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/meta-cognition-parallel

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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Install
$ npx -y skills add zhanghandong/rust-skills --skill meta-cognition-parallel --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/meta-cognition-parallel

Context preview

The summary Claude sees to decide when to auto-load this skill.

EXPERIMENTAL: Three-layer parallel meta-cognition analysis. Triggers on: /meta-parallel, 三层分析, parallel analysis, 并行元认知

SKILL.md

meta-cognition-parallel.SKILL.md
name: meta-cognition-parallel
description: "EXPERIMENTAL: Three-layer parallel meta-cognition analysis. Triggers on: /meta-parallel, 三层分析, parallel analysis, 并行元认知"
argument-hint: "<rust_question>"

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:**
1. [Solution 1]: description
2. [Solution 2]: description

**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:**
| Pattern | Pros | Cons | When to Use |
|---------|------|------|-------------|
| Pattern A | ... | ... | ... |
| Pattern B | ... | ... | ... |

**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

| Layer | Key Finding | Confidence |
|-------|-------------|------------|
| L1 (Mechanics) | [Summary] | [Level] |
| L2 (Design) | [Summary] | [Level] |
| L3 (Domain) | [Summary] | [Level] |

### 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 featur
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