Magi

                              新  世  紀
███████ ██    ██  █████  ██    ██  █████  ███████ ██      ██  █████  ██    ██
██      ██    ██ ██   ██ ███   ██ ██      ██      ██      ██ ██   ██ ███   ██
█████    ██  ██  ███████ ██ ██ ██ ██  ███ █████   ██      ██ ██   ██ ██ ██ ██
██        ████   ██   ██ ██  ████ ██   ██ ██      ██      ██ ██   ██ ██  ████
███████    ██    ██   ██ ██   ███  █████  ███████ ███████ ██  █████  ██   ███
                           エヴァンゲリオン

MAGI SYSTEM

"One mind is a hypothesis. Three minds are a verdict."

A Claude Code plugin that brings the MAGI supercomputer council from Neon Genesis Evangelion into your terminal. Three AI agents — each powered by Claude Opus — deliberate your engineering decisions in parallel, scoring 12 dimensions simultaneously. A fourth agent, MAGI Core, synthesizes their evaluations with sycophancy detection and bias calibration.

Just as the original MAGI reflected the three facets of Dr. Naoko Akagi's personality, each agent embodies a distinct cognitive framework — with built-in cognitive resistance to prevent LLM convergence.

Installation

Plugin (Recommended)

Run inside Claude Code interactive mode:

/plugin marketplace add ohta-rh/magi-system
/plugin install magi@magi-plugins

Manual Symlink

git clone https://github.com/ohta-rh/magi-system.git
ln -s "$(pwd)/magi-system/plugins/magi/skills/magi" ~/.claude/skills/magi
# The personas are plugin-native agents — link them too:
mkdir -p ~/.claude/agents
ln -s "$(pwd)"/magi-system/plugins/magi/agents/*.md ~/.claude/agents/

The plugin install is recommended — it registers skills, agents, and hooks in one step.

Requires Claude Code.

Usage

# Full deliberation
/magi Should we migrate from REST to GraphQL?

# Comparison mode (auto-detected)
/magi React Server Components vs traditional SPA architecture

# Quick triage (single-agent, Sonnet — fast and cheap)
/magi-quick Is adding Redis caching worth the complexity?

# Code review via git diff
/magi-review

# Pre-mortem failure analysis
/magi-premortem Rewrite the auth system in Rust

# With dialectic round (inter-agent rebuttals)
/magi Should we adopt microservices? --dialectic

# With adversarial challenge (devil's advocate)
/magi Migrate to Kubernetes --adversarial

The Three MAGI

              ┌──────────────────┐
              │  BALTHASAR · 2   │
              │    「Mother」      │
              └────────┬─────────┘
                      ╱ ╲
                    ╱ MAGI ╲
                  ╱  CORE   ╲
 ┌──────────────┴──┐   ┌──────┴───────────┐
 │  CASPAR  ·  3   │───│  MELCHIOR  ·  1  │
 │   「Woman」       │   │  「Scientist」    │
 └─────────────────┘   └──────────────────┘

MELCHIOR-1 — The Scientist

"Show me the benchmark, or it didn't happen."

The cold eye of technical truth. Reasons through the Scientific Method — forming falsifiable hypotheses, seeking disconfirmation, updating beliefs with Bayesian rigor. Explicitly anti-sycophantic: states findings bluntly, actively resists the tendency to soften negative judgments.

Axis	What it measures
Correctness & Rigor	Algorithm correctness, edge cases, fault tolerance, type safety
Performance & Efficiency	Computational complexity, memory, throughput, latency, scalability
Security	Threat model, attack surface, auth design, data protection
Technical Consistency	Architecture alignment, design principles, dependency fitness

BALTHASAR-2 — The Mother

"Will the on-call engineer at 3 AM understand this code?"

The guardian of long-term survival. Evaluates across three time horizons — 1 month, 6 months, 2 years. Designs for the weakest link. Cognitive resistance: must articulate the worst-case scenario at the 2-year horizon before approving.

Axis	What it measures
Maintainability & Readability	Code comprehensibility, naming, separation of concerns
Testability	Unit/integration test ease, mockability, testable design
Operability & Observability	Logging, metrics, alerting, deployment, rollback
Team Impact	Learning curve, onboarding burden, documentation, skill alignment

CASPAR-3 — The Woman

"Correct but ugly is just a different kind of wrong."

The voice of intuition and strategic vision. Reasons through Pattern Recognition and Aesthetic Judgment — forming a gestalt impression, reading the political terrain, calculating opportunity costs. Cognitive resistance: must name the best alternative NOT chosen before approving.

Axis	What it measures
Design Elegance	API beauty, abstraction quality, DX, interface intuitiveness
Innovation & Competitiveness	Paradigm adoption, differentiation, trend alignment
Feasibility	Implementation cost, timeline realism, incremental adoption
Adaptability & Extensibility	Future-proofing, extension points, pluggability

---

Voting: 3:0 unanimous (high confidence) / 2:1 majority (medium) / 1:1:1 indeterminate

Why Three?

A single reviewer has blind spots. Two create deadlocks. Three create a verdict — with a built-in mechanism to surface dissent. When MELCHIOR and CASPAR approve but BALTHASAR dissents, you know the proposal is technically sound and elegant but has a sustainability problem. The split is the insight.

Architecture

User → /magi "topic"
         │
    ┌────┴─────┐
    │ SKILL.md  │  Thin orchestrator
    └────┬──────┘
         │ Parallel launch by subagent_type (Opus)
    ┌────┼────────────┐
    ▼    ▼            ▼
 MELCHIOR BALTHASAR  CASPAR    Plugin-native persona agents
    │    │            │        (persona = system prompt)
    └────┼────────────┘
         │ If agent fails → 1 retry
         ▼
    ┌──────────┐
    │ MAGI Core │  Synthesis (Opus)
    └────┬──────┘  Extraction → Bias detection → Voting →
         │         Tension analysis → Output formatting
         ▼
    Deliberation Report
         │
         │ If 2:1 split → auto micro-dialectic
         ▼
    Phase 5: Interactive drill-down

Key design principle: The orchestrator does not perform judgment. MAGI Core is a separate agent ensuring true encapsulation.

Features

Sycophancy Detection

MAGI Core detects AI bias patterns in agent responses:

• Uniformly high scores with generic rationales
• Approve verdict despite substantive risks
• Critical risk dismissed without justification
• Overcorrection: uniformly harsh without evidence

Confidence is reduced when bias is detected.

Auto Micro-Dialectic

On 2:1 splits, the dissenter is automatically re-spawned for a brief rebuttal — no flag needed. The dissenter sees the majority's average score and must state whether they maintain their position.

Cross-Axis Tension Visualization

MAGI Core surfaces trade-offs between agents' axes:

Key Trade-offs:

• MELCHIOR Security:5 vs CASPAR Feasibility:2 — secure approach impractical at current team size
• BALTHASAR Operability:2 vs MELCHIOR Performance:5 — fast but unobservable in production

Risk Severity & Reversibility

Risks are classified as critical / moderate / informational. Each judgment includes a reversibility rating (Low/Medium/High). Low reversibility + Medium confidence triggers a caution warning.

Persistent Calibration Memory

MAGI Core keeps an agent memory across deliberations (~/.claude/agent-memory/magi-core/). Observed bias patterns accumulate over time and sharpen Calibration Notes — but memory never alters scores or verdicts, only confidence.

Comparison Mode

"A vs B" topics automatically produce a Score Matrix with per-agent recommendations:

| Agent | Axis | GraphQL | gRPC |
|-------|------|:---:|:---:|
| MELCHIOR | Correctness | 5 | 4 |
| MELCHIOR | Performance | 4 | 5 |
| ...

Five Skills

Skill	Purpose
/magi	Full council deliberation (3 agents + synthesis)
/magi-quick	Single-agent triage (Sonnet, fast)
/magi-review	Git diff-aware code review
/magi-premortem	Assume failure, reason backward
Dialectic/Adversarial	--dialectic / --adversarial flags

Configuration

Drop magi.config.json in your project root to customize agents:

{
  "agents": [
    { "name": "THREAT-MODEL", "persona": "Security threat analyst", "file": "agents/threat.md" },
    { "name": "COMPLIANCE", "persona": "Regulatory specialist", "file": "agents/compliance.md" },
    { "name": "ARCHITECTURE", "persona": "System architect", "file": "agents/arch.md" }
  ],
  "dialectic": true,
  "adversarial": false
}

Requirements: odd N >= 3 voting agents. Add "role": "advisory" for non-voting agents.

Development

Testing

bash tests/test-extraction.sh    # 15 schema validation tests
bash tests/test-e2e.sh           # 8 integration tests (vote tally, dissenter ID)
bash scripts/check-sizes.sh      # Governance limits + Current value verification

Pre-commit Hook

git config core.hooksPath .githooks

Auto-runs governance and extraction tests on plugin commits.

Governance

File size limits enforced by check-sizes.sh:

Category	Limit
SKILL.md (orchestrator)	500 lines
magi-core.md (meta-agent)	200 lines
Persona agents	150 lines
Reference / example files	100 lines

Project Structure

magi-system/
├── .claude-plugin/marketplace.json
├── .githooks/pre-commit
├── plugins/magi/
│   ├── .claude-plugin/plugin.json
│   ├── agents/                      # Plugin-native agents (frontmatter + system prompt)
│   │   ├── magi-core.md             # Synthesis + bias detection
│   │   ├── melchior.md              # The Scientist
│   │   ├── balthasar.md             # The Mother
│   │   └── caspar.md                # The Woman
│   ├── hooks/hooks.json             # Plugin-shipped log validation hook
│   ├── scripts/validate-log.sh      # Deliberation log schema check
│   └── skills/
│       ├── magi/                    # Full deliberation
│       │   ├── SKILL.md             # Thin orchestrator
│       │   ├── references/          # Schema, rules, formats
│       │   └── examples/            # Sample output
│       ├── magi-quick/              # Single-agent triage
│       ├── magi-review/             # Git diff review
│       └── magi-premortem/          # Failure analysis
├── scripts/                         # Validation & governance
└── tests/                           # Fixtures & test suites

FAQ

Q: What if all three disagree? A: "Indeterminate" verdict — the decision is deferred to you, Commander.

Q: Does it detect when I'm asking about non-engineering topics? A: Yes. MAGI will refuse to deliberate on topics that cannot be scored on its engineering axes.

Q: Can MAGI evaluate itself? A: Yes. The v6 roadmap was created by MAGI deliberating on its own improvement proposals — 27 proposed, 15 closed by 3:0 ruling.

License

MIT

---

    _人人人人人人人人人人人_
    ＞  問題ない。        ＜
    ＞  全ては計画通りだ。＜
    ￣Y^Y^Y^Y^Y^Y^Y^Y^Y^Y￣
             — Gendo Ikari