Agent skill

Meta Cognition Parallel

by majiayu000 in majiayu000/claude-skill-registry

EXPERIMENTAL: Three-layer parallel meta-cognition analysis. An agent skill from majiayu000/claude-skill-registry.

MITAuto-check passedAgent Workflows

Install Meta Cognition Parallel

skills CLI
$ npx skills add majiayu000/claude-skill-registry --skill meta-cognition-parallel -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install majiayu000/claude-skill-registry meta-cognition-parallel --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/analysis/meta-cognition-parallel .claude/skills/meta-cognition-parallel && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
meta-cognition-parallel
GitHub stars
666
Used in
1 other repo
Token cost
~2.1k tokens
SKILL.md length
323 words
Files
2
Skills in repo
1,273
Repo updated
First seen
Licence
MIT

At a glance

EXPERIMENTAL: Three-layer parallel meta-cognition analysis. An agent skill from majiayu000/claude-skill-registry.

  • Works in 9 steps: Parse User Query → Launch Three Parallel Agents → Collect Results → …
  • : /meta-parallel
  • SKILL.md covers Concept, Usage, Execution Mode Detection and Agent Mode (Plugin Install) -…, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Meta Cognition Parallel is an agent skill from majiayu000/claude-skill-registry. EXPERIMENTAL: Three-layer parallel meta-cognition analysis. Triggers on: /meta-parallel, 三层分析, parallel analysis, 并行元认知

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `metadata.json`).

It sits in Agent Workflows. The repository describes itself as: Searchable Claude Code skills catalog with source-linked guides and generated registry artifacts. The licence is MIT.

When your agent uses it

  • : /meta-parallel
  • Parallel analysis

Example prompts

  • “/meta-cognition-parallel”

Workflow steps

9 steps, taken from the step headings in SKILL.md.

  1. Parse User Query
  2. Launch Three Parallel Agents
  3. Collect Results
  4. Cross-Layer Synthesis
  5. Parse User Query
  6. Execute Layer 1 - Language Mechanics
  7. Execute Layer 2 - Design Choices
  8. Execute Layer 3 - Domain Constraints
  9. Cross-Layer Synthesis

What it can do on your machine

Read from SKILL.md and the folder at commit 2d14a69. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Meta Cognition Parallel loads about 2.1k tokens when it runs. Until then it costs about 36 tokens; SKILL.md has 323 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~36
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from majiayu000/claude-skill-registry at commit 2d14a69, republished under its MIT licence (© majiayu000). 323 words, ~2,095 tokens.

Download SKILL.mdSave it as .claude/skills/meta-cognition-parallel/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
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:

markdown
## 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:

markdown
## 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:

markdown
## 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:

markdown
## 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 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:

markdown
# 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:**
```rust
// 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.

© majiayu000, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in skills/analysis/meta-cognition-parallel of majiayu000/claude-skill-registry.

  • SKILL.md
  • metadata.json

Open the folder on GitHubat commit 2d14a69

Used in 1 other repository

We found 7 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in majiayu000/claude-skill-registry, which our catalogue first saw on October 7, 2026.

Compare with similar skills

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Using Superpowersfarm-fe/farm5.6k35 repos~1.4kAutomated safety check: PassMIT
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Categories

Questions about Meta Cognition Parallel

What does Meta Cognition Parallel do?

EXPERIMENTAL: Three-layer parallel meta-cognition analysis. An agent skill from majiayu000/claude-skill-registry. Meta Cognition Parallel is an agent skill from majiayu000/claude-skill-registry. EXPERIMENTAL: Three-layer parallel meta-cognition analysis.

When should I use Meta Cognition Parallel?

Meta Cognition Parallel fits situations like: : /meta-parallel; parallel analysis.

How do I install Meta Cognition Parallel in Claude Code?

Run `npx skills add majiayu000/claude-skill-registry --skill meta-cognition-parallel -a claude-code`. Or copy the skill folder (skills/analysis/meta-cognition-parallel in majiayu000/claude-skill-registry) into .claude/skills/meta-cognition-parallel in your project. Claude Code loads it when a task matches its description.

How do I install Meta Cognition Parallel in Codex?

Run `npx skills add majiayu000/claude-skill-registry --skill meta-cognition-parallel -a codex`. Or copy the skill folder (skills/analysis/meta-cognition-parallel in majiayu000/claude-skill-registry) into .agents/skills/meta-cognition-parallel in your project. Codex loads it when a task matches its description.

Can I use Meta Cognition Parallel in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add majiayu000/claude-skill-registry --skill meta-cognition-parallel -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/meta-cognition-parallel, .gemini/skills/meta-cognition-parallel, .github/skills/meta-cognition-parallel and .opencode/skills/meta-cognition-parallel in your project.

What does Meta Cognition Parallel need to run?

SKILL.md names no scripts, command-line tools or credentials: Meta Cognition Parallel is instructions for the agent only.

Does Meta Cognition Parallel access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Meta Cognition Parallel safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Meta Cognition Parallel use?

Meta Cognition Parallel is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Meta Cognition Parallel use?

About 2.1k tokens (SKILL.md is roughly 8.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Meta Cognition Parallel?

Skills that share tags, products or a category with Meta Cognition Parallel: MCP Server Builder (anthropics/skills, 180k stars), Hook Development for Claude Code Plugins (anthropics/claude-plugins-official, 38k stars), Using Superpowers (farm-fe/farm, 5.6k stars) and Executing Plans Inline (obra/superpowers, 296k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Meta Cognition Parallel?

majiayu000 (a GitHub user) maintains it in majiayu000/claude-skill-registry, which has 666 GitHub stars. The repository holds 1,273 skills in this directory. The repository was last updated on October 7, 2026.

Source: majiayu000/claude-skill-registry on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.