- `dag_health_report`
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- `dag_anomalies`
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- `dag_auto_repair`
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**Dependencies**: Agent #6 (PostgreSQL core), Agent #4 (SONA)
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**Blocked By**: Agents #4, #6
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**Blocks**: Agent #13
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**Deliverables**:
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- [ ] Pattern CRUD functions
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- [ ] Trajectory management functions
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- [ ] Learning control functions
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- [ ] Health and healing functions
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**Estimated Complexity**: Medium
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---
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### Agent #9: Self-Healing System
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**Type**: `coder`
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**Role**: Autonomous self-healing implementation
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**Responsibilities**:
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1. Implement `AnomalyDetector`
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2. Implement `IndexHealthChecker`
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3. Implement `LearningDriftDetector`
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4. Implement repair strategies
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5. Implement healing orchestrator
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**Files to Create/Modify**:
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```
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ruvector-dag/src/healing/
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├── mod.rs
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├── anomaly.rs
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├── index_health.rs
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├── drift_detector.rs
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├── strategies.rs
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└── orchestrator.rs
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```
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**Dependencies**: Agent #4 (SONA), Agent #6 (PostgreSQL hooks)
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**Blocked By**: Agents #4, #6
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**Blocks**: Agent #8 (healing SQL functions), Agent #13
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**Deliverables**:
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- [ ] Z-score anomaly detection
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- [ ] HNSW/IVFFlat health monitoring
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- [ ] Pattern drift detection
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- [ ] Repair strategy implementations
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- [ ] Healing loop orchestration
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**Estimated Complexity**: High
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---
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### Agent #10: QuDAG Client
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**Type**: `coder`
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**Role**: QuDAG network client implementation
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**Responsibilities**:
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1. Implement `QuDagClient`
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2. Implement network communication
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3. Implement pattern proposal flow
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4. Implement consensus validation
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5. Implement pattern synchronization
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**Files to Create/Modify**:
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```
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ruvector-dag/src/qudag/
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├── mod.rs
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├── client.rs
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├── network.rs
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├── proposal.rs
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├── consensus.rs
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└── sync.rs
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```
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**Dependencies**: Agent #4 (patterns to propose)
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**Blocked By**: Agent #4
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**Blocks**: Agents #11, #12
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**Deliverables**:
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- [ ] QuDAG network client
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- [ ] Async communication layer
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- [ ] Pattern proposal protocol
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- [ ] Consensus status tracking
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- [ ] Pattern sync mechanism
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**Estimated Complexity**: High
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---
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### Agent #11: QuDAG Cryptography
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**Type**: `security-manager`
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**Role**: Quantum-resistant cryptography
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**Responsibilities**:
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1. Implement ML-KEM-768 wrapper
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2. Implement ML-DSA signature wrapper
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3. Implement identity management
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4. Implement secure key storage
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5. Implement differential privacy for patterns
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**Files to Create/Modify**:
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```
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ruvector-dag/src/qudag/
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├── crypto/
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│ ├── mod.rs
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│ ├── ml_kem.rs
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│ ├── ml_dsa.rs
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│ ├── identity.rs
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│ ├── keystore.rs
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│ └── differential_privacy.rs
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```
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**Dependencies**: Agent #10 (QuDAG client)
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**Blocked By**: Agent #10
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**Blocks**: Agent #12
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**Deliverables**:
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- [ ] ML-KEM-768 encrypt/decrypt
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- [ ] ML-DSA sign/verify
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- [ ] Identity keypair management
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- [ ] Secure keystore (zeroize)
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- [ ] Laplace noise for DP
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**Estimated Complexity**: High
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---
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### Agent #12: QuDAG Token Integration
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**Type**: `backend-dev`
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**Role**: rUv token operations
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**Responsibilities**:
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1. Implement staking interface
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2. Implement reward claiming
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3. Implement balance tracking
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4. Implement token SQL functions
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5. Implement governance participation
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**Files to Create/Modify**:
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```
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ruvector-dag/src/qudag/
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├── tokens/
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│ ├── mod.rs
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│ ├── staking.rs
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│ ├── rewards.rs
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│ └── governance.rs
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ruvector-postgres/src/dag/functions/
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├── qudag.rs (SQL functions for QuDAG)
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```
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**Dependencies**: Agent #10 (QuDAG client), Agent #11 (crypto)
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**Blocked By**: Agents #10, #11
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**Blocks**: Agent #13
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**Deliverables**:
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- [ ] Staking operations
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- [ ] Reward computation
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- [ ] Balance queries
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- [ ] QuDAG SQL functions
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- [ ] Governance voting
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**Estimated Complexity**: Medium
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---
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### Agent #13: Test Suite Developer
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**Type**: `tester`
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**Role**: Comprehensive test implementation
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**Responsibilities**:
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1. Unit tests for all modules
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2. Integration tests
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3. Property-based tests
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4. Benchmark tests
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5. CI pipeline setup
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**Files to Create/Modify**:
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```
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ruvector-dag/tests/
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├── unit/
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│ ├── attention/
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│ ├── sona/
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│ ├── mincut/
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│ ├── healing/
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│ └── qudag/
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├── integration/
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│ ├── postgres/
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│ └── qudag/
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├── property/
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└── fixtures/
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ruvector-dag/benches/
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├── attention_bench.rs
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├── sona_bench.rs
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└── mincut_bench.rs
|
|
|
|
.github/workflows/
|
|
└── dag-tests.yml
|
|
```
|
|
|
|
**Dependencies**: All code agents (1-12)
|
|
|
|
**Blocked By**: Agents #1-12 (tests require implementations)
|
|
|
|
**Blocks**: None (can test incrementally)
|
|
|
|
**Deliverables**:
|
|
- [ ] >80% unit test coverage
|
|
- [ ] All integration tests passing
|
|
- [ ] Property tests (1000+ cases)
|
|
- [ ] Benchmarks meeting performance targets
|
|
- [ ] CI/CD pipeline
|
|
|
|
**Estimated Complexity**: High
|
|
|
|
---
|
|
|
|
### Agent #14: Test Data & Fixtures
|
|
|
|
**Type**: `tester`
|
|
|
|
**Role**: Test data generation and fixtures
|
|
|
|
**Responsibilities**:
|
|
1. Generate realistic query DAGs
|
|
2. Generate synthetic patterns
|
|
3. Generate trajectory data
|
|
4. Create mock QuDAG server
|
|
5. Create test databases
|
|
|
|
**Files to Create/Modify**:
|
|
```
|
|
ruvector-dag/tests/
|
|
├── fixtures/
|
|
│ ├── dag_generator.rs
|
|
│ ├── pattern_generator.rs
|
|
│ ├── trajectory_generator.rs
|
|
│ └── mock_qudag.rs
|
|
├── data/
|
|
│ ├── sample_dags.json
|
|
│ ├── sample_patterns.bin
|
|
│ └── sample_trajectories.json
|
|
```
|
|
|
|
**Dependencies**: Agent #1 (DAG structure definitions)
|
|
|
|
**Blocked By**: Agent #1
|
|
|
|
**Blocks**: Agent #13 (needs fixtures)
|
|
|
|
**Deliverables**:
|
|
- [ ] DAG generator for all complexity levels
|
|
- [ ] Pattern generator for learning tests
|
|
- [ ] Mock QuDAG server for network tests
|
|
- [ ] Sample data files
|
|
- [ ] Test database setup scripts
|
|
|
|
**Estimated Complexity**: Medium
|
|
|
|
---
|
|
|
|
### Agent #15: Documentation & Examples
|
|
|
|
**Type**: `api-docs`
|
|
|
|
**Role**: API documentation and usage examples
|
|
|
|
**Responsibilities**:
|
|
1. Rust API documentation
|
|
2. SQL API documentation
|
|
3. Usage examples
|
|
4. Integration guides
|
|
5. Troubleshooting guides
|
|
|
|
**Files to Create/Modify**:
|
|
```
|
|
ruvector-dag/
|
|
├── README.md
|
|
├── examples/
|
|
│ ├── basic_usage.rs
|
|
│ ├── attention_selection.rs
|
|
│ ├── learning_workflow.rs
|
|
│ └── qudag_integration.rs
|
|
|
|
docs/dag/
|
|
├── USAGE.md
|
|
├── TROUBLESHOOTING.md
|
|
└── EXAMPLES.md
|
|
```
|
|
|
|
**Dependencies**: All code agents (1-12)
|
|
|
|
**Blocked By**: None (can document spec first, update with impl)
|
|
|
|
**Blocks**: None
|
|
|
|
**Deliverables**:
|
|
- [ ] Complete rustdoc for all public APIs
|
|
- [ ] SQL function documentation
|
|
- [ ] Working code examples
|
|
- [ ] Integration guide
|
|
- [ ] Troubleshooting guide
|
|
|
|
**Estimated Complexity**: Medium
|
|
|
|
---
|
|
|
|
## Task Dependencies Graph
|
|
|
|
```
|
|
┌─────┐
|
|
│ 0 │ Queen
|
|
└──┬──┘
|
|
│
|
|
┌─────────────┼─────────────┐
|
|
│ │ │
|
|
┌──┴──┐ ┌──┴──┐ ┌──┴──┐
|
|
│ 1 │ │ 14 │ │ 15 │
|
|
└──┬──┘ └──┬──┘ └─────┘
|
|
│ │
|
|
┌────┼────┬───────┤
|
|
│ │ │ │
|
|
┌──┴─┐┌─┴──┐┌┴──┐┌───┴───┐
|
|
│ 2 ││ 4 ││ 5 ││ (13) │
|
|
└──┬─┘└─┬──┘└─┬─┘└───────┘
|
|
│ │ │
|
|
┌──┴─┐ │ │
|
|
│ 3 │ │ │
|
|
└──┬─┘ │ │
|
|
│ │ │
|
|
└────┼─────┘
|
|
│
|
|
┌──┴──┐
|
|
│ 6 │ PostgreSQL Core
|
|
└──┬──┘
|
|
│
|
|
┌────┼────┬────┐
|
|
│ │ │ │
|
|
┌──┴─┐┌─┴──┐│ ┌──┴──┐
|
|
│ 7 ││ 8 ││ │ 9 │
|
|
└────┘└────┘│ └─────┘
|
|
│
|
|
┌──┴──┐
|
|
│ 10 │ QuDAG Client
|
|
└──┬──┘
|
|
│
|
|
┌──┴──┐
|
|
│ 11 │ QuDAG Crypto
|
|
└──┬──┘
|
|
│
|
|
┌──┴──┐
|
|
│ 12 │ QuDAG Tokens
|
|
└──┬──┘
|
|
│
|
|
┌──┴──┐
|
|
│ 13 │ Tests
|
|
└─────┘
|
|
```
|
|
|
|
## Execution Phases
|
|
|
|
### Phase 1: Foundation (Agents 1, 14, 15)
|
|
- Agent #1: Core DAG Engine
|
|
- Agent #14: Test fixtures (parallel)
|
|
- Agent #15: Documentation skeleton (parallel)
|
|
|
|
**Duration**: Can start immediately
|
|
**Milestone**: QueryDag and OperatorNode complete
|
|
|
|
### Phase 2: Core Features (Agents 2, 3, 4, 5)
|
|
- Agent #2: Basic Attention
|
|
- Agent #3: Advanced Attention (after Agent #2)
|
|
- Agent #4: SONA Integration
|
|
- Agent #5: MinCut Optimization
|
|
|
|
**Duration**: After Phase 1 foundation
|
|
**Milestone**: All attention mechanisms and learning components
|
|
|
|
### Phase 3: PostgreSQL Integration (Agents 6, 7, 8, 9)
|
|
- Agent #6: PostgreSQL Core
|
|
- Agent #7: SQL Functions Part 1 (after Agent #6)
|
|
- Agent #8: SQL Functions Part 2 (after Agent #6)
|
|
- Agent #9: Self-Healing (after Agent #6)
|
|
|
|
**Duration**: After Phase 2 core features
|
|
**Milestone**: Full PostgreSQL extension functional
|
|
|
|
### Phase 4: QuDAG Integration (Agents 10, 11, 12)
|
|
- Agent #10: QuDAG Client
|
|
- Agent #11: QuDAG Crypto (after Agent #10)
|
|
- Agent #12: QuDAG Tokens (after Agent #11)
|
|
|
|
**Duration**: Can start after Agent #4 (SONA)
|
|
**Milestone**: Distributed pattern learning operational
|
|
|
|
### Phase 5: Testing & Validation (Agent 13)
|
|
- Agent #13: Full test suite
|
|
- Integration testing
|
|
- Performance validation
|
|
|
|
**Duration**: Ongoing throughout, intensive at end
|
|
**Milestone**: All tests passing, benchmarks met
|
|
|
|
## Coordination Protocol
|
|
|
|
### Memory Keys for Cross-Agent Communication
|
|
|
|
```
|
|
swarm/dag/
|
|
├── status/
|
|
│ ├── agent_{N}_status # Individual agent status
|
|
│ ├── phase_status # Current phase
|
|
│ └── blockers # Active blockers
|
|
├── artifacts/
|
|
│ ├── agent_{N}_files # Files created/modified
|
|
│ ├── interfaces # Shared interface definitions
|
|
│ └── schemas # Data schemas
|
|
├── decisions/
|
|
│ ├── api_decisions # API design decisions
|
|
│ ├── implementation # Implementation choices
|
|
│ └── conflicts # Resolved conflicts
|
|
└── metrics/
|
|
├── progress # Completion percentages
|
|
├── performance # Performance measurements
|
|
└── issues # Known issues
|
|
```
|
|
|
|
### Communication Hooks
|
|
|
|
Each agent MUST run before work:
|
|
```bash
|
|
npx claude-flow@alpha hooks pre-task --description "Agent #{N}: {task}"
|
|
npx claude-flow@alpha hooks session-restore --session-id "swarm-dag"
|
|
```
|
|
|
|
Each agent MUST run after work:
|
|
```bash
|
|
npx claude-flow@alpha hooks post-edit --file "{file}" --memory-key "swarm/dag/artifacts/agent_{N}_files"
|
|
npx claude-flow@alpha hooks post-task --task-id "agent_{N}_{task}"
|
|
```
|
|
|
|
## Success Criteria
|
|
|
|
| Agent | Must Complete | Performance Target |
|
|
|-------|---------------|-------------------|
|
|
| #1 | QueryDag, traversals, serialization | - |
|
|
| #2 | 4 attention mechanisms | <100μs per mechanism |
|
|
| #3 | 3 attention mechanisms + selector | <200μs per mechanism |
|
|
| #4 | SONA engine, MicroLoRA, ReasoningBank | <100μs adaptation |
|
|
| #5 | MinCut engine, dynamic updates | O(n^0.12) amortized |
|
|
| #6 | Extension scaffold, hooks, worker | - |
|
|
| #7 | 11 SQL functions | <5ms per function |
|
|
| #8 | 11 SQL functions | <5ms per function |
|
|
| #9 | Healing system | <1s detection latency |
|
|
| #10 | QuDAG client, sync | <500ms network ops |
|
|
| #11 | ML-KEM, ML-DSA | <10ms crypto ops |
|
|
| #12 | Token operations | <100ms token ops |
|
|
| #13 | >80% coverage, all benchmarks | - |
|
|
| #14 | All fixtures, mock server | - |
|
|
| #15 | Complete docs, examples | - |
|
|
|
|
---
|
|
|
|
*Document: 11-AGENT-TASKS.md | Version: 1.0 | Last Updated: 2025-01-XX*
|