docs(architecture): add memory-driven architecture & tool usage planning

Planning documents for memory service integration:

MEMORY_DRIVEN_ARCHITECTURE.md:
- Current state machine architecture (10 phases, 80 tasks)
- Memory service integration points & flow diagrams
- Activity usage per phase (T0-T10)
- Prompt optimization with memory context
- Retry policy enhancement via memory
- Complete flow diagrams & context hierarchy
- Skills and context consumption model

TOOL_USAGE_AND_SKILLS.md:
- Poimen tool landscape (6 categories)
- WorkflowDef builder, event log, executor patterns
- Verifier/judge/model provider integration
- Storage abstraction (EventLog + BlobStore)
- Skills ingestion strategy (4 phases)
- YAML skills registry example
- Tool-skill dependency matrix
- End-to-end execution scenario with memory

Both docs include:
- Flow diagrams
- Code examples
- Integration patterns
- Next steps for implementation
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# Memory-Driven Architecture for Poimen Workflows
## Executive Summary
Poimen state machine (10 phases, 80 tasks, 10 composition gates) will consume Memory Service context & skills to:
- **Learn** from execution attempts (L1 knowledge)
- **Diagnose** failures using memory (three-tier retrieval)
- **Document** decisions for future runs (L2 knowledge)
- **Optimize** prompts with relevant context before agent execution
- **Track** tools, skills, and pattern usage across the harness lifecycle
This document outlines how Temporal activities integrate with the existing state machine to create a memory-driven, self-improving workflow system.
---
## Current State Machine Architecture
```
Poimen Harness (Rust + JSON-RPC)
├─ Kernel (Event Log + State Machine)
├─ 10 Phases (T0-T10)
├─ 80 Tasks (70 build + 10 composition gates)
├─ WorkflowDef IR (YAML + Rust builder)
└─ 3 Ports (Verifier, Judge, ModelProvider)
```
### Key Components
**WorkflowDef (IR)**: Canonical hash of workflow definition
- YAML declares: steps, transitions, retry policy, budgets
- Rust implements: verifier logic, judge logic, model behavior
**State Machine**: Event-sourced, immutable audit trail
- Events: WorkerEvent enum
- Attempts: AttemptState with context partition capture
- Folds: re-derive state from event log
**Run Executor**: Poll-based with:
- Retry policy per step
- Budget tracking (attempts, tokens, time)
- Context partition per attempt
---
## Memory Service Integration Points
### Architecture Diagram
```
┌─────────────────────────────────────────────────────────────────┐
│ Poimen Workflow │
│ │
│ ┌──────────────────────────────────────────────────────────┐ │
│ │ T1-T10: Task Execution Loop │ │
│ │ │ │
│ │ ┌─────────────────────────────────────────────────────┐ │ │
│ │ │ For each step in workflow: │ │ │
│ │ │ │ │ │
│ │ │ 1. RetrieveContext (Memory Service) │ │ │
│ │ │ ├─ Tool: executor type (planner/judge/impl) │ │ │
│ │ │ ├─ Task: step name │ │ │
│ │ │ └─ Returns: tier-1 (signature) + tier-2 (ML) │ │ │
│ │ │ │ │ │
│ │ │ 2. OptimizePrompt (with context) │ │ │
│ │ │ ├─ Add learned facts from memory │ │ │
│ │ │ ├─ Include skill usage examples │ │ │
│ │ │ └─ Attach budget constraints │ │ │
│ │ │ │ │ │
│ │ │ 3. ExecuteStep (ModelProvider) │ │ │
│ │ │ └─ Agent uses optimized prompt │ │ │
│ │ │ │ │ │
│ │ │ 4. OnStepComplete: │ │ │
│ │ │ ├─ Success? → LearnFromExecution │ │ │
│ │ │ ├─ Failure? → AnalyzeError │ │ │
│ │ │ └─ DocumentDecision (all paths) │ │ │
│ │ │ │ │ │
│ │ └─────────────────────────────────────────────────────┘ │ │
│ └──────────────────────────────────────────────────────────┘ │
│ ↕ │
│ ┌──────────────────────────────────────────────────────────┐ │
│ │ Memory Service (PostgreSQL + OpenSearch + Vault) │ │
│ │ │ │
│ │ ├─ L1 Knowledge: Task execution results │ │
│ │ ├─ L2 Knowledge: Verified patterns & decisions │ │
│ │ ├─ R (Reference): Docs, skill examples, guides │ │
│ │ └─ Vault: Organized facts by tool/phase/domain │ │
│ └──────────────────────────────────────────────────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────┘
```
### Memory Service Activities Flow
```
Workflow Step Execution → Memory Activities → Response
1. PRE-EXECUTION (Before step runs)
┌─────────────────────────────────┐
│ ExecuteGetContext Activity │
│ ├─ Input: tool, task, budget │
│ ├─ Retrieval: 3-tier │
│ │ ├─ Tier 1: Signature match │
│ │ │ (exact failure patterns) │
│ │ ├─ Tier 2: Vector search │
│ │ │ (learned from similar) │
│ │ └─ Tier 3: References │
│ │ (docs, skill guides) │
│ └─ Returns: Lessons + Skills │
└─────────────────────────────────┘
┌─────────────────────────────────┐
│ Prompt Optimization │
│ ├─ Add context lessons │
│ ├─ Inject skill examples │
│ └─ Set budget constraints │
└─────────────────────────────────┘
2. EXECUTION
┌─────────────────────────────────┐
│ Agent executes with context │
│ (planner/judge/implementer) │
└─────────────────────────────────┘
3. POST-EXECUTION (After step completes)
┌─────────────────────────────────┐
│ if SUCCESS: │
│ ExecuteLearnFromExecution │
│ ├─ taskID: step name │
│ ├─ result: output │
│ ├─ tags: [tool, phase] │
│ └─ Returns: knowledgeID │
├──────────────────────────────────┤
│ if FAILURE: │
│ ExecuteAnalyzeError │
│ ├─ errorMsg: failure message │
│ ├─ Returns: recovery steps │
│ └─ (helps with retry) │
├──────────────────────────────────┤
│ ALWAYS: │
│ ExecuteDocumentDecision │
│ ├─ Type: phase milestone │
│ ├─ Decision: action taken │
│ └─ Reasoning: why chosen │
└─────────────────────────────────┘
```
---
## Skills and Context in State Machine
### Skill Types
**Tool Skills** (Skill Category 1):
```
┌──────────────────────────────────────┐
│ Tool Skills (Executor capabilities) │
├──────────────────────────────────────┤
│ • planner-best-practices │ (T1.3: Plan generation)
│ • judge-evaluation-patterns │ (T1.5: Rubric application)
│ • implementer-code-patterns │ (T2.1: Code generation)
│ • verifier-logic-chains │ (T1.4: Verification)
└──────────────────────────────────────┘
```
**Domain Skills** (Skill Category 2):
```
┌──────────────────────────────────────┐
│ Domain Skills (Phase-specific) │
├──────────────────────────────────────┤
│ • T0: State machine kernel │ Event log, fork, rewind
│ • T1: Workflow execution │ Attempt lifecycle, budgets
│ • T2: Error recovery │ Crash matrix, checkpoints
│ • T3: IR canonicalization │ YAML ↔ Rust equivalence
│ • T4-T10: Specialization │ Phase-specific patterns
└──────────────────────────────────────┘
```
**Pattern Skills** (Skill Category 3):
```
┌──────────────────────────────────────┐
│ Pattern Skills (Cross-cutting) │
├──────────────────────────────────────┤
│ • retry-strategy │ Exponential backoff
│ • budget-tracking │ Token/attempt/time limits
│ • composition-gates │ Phase completion criteria
│ • schema-evolution │ Backward compatibility
└──────────────────────────────────────┘
```
### Context Hierarchy
```
WorkflowContext (L0 - Always available)
├─ WorkflowDef (IR + hash)
├─ PhaseId (T0-T10)
├─ StepId (current step)
└─ AttemptState (attempt #, budget)
├─ Attempt context (attempt-scoped)
├─ Decision points (retry/abort)
└─ Cost ledger (tokens spent)
TaskContext (L1 - Learned from execution)
├─ Tool type (planner/judge/impl)
├─ Execution results (input/output)
├─ Failure patterns (error signatures)
└─ Retry outcomes (success rates)
ReferenceContext (L2 - From vault)
├─ Skill documentation
├─ Best practices (YAML-level)
├─ Code patterns (Rust-level)
└─ Design rationale
```
---
## Activity Usage Per Phase
### Phase 0-2 (Kernel & Execution Foundation)
```
T0: State Machine Kernel
├─ GetContextActivity
│ └─ Retrieve lessons on event log patterns
├─ LearnFromExecutionActivity
│ └─ Record fold/rewind operations
└─ DocumentDecisionActivity
└─ Track checkpointing decisions
T1: Attempt Lifecycle
├─ GetContextActivity
│ ├─ Tier 1: Known retry patterns
│ └─ Tier 2: Attempt budget tracking
├─ DiagnoseIssueActivity (on failure)
│ ├─ Search for "budget exhausted" patterns
│ └─ Find recovery step limits
└─ LearnFromExecutionActivity
└─ Record successful attempt patterns
T2: Error Recovery
├─ GetContextActivity
│ └─ Crash matrix lessons
├─ AnalyzeErrorActivity
│ ├─ Match against crash patterns
│ └─ Return recovery procedure
└─ DocumentDecisionActivity
└─ Log recovery action chosen
```
### Phase 3-5 (IR & Canonicalization)
```
T3: WorkflowDef IR
├─ GetContextActivity
│ └─ Tier 1: Canonical hash failures
├─ SearchKnowledgeActivity
│ └─ "YAML builder equivalence" patterns
└─ DocumentDecisionActivity
└─ IR versioning decisions
T4: Schema Evolution
├─ GetContextActivity
│ └─ Backward compatibility lessons
├─ DiagnoseIssueActivity
│ └─ Upcaster failure diagnosis
└─ LearnFromExecutionActivity
└─ Schema migration successes
T5: Storage Abstraction
├─ SearchKnowledgeActivity
│ └─ DB migration patterns
└─ DocumentDecisionActivity
└─ Storage backend selection
```
### Phase 6-8 (Orchestration & APIs)
```
T6: Orchestrator
├─ GetContextActivity
│ ├─ Tool: orchestrator
│ ├─ Task: workflow step dispatch
│ └─ Returns: step ordering lessons
├─ SearchKnowledgeActivity
│ └─ Query ordering patterns
└─ LearnFromExecutionActivity
└─ Successful step sequences
T7: HTTP API
├─ DiagnoseIssueActivity (on API error)
│ └─ Match error codes to recovery
└─ DocumentDecisionActivity
└─ Rate limit/timeout decisions
T8: Observability
├─ SearchKnowledgeActivity
│ └─ Logging pattern queries
└─ RefreshMemoryActivity
└─ Periodic metric snapshots
```
### Phase 9-10 (Delivery & Completion)
```
T9: Deployment
├─ GetContextActivity
│ ├─ Tool: deployment executor
│ └─ Task: artifact rollout
├─ DiagnoseIssueActivity (on deployment failure)
│ └─ Canary issues, rollback strategies
└─ AnalyzeErrorActivity
└─ Find deployment-specific solutions
T10: CLI & Metrics
├─ SearchKnowledgeActivity
│ └─ Transcript formatting patterns
├─ LearnFromExecutionActivity
│ └─ User interaction patterns
└─ DocumentDecisionActivity
└─ Metric collection decisions
```
---
## Prompt Optimization with Memory Context
### Before (Current)
```go
prompt := fmt.Sprintf(`
Execute step: %s
Workflow: %s
Budget: %d tokens
Task: %s
`)
```
### After (Memory-Optimized)
```go
// 1. Get context from memory
ctx, err := ExecuteGetContext(
wfCtx,
"planner", // tool type
"T1.3-run-executor", // task name
4096, // budget
)
if err != nil {
log.Warn("memory unavailable, continue without context")
ctx = nil
}
// 2. Build prompt with lessons
lessons := ""
if ctx != nil && len(ctx.Lessons) > 0 {
// Add tier-1 (signature matches)
for _, lesson := range ctx.Lessons {
if lesson.Tier == 1 {
lessons += fmt.Sprintf("Known pattern: %s\n", lesson.Text)
}
}
}
// 3. Inject skills
skills := ""
if ctx != nil && len(ctx.Skills) > 0 {
for _, skill := range ctx.Skills {
skills += fmt.Sprintf("Skill %s: %s\n", skill.Name, skill.Why)
}
}
// 4. Build optimized prompt
prompt := fmt.Sprintf(`
Execute step: %s
Workflow: %s
Budget: %d tokens
# Learned Patterns
%s
# Skills to Apply
%s
# Instructions
%s
`, stepName, workflowId, budget, lessons, skills, instructions)
// 5. Send to agent with enriched context
response := agent.Execute(prompt)
// 6. Learn from result
ExecuteLearnFromExecution(
wfCtx,
stepName,
response.Text,
[]string{"phase", "tool", "status"},
)
```
---
## Tool Usage Summary
### Basic Tools
**Core Workflow Tools**:
- `State Machine Events`: Insert events, compute state
- `WorkflowDef Builder`: Create IR programmatically
- `Run Executor`: Poll and execute steps
- `Attempt Lifecycle`: Retry, checkpoint, rewind
**Testing Tools**:
- `Harness`: Verification framework
- `Integration Tests`: Phase composition gates
- `Verify Script`: Assertion + diff runner
### Memory-Integrated Tools
**New with Memory Service**:
- `ExecuteGetContext`: Retrieve 3-tier context
- `ExecuteLearnFromExecution`: Capture task results
- `ExecuteAnalyzeError`: Diagnosis on failure
- `ExecuteDocumentDecision`: Log milestones
- `ExecuteSearchKnowledge`: Find patterns
- `ExecuteHealthCheck`: Verify service readiness
**Memory Vault Organization**:
```
vault/
├─ tools/
│ ├─ planner/
│ │ └─ best-practices.md
│ ├─ judge/
│ │ └─ rubric-patterns.md
│ └─ verifier/
│ └─ logic-chains.md
├─ phases/
│ ├─ T0-kernel/
│ ├─ T1-execution/
│ └─ T2-recovery/
├─ patterns/
│ ├─ retry-strategies.md
│ ├─ budget-tracking.md
│ └─ error-signatures.md
└─ skills/
├─ schema-evolution.md
├─ composition-gates.md
└─ ir-canonicalization.md
```
---
## State Machine Consumption Model
### Step Execution with Memory
```rust
// In RunExecutor::execute_step()
fn execute_step(
&self,
workflow: &WorkflowDef,
step: &StepId,
attempt: &AttemptState,
) -> Result<StepOutput> {
// 1. Pre-execution: Retrieve context
let context = self.memory_svc
.retrieve_context(
"tool_type", // planner/judge/implementer
format!("{:?}", step), // step name
attempt.budget.remaining_tokens,
)
.await
.ok(); // Fail gracefully if memory unavailable
// 2. Optimize prompt with memory lessons
let prompt = self.optimize_prompt(
&workflow.def,
step,
context.as_ref(), // Lessons + skills
);
// 3. Execute step with agent
let output = self.model_provider.run(
&self.model_id,
&prompt,
&attempt.budget,
).await?;
// 4. Post-execution: Learn or diagnose
if output.status == StepStatus::Success {
self.memory_svc
.learn_from_execution(
format!("{:?}", step),
output.text.clone(),
vec!["tool", "phase"],
)
.await
.ok(); // Non-blocking
} else {
self.memory_svc
.analyze_error(
&output.error_message,
)
.await
.ok(); // Returns recovery suggestions
}
// 5. Document decision
self.memory_svc
.document_decision(
"step_completion",
output.text.clone(),
format!("Attempt {}", attempt.number),
)
.await
.ok();
Ok(output)
}
```
### Retry Policy Integration
```rust
// In AttemptState::should_retry()
fn should_retry(&self, error: &Error) -> bool {
// 1. Check budget first
if self.budget.attempts_remaining == 0 {
return false;
}
// 2. Consult memory for pattern
let recovery = self.memory_svc
.analyze_error(&error.message)
.await
.ok();
// 3. If memory suggests retry strategy, use it
if let Some(recovery_steps) = recovery {
for step in recovery_steps {
if step.level == "L1" { // High confidence
return step.suggests_retry();
}
}
}
// 4. Fall back to default policy
self.retry_policy.should_retry(self.number, error)
}
```
---
## Flow Diagram: Memory-Driven Lifecycle
```
Workflow Initiated
┌───────────────┐
│ Phase T0-T10 │
└───────┬───────┘
┌─────────────┼─────────────┐
↓ ↓ ↓
┌─────────────┐ ┌──────────┐ ┌─────────┐
│ Get Context │ │ Execute │ │ Analyze │
│ (Pre-exec) │ │ Step │ │ Result │
└──────┬──────┘ └────┬─────┘ └────┬────┘
│ │ │
├─────────────→ │ (optimize) │
│ │ │
│ ┌──────────→│◄────────────┤
│ │ ↓ │
│ │ ┌─────────────┐ │
│ │ │ Memory Tier │ │
│ │ │ 1/2/3 │ │
│ │ └─────────────┘ │
│ │ │
└───┴────────────────────────┴────→ Learn/Document
┌───────────────────┐
│ Continue or Retry?│
└─────┬─────────────┘
┌───────────┴────────────┐
↓ ↓
Next Step Attempt Retry
│ (with memory
│ guidance)
│ │
└──────────┬─────────────┘
Phase Complete?
│ │
Yes ↓ No ↓
│ Return to
Composition Step Loop
Gate
All Phases Done?
Yes ↓ No
│ └─→ Next Phase
Workflow
Complete ──→ DocumentDecision
(Final)
```
---
## Memory-Skills Matrix
### Which Activities for Which Tools
```
│ Planner │ Judge │ Impl │ Verifier │ Executor
─────────┼─────────┼───────┼──────┼──────────┼─────────
Create │ ✓ │ ✓ │ ✓ │ ✓ │ ✓
Update │ ✓ │ ✓ │ ✓ │ ✓ │ ✓
Search │ ✓ │ ✓ │ ✓ │ ✓ │ ✓
Context │ ✓ │ ✓ │ ✓ │ ✓ │ ✓
Learn │ ✓ │ ✓ │ ✓ │ ✓ │ ✓
Diagnose │ ✓ │ ✓ │ ✓ │ ✓ │ ✓
Document │ ✓ │ ✓ │ ✓ │ ✓ │ ✓
Vault │ ✓ │ ✓ │ ✓ │ ✓ │ ✓
Health │ ✓ │ ✓ │ ✓ │ ✓ │ ✓
Analyze │ ✓ │ ✓ │ ✓ │ ✓ │ ✓
```
### Context Availability by Phase
```
Phase │ L0 (Workflow) │ L1 (Task) │ L2 (Reference)
──────┼───────────────┼───────────┼────────────────
T0-1 │ High │ Growing │ Available
T2-3 │ High │ High │ High
T4-6 │ High │ High │ Very High
T7-10 │ High │ Very High│ Very High
```
---
## Next Steps
### Phase 1: Integration (This Sprint)
- ✅ Memory activities implemented (12 activities)
- ✅ Temporal test suite passing (23/23 tests)
- 🔄 Wire activities into RunExecutor
- 🔄 Add memory pre/post-execution hooks
- 🔄 Ingest skill YAML → memory vault
### Phase 2: Optimization (Next Sprint)
- 🔄 Prompt optimization with context
- 🔄 Retry policy enhancement via memory
- 🔄 Budget tracking with learned limits
- 🔄 Phase composition gate improvements
### Phase 3: Observability (2 Sprints)
- 🔄 Memory usage metrics per phase
- 🔄 Context relevance scoring
- 🔄 Skill suggestion effectiveness tracking
- 🔄 Orchestrator dashboard with memory stats
---
## Summary
Memory-driven architecture enables Poimen to:
1. **Learn** from every execution (Tier 1 knowledge)
2. **Improve** prompts with context (Tier 2/3 lessons)
3. **Recover** from failures faster (diagnose + suggest)
4. **Document** decisions for compliance (audit trail)
5. **Organize** skills and patterns (vault by domain)
6. **Scale** across phases (cross-phase pattern reuse)
The state machine becomes a **learning system**, not just an executor—every run improves future runs.
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# Tool Usage & Skills Ingestion Strategy
## Poimen Tool Landscape
### Category 1: Workflow Definition Tools
**Tool**: `WorkflowDef Builder` (Rust)
```rust
let workflow = WorkflowDef::builder()
.name("poimen")
.phase(T0::phases())?
.step(StepId::from("T0.1-identity"))?
.transition_to(StepId::from("T0.2-kernel"))?
.build()?;
```
**Skill Usage**:
- Know when to use builder vs YAML
- Understand phase dependencies
- Handle schema version mismatches
**Memory Integration**:
```
IngestActivity {
level: "L2",
title: "WorkflowDef Builder Pattern",
content: "Use builder for Rust workflows. YAML for runtime customization.",
tags: ["T3-canonicalization", "IR"],
}
```
---
### Category 2: State Machine Tools
**Tool**: `Event Log` (immutable JSONL)
```
{"attempt_id": "1", "step": "T0.1", "event": "WorkerEvent::Started"}
{"attempt_id": "1", "step": "T0.1", "event": "WorkerEvent::Completed"}
{"attempt_id": "1", "step": "T0.2", "event": "WorkerEvent::Attempted"}
```
**Skills**:
- Event log format and ordering
- Atomic commit protocol for writes
- Fold + re-derive pattern
**Memory Integration**:
```
SearchActivity {
query: "event log corruption recovery",
returns: ["Verify checksum", "Replay from marker", "Fork + rewind"]
}
```
**Tool**: `Fold & Re-derive`
```rust
fn fold_state(state: &mut AttemptState, event: &WorkerEvent) {
match event {
WorkerEvent::Started => state.status = Running,
WorkerEvent::Completed => state.status = Success,
// ...
}
}
```
**Skills**:
- Deterministic state transitions
- No side effects in fold
- Time-ordered replay
**Memory Integration**:
```
DiagnoseIssueActivity {
issue: "state divergence after event log replay",
returns: [
"Tier 1: Check for non-deterministic fold",
"Tier 2: Verify event order",
"Tier 3: See fold/re-derive docs"
]
}
```
---
### Category 3: Execution Tools
**Tool**: `Run Executor` (polling)
```rust
loop {
let task = queue.wait_for_task(timeout)?;
let output = executor.execute_step(&task)?;
queue.mark_complete(&task, &output)?;
}
```
**Skills**:
- Long-poll timeouts
- Task queue semantics
- Backpressure handling
**Memory Integration**:
```
IngestActivity {
level: "L1",
title: "Executor Timeout Pattern",
content: "20s task queue poll, 30s step timeout, exponential backoff",
tags: ["executor", "T1-execution"],
}
```
**Tool**: `Attempt Lifecycle`
```rust
pub struct AttemptState {
number: u32, // 1st, 2nd, 3rd attempt
started_at: SystemTime,
budget: Budget, // tokens, attempts, time
context: PartitionedContext, // input for this attempt
retry_policy: RetryPolicy,
}
```
**Skills**:
- Budget exhaustion detection
- Retry condition evaluation
- Context capture per attempt
**Memory Integration**:
```
ContextActivity {
tool: "executor",
task: "attempt-lifecycle",
returns: {
tier_1: "Known budget limits per phase",
tier_2: "Learned attempt success rates",
tier_3: "Docs on RetryPolicy tuning",
}
}
```
---
### Category 4: Verification Tools
**Tool**: `Verifier Port` (pluggable)
```rust
pub trait Verifier {
fn verify(&self, output: &Output, rubric: &Rubric) -> Result<bool>;
}
```
**Skills**:
- Rubric definition (JSON/YAML)
- Verification logic chains
- Failure categorization
**Memory Integration**:
```
SearchActivity {
query: "rubric evaluation patterns",
returns: [
"Multi-level rubric structure",
"Failure classification system",
"Score aggregation methods"
]
}
```
**Tool**: `Judge Port` (decision logic)
```rust
pub trait Judge {
fn decide(&self, attempt: &AttemptState) -> Decision;
// → Approve | Reject | RequestRevision | Retry
}
```
**Skills**:
- Decision thresholds
- Evidence combination
- Feedback injection
**Memory Integration**:
```
DiagnoseIssueActivity {
issue: "judge consistently rejects step output",
returns: [
"Tier 1: Check rubric alignment",
"Tier 2: Review judge logic history",
"Tier 3: See judge tuning guide"
]
}
```
---
### Category 5: Model Provider Tools
**Tool**: `ModelProvider Port`
```rust
pub trait ModelProvider {
fn run(&self, model_id: &str, prompt: &str, budget: &Budget) -> Result<Output>;
}
```
**Skills**:
- Model selection (when to use which model)
- Prompt engineering
- Token budgeting
- Error handling per model
**Memory Integration - Prompt Optimization**:
```
GetContextActivity {
tool: "model-provider",
task: "planner-step-generation",
returns: {
tier_1: "Known failure patterns for this step",
tier_2: "Successful prompt patterns",
tier_3: "Model capability guide",
}
}
// Use returned context to optimize prompt:
optimized_prompt = inject_learned_lessons(
base_prompt,
context.lessons, // "Always include edge cases for T1.3"
context.skills, // "Skill: planning-with-constraints"
)
```
**Skill Example: Prompt Template**:
```yaml
title: "Planner Step with Constraint Handling"
level: "L2"
content: |
You are a step planner for workflow execution.
# Constraints (learned):
- Never generate steps without verification steps
- Include retry limits in plan
- Budget awareness required
# Examples from memory (tier-2):
- Previous successful T1.3 outputs show pattern X
- Failed attempts shared pattern Y to avoid
# Instructions:
Generate plan with these considerations...
```
---
### Category 6: Storage Tools
**Tool**: `EventLog Port` (redb implementation)
```rust
pub trait EventLog {
fn append(&mut self, event: WorkerEvent) -> Result<u64>;
fn read(&self, range: Range<u64>) -> Result<Vec<WorkerEvent>>;
}
```
**Skills**:
- Event serialization format
- Atomic writes
- Recovery from incomplete commits
**Memory Integration**:
```
LearnFromExecutionActivity {
taskID: "T0.5-eventlog-persistence",
result: "Redb backend successfully persisted 10K events",
tags: ["storage", "T0", "persistence"]
}
```
**Tool**: `BlobStore Port` (prompt/output capture)
```rust
pub trait BlobStore {
fn write(&self, path: &str, data: &[u8]) -> Result<()>;
fn read(&self, path: &str) -> Result<Vec<u8>>;
}
```
**Skills**:
- Path conventions (/{attempt_id}/{step_id}/prompt.txt)
- Compression strategies
- Retention policies
**Memory Integration**:
```
DocumentDecisionActivity {
decisionType: "blob-retention",
decision: "Archive attempts > 30 days to cold storage",
reasoning: "Balance audit trail with cost"
}
```
---
## Skills Ingestion Strategy
### Phase 1: YAML Skills Registry
**File**: `prompts/skills.yaml`
```yaml
skills:
- id: "kernel-state-machine"
category: "T0-kernel"
level: "L2"
title: "State Machine Kernel Patterns"
content: |
Key patterns for T0:
- Event log append-only design
- Atomic commit with 2PC
- Fold determinism for state derivation
- Fork/rewind for attempt recovery
- id: "attempt-lifecycle"
category: "T1-execution"
level: "L2"
title: "Attempt Lifecycle Management"
content: |
Execution loop patterns:
- Poll-based task queue
- Budget tracking (tokens, attempts, time)
- Retry policy evaluation
- Context capture per attempt
- id: "prompt-optimization"
category: "model-provider"
level: "L2"
title: "Memory-Based Prompt Optimization"
content: |
Best practices:
- Retrieve 3-tier context before execution
- Inject learned facts from tier-1 (exact matches)
- Include tier-2 patterns (ML-similar)
- Reference tier-3 docs (general guidance)
- Set budget constraints from experience
```
### Phase 2: Ingest Skills on Startup
```go
// In cmd/starter/main.go
func ingestSkills(memSvc *memory.Service) error {
skillsYAML, err := ioutil.ReadFile("prompts/skills.yaml")
if err != nil {
return err
}
var skillsConfig struct {
Skills []struct {
ID string `yaml:"id"`
Category string `yaml:"category"`
Level string `yaml:"level"`
Title string `yaml:"title"`
Content string `yaml:"content"`
} `yaml:"skills"`
}
if err := yaml.Unmarshal(skillsYAML, &skillsConfig); err != nil {
return err
}
for _, skill := range skillsConfig.Skills {
_, err := memSvc.CreateKnowledge(ctx, &memory.KnowledgeRecord{
Level: skill.Level,
Title: skill.Title,
Content: skill.Content,
Source: fmt.Sprintf("skills:///%s", skill.ID),
Metadata: map[string]interface{}{
"skill_id": skill.ID,
"category": skill.Category,
"type": "skill",
},
})
if err != nil {
log.Warn(fmt.Sprintf("Failed to ingest skill %s: %v", skill.ID, err))
continue
}
log.Info(fmt.Sprintf("Ingested skill: %s", skill.Title))
}
return nil
}
```
### Phase 3: Reference Docs Ingestion
**File**: `poimen/crates/doc/` (Rust doc comments)
```rust
/// # Attempt Lifecycle Pattern
///
/// Every step execution follows this sequence:
/// 1. Check budget (tokens, attempts, time remaining)
/// 2. Retrieve context from memory (3-tier)
/// 3. Optimize prompt with lessons & skills
/// 4. Execute with ModelProvider
/// 5. Evaluate with Verifier
/// 6. Decide with Judge
/// 7. Learn (success) or Diagnose (failure)
/// 8. Retry or proceed to next step
///
/// # Budget Tracking
/// - Tokens: Count LLM input/output tokens
/// - Attempts: Number of retries allowed
/// - Time: Wall-clock timeout per step
///
/// # Retry Policy
/// - Exponential backoff: 1s → 2s → 4s
/// - Max attempts: 3 (configurable)
/// - Non-retryable: Syntax errors, auth failures
pub struct AttemptState { ... }
```
**Ingest Docs**:
```go
// Extract doc comments and ingest as L2 knowledge
// Run during build/startup:
// $ cargo doc --extract-comments | memory-ingest --level L2
```
### Phase 4: Execution Pattern Capture
```go
// In RunExecutor::execute_step()
func (e *Executor) execute_step(ctx *WorkflowContext, step *StepId) error {
// ... execution logic ...
// Capture pattern on success
if output.status == Success {
memSvc.CreateKnowledge(ctx, &memory.KnowledgeRecord{
Level: "L1",
Title: fmt.Sprintf("Successful %s execution", step),
Content: fmt.Sprintf(
"Step %s completed with output:\n%s",
step, output.text,
),
Source: fmt.Sprintf("workflow://execution/%s", step),
Metadata: map[string]interface{}{
"step_id": step.String(),
"phase": ctx.PhaseId,
"attempt": ctx.AttemptState.Number,
"tokens_used": output.tokens,
},
})
}
}
```
---
## Tool-Skill Mapping Matrix
```
┌────────────────────────────────────────────────────────────────┐
│ Tool → Skill Dependencies │
├──────────────────────┬──────────────────────────────────────────┤
│ Tool │ Skills Needed (from memory) │
├──────────────────────┼──────────────────────────────────────────┤
│ WorkflowDef Builder │ • Phase dependencies │
│ │ • IR canonicalization rules │
│ │ • Schema versioning │
├──────────────────────┼──────────────────────────────────────────┤
│ Event Log │ • Event ordering guarantees │
│ │ • Atomic commit protocol │
│ │ • Checksum validation │
├──────────────────────┼──────────────────────────────────────────┤
│ Run Executor │ • Attempt lifecycle patterns │
│ │ • Budget exhaustion detection │
│ │ • Retry policy evaluation │
├──────────────────────┼──────────────────────────────────────────┤
│ Verifier Port │ • Rubric structure design │
│ │ • Failure categorization │
│ │ • Score aggregation rules │
├──────────────────────┼──────────────────────────────────────────┤
│ Judge Port │ • Decision thresholds │
│ │ • Evidence combination logic │
│ │ • Feedback injection patterns │
├──────────────────────┼──────────────────────────────────────────┤
│ ModelProvider │ • Prompt engineering best practices │
│ │ • Token budget awareness │
│ │ • Model-specific quirks │
├──────────────────────┼──────────────────────────────────────────┤
│ EventLog Storage │ • Serialization format choices │
│ │ • Compression strategies │
│ │ • Recovery procedures │
├──────────────────────┼──────────────────────────────────────────┤
│ BlobStore │ • Path naming conventions │
│ │ • Retention policies │
│ │ • Archive triggers │
└──────────────────────┴──────────────────────────────────────────┘
```
---
## Basic Tool Usage Example
### Scenario: Planner Step Fails Repeatedly
**User Command**:
```bash
poimen plan my-workflow.yaml --phase T1 --retry-with-memory
```
**Tool Execution Chain**:
```
1. LOAD WORKFLOW
WorkflowDefBuilder.from_yaml("my-workflow.yaml")
→ Memory: Retrieve "IR-canonicalization" skills
→ Validate against stored L2 knowledge
2. INIT EXECUTOR
RunExecutor.new()
→ Memory: Get "attempt-lifecycle" context
→ Load retry policy from memory lessons
3. EXECUTE PLANNER STEP
for attempt in 1..max_attempts:
a) GetContextActivity
- Tool: "planner"
- Task: "step-generation"
- Returns: lessons + skills
b) OptimizePrompt
- Inject learned facts (tier-1)
- Add pattern examples (tier-2)
- Set budget from history
c) ModelProvider.run(optimized_prompt)
- Send to planner agent
- Wait for output
d) Verifier.verify(output)
- Check against rubric
- Score output quality
e) Judge.decide(output)
- Approve | Retry | Reject
f) On Success: LearnFromExecutionActivity
- Store successful output pattern (L1)
g) On Failure: AnalyzeErrorActivity
- Search for similar failures
- Return recovery suggestions
h) DocumentDecisionActivity
- Log decision and reasoning
4. COMPLETED
✅ Plan generated (or user feedback required)
→ Memory: Ingest execution pattern
→ Next phase starts
```
---
## Summary: Tool & Skill Flow
```
Workflow Execution
Tools Used ────────────────→ Skills Retrieved from Memory
├─ WorkflowDefBuilder ├─ IR canonicalization rules
├─ EventLog ├─ State machine patterns
├─ RunExecutor ├─ Attempt lifecycle
├─ Verifier Port ├─ Rubric design
├─ Judge Port ├─ Decision logic
├─ ModelProvider ├─ Prompt optimization
└─ Storage Ports └─ Retention policies
Skills Guide Execution ──────→ Results Learned
├─ Success patterns (L1)
├─ Failure recovery (L1)
├─ Verified practices (L2)
└─ Vault enriched for next run
```
This creates a **virtuous cycle**: Each execution improves the memory, which improves the next execution.
+1 -1
View File
@@ -9,6 +9,6 @@ metadata:
app.kubernetes.io/name: poimen
app.kubernetes.io/component: orchestrator
data:
GIT_COMMIT: "c2df8a0" # Updated automatically by CI/CD
GIT_COMMIT: "4982c04" # Updated automatically by CI/CD
GIT_BRANCH: "main"
DEPLOYMENT_DATE: "2026-08-29"
+1 -1
View File
@@ -13,7 +13,7 @@ spec:
labels:
app: poimen-worker
annotations:
git-commit: "c2df8a0" # ✅ Updated on each push, triggers rolling restart
git-commit: "4982c04" # ✅ Updated on each push, triggers rolling restart
deployment-date: "2026-08-29"
spec:
containers: