Meta-Cognition Parallel Analysis (Experimental)

Status: Experimental | Version: 0.2.0 | Last Updated: 2025-01-27

This skill tests parallel three-layer cognitive analysis.

Concept

Instead of sequential analysis, this skill launches three parallel analyzers - one for each cognitive layer - then synthesizes their results.

User Question │ ▼ ┌─────────────────────────────────────────────────────┐ │ meta-cognition-parallel │ │ (Coordinator) │ └─────────────────────────────────────────────────────┘ │ ├─── Layer 1 ──► Language Mechanics ──► L1 Result │ ├─── Layer 2 ──► Design Choices ──► L2 Result │ ├── Parallel (Agent Mode) │ │ or Sequential (Inline) └─── Layer 3 ──► Domain Constraints ──► L3 Result │ ▼ ┌─────────────────────────────────────────────────────┐ │ Cross-Layer Synthesis │ │ (In main context with all results) │ └─────────────────────────────────────────────────────┘ │ ▼ Domain-Correct Architectural Solution

Usage

/meta-parallel <your Rust question>

Example:

/meta-parallel 我的交易系统报 E0382 错误，应该用 clone 吗？

Execution Mode Detection

CRITICAL: Check agent file availability first to determine execution mode.

Try to read layer analyzer files:

• ../../agents/layer1-analyzer.md

• ../../agents/layer2-analyzer.md

• ../../agents/layer3-analyzer.md

Agent Mode (Plugin Install) - Parallel Execution

When all layer analyzer files exist at ../../agents/ :

Step 1: Parse User Query

Extract from $ARGUMENTS :

• The original question

• Any code snippets

• Domain hints (trading, web, embedded, etc.)

Step 2: Launch Three Parallel Agents

CRITICAL: Launch all three Tasks in a SINGLE message to enable parallel execution.

Read agent files, then launch in parallel:

Task( subagent_type: "general-purpose", run_in_background: true, prompt: <content of ../../agents/layer1-analyzer.md> + "\n\n## User Query\n" + $ARGUMENTS )

Task( subagent_type: "general-purpose", run_in_background: true, prompt: <content of ../../agents/layer2-analyzer.md> + "\n\n## User Query\n" + $ARGUMENTS )

Task( subagent_type: "general-purpose", run_in_background: true, prompt: <content of ../../agents/layer3-analyzer.md> + "\n\n## User Query\n" + $ARGUMENTS )

Step 3: Collect Results

Wait for all three agents to complete. Each returns structured analysis.

Step 4: Cross-Layer Synthesis

With all three results, perform synthesis per template below.

Inline Mode (Skills-only Install) - Sequential Execution

When layer analyzer files are NOT available, execute analysis directly:

Step 1: Parse User Query

Same as Agent Mode - extract question, code, and domain hints from $ARGUMENTS .

Step 2: Execute Layer 1 - Language Mechanics

Analyze the Rust language mechanics involved:

Layer 1: Language Mechanics

Error/Pattern Identified:

• Error code: E0XXX (if applicable)
• Pattern: ownership/borrowing/lifetime/etc.

Root Cause: [Explain why this error occurs in terms of Rust's ownership model]

Language-Level Solutions:

Confidence: HIGH | MEDIUM | LOW Reasoning: [Why this confidence level]

Focus areas:

• Ownership rules (move, copy, borrow)

• Lifetime annotations

• Borrowing rules (shared vs mutable)

• Error codes and their meanings

Step 3: Execute Layer 2 - Design Choices

Analyze the design patterns and trade-offs:

Layer 2: Design Choices

Design Pattern Context:

• Current approach: [What pattern is being used]
• Problem: [Why it conflicts with Rust's rules]

Design Alternatives:

Recommended Pattern: [Which pattern fits best and why]

Confidence: HIGH | MEDIUM | LOW Reasoning: [Why this confidence level]

Focus areas:

• Smart pointer choices (Box, Rc, Arc)

• Interior mutability patterns (Cell, RefCell, Mutex)

• Ownership transfer vs sharing

• Cloning vs references

Step 4: Execute Layer 3 - Domain Constraints

Analyze domain-specific requirements:

Layer 3: Domain Constraints

Domain Identified: [trading/fintech | web | CLI | embedded | etc.]

Domain-Specific Requirements:

• Performance: [requirements]
• Safety: [requirements]
• Concurrency: [requirements]
• Auditability: [requirements]

Domain Best Practices:

1. [Best practice 1]
2. [Best practice 2]

Constraints on Solution:

• MUST: [hard requirements]
• SHOULD: [soft requirements]
• AVOID: [anti-patterns for this domain]

Confidence: HIGH | MEDIUM | LOW Reasoning: [Why this confidence level]

Focus areas:

• Industry requirements (FinTech regulations, web scalability, etc.)

• Performance constraints

• Safety and correctness requirements

• Common patterns in the domain

Step 5: Cross-Layer Synthesis

Combine all three layers:

Cross-Layer Synthesis

Layer Results Summary

Cross-Layer Reasoning

1. L3 → L2: [How domain constraints affect design choice]
2. L2 → L1: [How design choice determines mechanism]
3. L1 ← L3: [Direct domain impact on language features]

Synthesized Recommendation

Problem: [Restated with full context]

Solution: [Domain-correct architectural solution]

Rationale:

• Domain requires: [L3 constraint]
• Design pattern: [L2 pattern]
• Mechanism: [L1 implementation]

Confidence Assessment

• Overall: HIGH | MEDIUM | LOW
• Limiting Factor: [Which layer had lowest confidence]

Output Template

Both modes produce the same output format:

Three-Layer Meta-Cognition Analysis

Query: [User's question]

Layer 1: Language Mechanics

[L1 analysis result]

Layer 2: Design Choices

[L2 analysis result]

Layer 3: Domain Constraints

[L3 analysis result]

Cross-Layer Synthesis

Reasoning Chain

L3 Domain: [Constraint] ↓ implies L2 Design: [Pattern] ↓ implemented via L1 Mechanism: [Feature]

Final Recommendation

Do: [Recommended approach]

Don't: [What to avoid]

Code Pattern:

// Recommended implementation

Analysis performed by meta-cognition-parallel v0.2.0 (experimental)

---

## Test Scenarios

### Test 1: Trading System E0382

/meta-parallel 交易系统报 E0382，trade record 被 move 了

Expected: L3 identifies FinTech constraints → L2 suggests shared immutable → L1 recommends Arc<T>

### Test 2: Web API Concurrency

/meta-parallel Web API 中多个 handler 需要共享数据库连接池

Expected: L3 identifies Web constraints → L2 suggests connection pooling → L1 recommends Arc<Pool>

### Test 3: CLI Tool Config

/meta-parallel CLI 工具如何处理配置文件和命令行参数的优先级

Expected: L3 identifies CLI constraints → L2 suggests config precedence pattern → L1 recommends builder pattern

---

## Error Handling

| Error | Cause | Solution |
|-------|-------|----------|
| Agent files not found | Skills-only install | Use inline mode (sequential) |
| Agent timeout | Complex analysis | Wait longer or use inline mode |
| Incomplete layer result | Agent issue | Fill in with inline analysis |

## Limitations

- **Agent Mode:** Parallel execution, faster but requires plugin install
- **Inline Mode:** Sequential execution, slower but works everywhere
- Cross-layer synthesis quality depends on result structure
- May have higher latency than simple single-layer analysis

## Feedback

This is experimental. Please report issues and suggestions to improve the three-layer analysis approach.