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skills/meta-cognition-parallel/SKILL.md
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skills/meta-cognition-parallel/SKILL.md
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---
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name: meta-cognition-parallel
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description: "EXPERIMENTAL: Three-layer parallel meta-cognition analysis. Triggers on: /meta-parallel, 三层分析, parallel analysis, 并行元认知"
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argument-hint: "<rust_question>"
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---
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# Meta-Cognition Parallel Analysis (Experimental)
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> **Status:** Experimental | **Version:** 0.2.0 | **Last Updated:** 2025-01-27
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>
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> This skill tests parallel three-layer cognitive analysis.
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## Concept
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Instead of sequential analysis, this skill launches three parallel analyzers - one for each cognitive layer - then synthesizes their results.
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```
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User Question
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│
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▼
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┌─────────────────────────────────────────────────────┐
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│ meta-cognition-parallel │
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│ (Coordinator) │
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└─────────────────────────────────────────────────────┘
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│
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├─── Layer 1 ──► Language Mechanics ──► L1 Result
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│
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├─── Layer 2 ──► Design Choices ──► L2 Result
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│ ├── Parallel (Agent Mode)
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│ │ or Sequential (Inline)
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└─── Layer 3 ──► Domain Constraints ──► L3 Result
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│
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▼
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┌─────────────────────────────────────────────────────┐
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│ Cross-Layer Synthesis │
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│ (In main context with all results) │
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└─────────────────────────────────────────────────────┘
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│
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▼
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Domain-Correct Architectural Solution
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```
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## Usage
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```
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/meta-parallel <your Rust question>
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```
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**Example:**
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```
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/meta-parallel 我的交易系统报 E0382 错误，应该用 clone 吗？
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```
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## Execution Mode Detection
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**CRITICAL: Check agent file availability first to determine execution mode.**
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Try to read layer analyzer files:
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- `../../agents/layer1-analyzer.md`
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- `../../agents/layer2-analyzer.md`
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- `../../agents/layer3-analyzer.md`
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---
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## Agent Mode (Plugin Install) - Parallel Execution
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**When all layer analyzer files exist at `../../agents/`:**
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### Step 1: Parse User Query
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Extract from `$ARGUMENTS`:
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- The original question
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- Any code snippets
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- Domain hints (trading, web, embedded, etc.)
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### Step 2: Launch Three Parallel Agents
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**CRITICAL: Launch all three Tasks in a SINGLE message to enable parallel execution.**
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```
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Read agent files, then launch in parallel:
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Task(
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subagent_type: "general-purpose",
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run_in_background: true,
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prompt: <content of ../../agents/layer1-analyzer.md>
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+ "\n\n## User Query\n" + $ARGUMENTS
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)
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Task(
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subagent_type: "general-purpose",
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run_in_background: true,
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prompt: <content of ../../agents/layer2-analyzer.md>
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+ "\n\n## User Query\n" + $ARGUMENTS
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)
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Task(
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subagent_type: "general-purpose",
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run_in_background: true,
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prompt: <content of ../../agents/layer3-analyzer.md>
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+ "\n\n## User Query\n" + $ARGUMENTS
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)
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```
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### Step 3: Collect Results
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Wait for all three agents to complete. Each returns structured analysis.
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### Step 4: Cross-Layer Synthesis
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With all three results, perform synthesis per template below.
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---
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## Inline Mode (Skills-only Install) - Sequential Execution
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**When layer analyzer files are NOT available, execute analysis directly:**
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### Step 1: Parse User Query
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Same as Agent Mode - extract question, code, and domain hints from `$ARGUMENTS`.
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### Step 2: Execute Layer 1 - Language Mechanics
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Analyze the Rust language mechanics involved:
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```markdown
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## Layer 1: Language Mechanics
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**Error/Pattern Identified:**
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- Error code: E0XXX (if applicable)
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- Pattern: ownership/borrowing/lifetime/etc.
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**Root Cause:**
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[Explain why this error occurs in terms of Rust's ownership model]
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**Language-Level Solutions:**
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1. [Solution 1]: description
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2. [Solution 2]: description
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**Confidence:** HIGH | MEDIUM | LOW
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**Reasoning:** [Why this confidence level]
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```
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**Focus areas:**
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- Ownership rules (move, copy, borrow)
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- Lifetime annotations
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- Borrowing rules (shared vs mutable)
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- Error codes and their meanings
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### Step 3: Execute Layer 2 - Design Choices
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Analyze the design patterns and trade-offs:
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```markdown
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## Layer 2: Design Choices
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**Design Pattern Context:**
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- Current approach: [What pattern is being used]
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- Problem: [Why it conflicts with Rust's rules]
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**Design Alternatives:**
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| Pattern | Pros | Cons | When to Use |
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|---------|------|------|-------------|
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| Pattern A | ... | ... | ... |
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| Pattern B | ... | ... | ... |
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**Recommended Pattern:**
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[Which pattern fits best and why]
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**Confidence:** HIGH | MEDIUM | LOW
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**Reasoning:** [Why this confidence level]
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```
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**Focus areas:**
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- Smart pointer choices (Box, Rc, Arc)
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- Interior mutability patterns (Cell, RefCell, Mutex)
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- Ownership transfer vs sharing
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- Cloning vs references
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### Step 4: Execute Layer 3 - Domain Constraints
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Analyze domain-specific requirements:
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```markdown
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## Layer 3: Domain Constraints
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**Domain Identified:** [trading/fintech | web | CLI | embedded | etc.]
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**Domain-Specific Requirements:**
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- [ ] Performance: [requirements]
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- [ ] Safety: [requirements]
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- [ ] Concurrency: [requirements]
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- [ ] Auditability: [requirements]
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**Domain Best Practices:**
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1. [Best practice 1]
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2. [Best practice 2]
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**Constraints on Solution:**
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- MUST: [hard requirements]
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- SHOULD: [soft requirements]
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- AVOID: [anti-patterns for this domain]
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**Confidence:** HIGH | MEDIUM | LOW
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**Reasoning:** [Why this confidence level]
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```
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**Focus areas:**
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- Industry requirements (FinTech regulations, web scalability, etc.)
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- Performance constraints
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- Safety and correctness requirements
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- Common patterns in the domain
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### Step 5: Cross-Layer Synthesis
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Combine all three layers:
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```markdown
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## Cross-Layer Synthesis
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### Layer Results Summary
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| Layer | Key Finding | Confidence |
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|-------|-------------|------------|
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| L1 (Mechanics) | [Summary] | [Level] |
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| L2 (Design) | [Summary] | [Level] |
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| L3 (Domain) | [Summary] | [Level] |
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### Cross-Layer Reasoning
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1. **L3 → L2:** [How domain constraints affect design choice]
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2. **L2 → L1:** [How design choice determines mechanism]
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3. **L1 ← L3:** [Direct domain impact on language features]
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### Synthesized Recommendation
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**Problem:** [Restated with full context]
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**Solution:** [Domain-correct architectural solution]
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**Rationale:**
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- Domain requires: [L3 constraint]
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- Design pattern: [L2 pattern]
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- Mechanism: [L1 implementation]
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### Confidence Assessment
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- **Overall:** HIGH | MEDIUM | LOW
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- **Limiting Factor:** [Which layer had lowest confidence]
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```
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---
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## Output Template
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Both modes produce the same output format:
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```markdown
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# Three-Layer Meta-Cognition Analysis
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> Query: [User's question]
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---
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## Layer 1: Language Mechanics
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[L1 analysis result]
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---
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## Layer 2: Design Choices
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[L2 analysis result]
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---
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## Layer 3: Domain Constraints
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[L3 analysis result]
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---
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## Cross-Layer Synthesis
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### Reasoning Chain
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```
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L3 Domain: [Constraint]
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↓ implies
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L2 Design: [Pattern]
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↓ implemented via
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L1 Mechanism: [Feature]
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```
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### Final Recommendation
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**Do:** [Recommended approach]
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**Don't:** [What to avoid]
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**Code Pattern:**
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```rust
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// Recommended implementation
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```
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---
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*Analysis performed by meta-cognition-parallel v0.2.0 (experimental)*
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```
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---
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## Test Scenarios
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### Test 1: Trading System E0382
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```
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/meta-parallel 交易系统报 E0382，trade record 被 move 了
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```
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Expected: L3 identifies FinTech constraints → L2 suggests shared immutable → L1 recommends Arc<T>
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### Test 2: Web API Concurrency
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```
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/meta-parallel Web API 中多个 handler 需要共享数据库连接池
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```
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Expected: L3 identifies Web constraints → L2 suggests connection pooling → L1 recommends Arc<Pool>
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### Test 3: CLI Tool Config
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```
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/meta-parallel CLI 工具如何处理配置文件和命令行参数的优先级
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```
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Expected: L3 identifies CLI constraints → L2 suggests config precedence pattern → L1 recommends builder pattern
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---
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## Error Handling
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| Error | Cause | Solution |
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|-------|-------|----------|
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| Agent files not found | Skills-only install | Use inline mode (sequential) |
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| Agent timeout | Complex analysis | Wait longer or use inline mode |
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| Incomplete layer result | Agent issue | Fill in with inline analysis |
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## Limitations
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- **Agent Mode:** Parallel execution, faster but requires plugin install
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- **Inline Mode:** Sequential execution, slower but works everywhere
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- Cross-layer synthesis quality depends on result structure
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- May have higher latency than simple single-layer analysis
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## Feedback
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This is experimental. Please report issues and suggestions to improve the three-layer analysis approach.
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Reference in New Issue
Block a user