Blueprint Plan - Strategy Architecture & Task Decomposition

Overview

Transform vague strategy ideas into executable Linear Tickets with proper risk assessment, backtest specifications, and Postmortem immune screening to prevent regression.

Core Principle

./postmortem/ = 深度病历库 (Deep Case History)
./CLAUDE.md   = 高频手术准则 (High-Frequency Operating Rules)

Rule: 新策略必须通过历史病历的"免疫筛查"

When to Use

• User wants to plan a new trading strategy for Polymarket
• User mentions "策略规划", "strategy planning", or "feature decomposition"
• Before any implementation of market-making or trading logic

Do NOT use when:

• Debugging existing strategy code
• Running backtests (use execution skills instead)
• Simple code changes unrelated to strategy

Workflow

digraph blueprint_plan {
    rankdir=TB;
    node [shape=box];

    start [label="User: New Strategy Idea" shape=ellipse];
    pm_scan [label="0. Postmortem Immune Scan\n(MANDATORY FIRST)" style=filled fillcolor=lightyellow];
    context [label="1. Context Retrieval\n(GitHub MCP)"];
    review [label="2. Strategy Risk Review\n(Superpowers Analysis)"];
    linear [label="3. Linear Ticket Creation\n(Linear MCP)"];
    done [label="Tickets Ready" shape=ellipse];

    start -> pm_scan;
    pm_scan -> context;
    context -> review;
    review -> linear;
    linear -> done;
}

Phase 0: Postmortem Immune Scan (MANDATORY)

Goal: Screen new strategy against historical failures to prevent regression.

Step 0.1: Scan Postmortem Directory

# List all postmortem files
ls -la ./postmortem/

# Read each relevant postmortem
cat ./postmortem/*.md

Step 0.2: Keyword Matching

Search postmortems for terms related to the new strategy:

Strategy Type	Keywords to Scan
Market Making	spread, inventory, quote, bid, ask, fill
Mean Reversion	revert, mean, deviation, zscore, band
Momentum	trend, breakout, signal, momentum
Arbitrage	arb, spread, cross-market, latency
Any Strategy	API, rate limit, timeout, websocket, order

Tool: Grep
Pattern: [relevant keywords]
Path: ./postmortem/

Step 0.3: Immune Report Generation

For each relevant postmortem found, extract:

## 🛡️ Immune Screening Report

### Relevant Historical Incidents

| PM File | Incident | Root Cause | Relevance to New Strategy |
|---------|----------|------------|---------------------------|
| PM-001.md | Order duplication | Missing idempotency | HIGH - uses same order API |
| PM-003.md | Liquidity trap | No exit strategy | MEDIUM - similar market type |

### Mandatory Mitigations (from Postmortems)

- [ ] [Mitigation 1 from PM-001]
- [ ] [Mitigation 2 from PM-003]

### Cleared (No Relevant History)

- [List of scanned categories with no matches]

BLOCKING: If HIGH relevance incidents found, mitigations MUST be included in ticket acceptance criteria.

Output: Immune Screening Report appended to ticket.

🔄 Ralph Loop: Thorough Context Gathering (Optional)

When to Activate: Complex strategies requiring deep codebase understanding.

For strategies touching multiple existing systems, use Ralph Loop to iteratively build comprehensive context:

Skill: ralph-loop:ralph-loop

Prompt Template:
"Gather comprehensive context for [strategy_name].

Target areas:
- Existing strategies in strategies/
- Backtest framework in backtest/
- API integrations in api/
- PM files in postmortem/

Build context map:
- [ ] All relevant files identified
- [ ] Interface contracts documented
- [ ] PM risks catalogued
- [ ] Dependencies mapped

Output <promise>CONTEXT COMPLETE</promise> when context map is comprehensive."

Options:
--max-iterations 8
--completion-promise "CONTEXT COMPLETE"

Ralph Loop Context Gathering Cycle

digraph ralph_context {
    rankdir=LR;
    node [shape=box];

    start [label="Strategy Idea" shape=ellipse];
    explore [label="Explore Codebase"];
    gap [label="Gaps Found?" shape=diamond];
    deepen [label="Deepen Search"];
    done [label="<promise>\nCONTEXT COMPLETE" shape=ellipse style=filled fillcolor=lightgreen];

    start -> explore;
    explore -> gap;
    gap -> deepen [label="Yes"];
    deepen -> explore;
    gap -> done [label="No"];
}

Context Completeness Checklist

Area	Questions to Answer
Strategies	What patterns exist? What interfaces are required?
Backtest	What data format? What metrics calculated?
API	What rate limits? What auth method?
Postmortems	What risks relate to this strategy type?
Dependencies	What versions? What conflicts possible?

When to Use Ralph Loop for Planning

Situation	Use Ralph Loop?
New strategy type (no similar exists)	✅ Yes - need thorough exploration
Many existing strategies to learn from	✅ Yes - comprehensive pattern mining
Simple variant of existing strategy	❌ No - direct PM scan sufficient
User provided detailed specs	❌ No - context already clear

Phase 1: Context Retrieval

Required: Confirm project structure before proceeding.

Step 1.1: Write Implementation Plan

Use Skill tool: superpowers:writing-plans
Purpose: Create structured implementation plan for the strategy
Input: Strategy idea, PM mitigations from Phase 0, risk assessment
Output: Detailed plan with phases, acceptance criteria, dependencies

Step 1.2: Retrieve Codebase Context

Use GitHub MCP to inspect:

• backtest/ directory: Existing backtest framework, data sources, metrics
• strategies/ directory: Current strategy implementations, common patterns

Action: Use mcp__github__get_file_contents to list directories
If directories don't exist: Note this as "greenfield implementation"

Output: Implementation plan + summary of existing codebase context or "greenfield" status.

Phase 2: Strategy Risk Review

Analyze the proposed strategy for Polymarket-specific risks.

Step 2.1: Invoke Code Review for Risk Analysis

If strategy design document or pseudo-code exists, use superpowers to analyze risks:

Use Skill tool: superpowers:requesting-code-review
Focus areas:
- Risk patterns in strategy logic
- Error handling assumptions
- Edge case coverage
- PM anti-pattern detection in design

Step 2.2: Manual Risk Matrix Analysis

Analyze the proposed strategy for Polymarket-specific risks:

Risk Category	Check Items
Inventory Risk	Position limits, hedging approach, exposure caps
Slippage	Order book depth, spread compensation, market impact
Liquidity	Market depth assumptions, exit strategy
Model Risk	Probability estimation method, edge decay
PM-Flagged Risks	All HIGH/MEDIUM items from Phase 0

Output: Risk assessment summary with mitigation recommendations (combining superpowers analysis + manual review).

Phase 3: Linear Ticket Creation

Main Ticket Structure

Create a Feature/Strategy ticket with:

## Strategy: [Strategy Name]

### Description
[Brief strategy overview]

### 🛡️ Postmortem Immune Screening
[Summary from Phase 0 - REQUIRED SECTION]

**Relevant Incidents:** [count]
**Mandatory Mitigations:** [list]

### Risk Assessment
[Summary from Phase 2]

### Backtest Baseline Metrics
| Metric | Target | Minimum Acceptable |
|--------|--------|-------------------|
| Sharpe Ratio | ≥ 2.0 | ≥ 1.5 |
| Max Drawdown (MDD) | ≤ 10% | ≤ 15% |
| APR | ≥ 30% | ≥ 20% |

### Acceptance Criteria
- [ ] Strategy passes backtest with baseline metrics
- [ ] Risk limits implemented
- [ ] Paper trading validation complete
- [ ] **PM mitigations verified:** [list each]

Required Sub-tickets

Auto-create two child tickets:

1. 策略实现 (Strategy Implementation)

   • Core trading logic
   • Order placement/cancellation
   • Position management
   • PM mitigation implementations

2. 回测用例编写 (Backtest Case Development)

   • Historical data integration
   • Performance metrics calculation
   • Edge case scenarios
   • PM regression test cases

Use mcp__plugin_linear_linear__create_issue with parentId for sub-tickets.

Quick Reference

Phase	Tool	Key Action
0. PM Scan	Grep + Read	Scan postmortem/ for relevant incidents
0b. 🔄 Ralph	ralph-loop:ralph-loop	Thorough context gathering (optional)
1. Plan	superpowers:writing-plans	Create structured implementation plan
1. Context	mcp__github__get_file_contents	List backtest/, strategies/
2. Review	superpowers:requesting-code-review	Risk analysis + code review (if design doc exists)
3. Linear	mcp__plugin_linear_linear__create_issue	Create tickets with PM section

Common Mistakes

Mistake	Fix
Skipping PM scan	Phase 0 is MANDATORY, not optional
Ignoring HIGH relevance incidents	MUST include mitigations in acceptance criteria
Skipping context check	Always verify codebase structure first
Missing metrics baseline	Include Sharpe, MDD, APR targets in every ticket
No sub-ticket linking	Use parentId to properly link sub-tasks
Vague risk assessment	Be specific: "10% position cap" not "manage inventory"

Postmortem File Format Reference

Expected structure in ./postmortem/:

postmortem/
├── PM-001-order-duplication.md
├── PM-002-api-timeout-cascade.md
├── PM-003-liquidity-trap.md
└── TEMPLATE.md

Each PM file should contain:

• Incident Date
• Root Cause
• Impact
• Mitigations Implemented
• Keywords (for searchability)

Example Invocation

Standard Mode

User: "Plan a mean-reversion strategy for Polymarket presidential election markets"

Claude:
0. [PM Scan] Scanning postmortem/ for: revert, mean, election, spread...
   Found: PM-003 (liquidity trap in election markets) - HIGH relevance
   Mitigation required: Exit strategy for illiquid periods

1. [Context] Checking backtest/ and strategies/ via GitHub...
   Found existing mean-reversion base class

2. [Review] Risk assessment for mean-reversion in binary markets...
   Added PM-003 mitigation to risk matrix

3. [Linear] Creating main ticket + 2 sub-tickets...
   - Main ticket includes PM Immune Screening section
   - Acceptance criteria includes PM-003 mitigation verification

Output: Links to created Linear tickets with PM screening embedded

🔄 Ralph Loop Mode (Deep Context Gathering)

User: "Plan a cross-market arbitrage strategy，这是我们第一次做套利"

Claude:
0. [PM Scan] Scanning postmortem/ for: arb, spread, cross-market, latency...
   Found: Multiple potential risks
   First arbitrage strategy → Need thorough context

🔄 [Ralph Loop: Context Gathering]
   Invoking: /ralph-loop "Gather comprehensive context for cross-market arbitrage.
   Areas: strategies/, backtest/, api/, postmortem/
   First arb strategy - need complete understanding.
   Output <promise>CONTEXT COMPLETE</promise> when map is comprehensive."
   --max-iterations 8
   --completion-promise "CONTEXT COMPLETE"

   Iteration 1: Explored strategies/ → Found market-making base, no arb
   Iteration 2: Explored backtest/ → Multi-market data format identified
   Iteration 3: Explored api/ → Rate limits per exchange documented
   Iteration 4: Deep PM scan → 3 latency-related incidents found
   Iteration 5: Dependencies → Websocket libraries identified

   <promise>CONTEXT COMPLETE</promise>

🔄 [Ralph Loop Complete]
   Context Map Built:
   - Existing patterns: Market-making (adaptable)
   - Backtest: Supports multi-market (need sync logic)
   - API: 3 exchange connectors, different rate limits
   - PM Risks: Latency (PM-004), Data sync (PM-006), Order timing (PM-009)
   - Dependencies: asyncio, websockets (no conflicts)

1-3. [Proceeding with Context, Review, Linear...]
   Tickets created with comprehensive PM risks from deep scan

Output: Well-informed tickets based on thorough codebase exploration