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Enchanted Plugins Roadmap

Vision: Build the algorithm-driven operating system for AI-assisted development. 20 plugins connected through an MCP client, each backed by a named formal algorithm.

Architecture Phases

Phase 1 (NOW)          Phase 2               Phase 3               Phase 4
5 plugins              MCP Client POC        10 plugins            Production MCP
Individual installs    Unified interface     Full coverage         Real-time dashboard
                                                                   Developer adoption

Foundation Infrastructure

Before the first plugin ships, the ecosystem needs one shared piece: the repo template every sibling is cloned from.

Repo Role Status
enchanter-ai/schematic Canonical repo template. Ships the 8-section CLAUDE.md, 10 shared/vis/conduct/*.md modules, docs/architecture/ auto-generation pipeline, plugins/example-subplugin/ skeleton, renderer toolchain. Never installed — cloned. Shipped

The template is the contract. When it drifts, all downstream siblings drift — so changes to schematic are treated as brand-standard changes, not per-plugin improvements.


Phase 1: Core 5 Plugins (Foundation)

The first 5 plugins answer the 5 fundamental questions of AI-assisted development.

# Plugin Question Algorithms Version Status
1 Wixie What did I say? (prompt quality) Gauss Convergence, Boolean SAT, Game Theory, Cross-Domain Adaptation v3.0.0 Shipped — 7 plugins
2 Emu What did I spend? (token health) Markov Drift, Shannon Compression, Linear Runway, Atomic Serialization v2.0.0 Shipped — 4 plugins
3 Crow What just happened? (change comprehension) Bayesian Trust, Semantic Diff, Information-Gain, Session Continuity v1.0.0 Shipped — 5 plugins
4 Hydra Is it safe? (security) Aho-Corasick, Shannon Entropy, Config Poisoning, Phantom Dependency, EMA Posture Decay v1.0.0 Shipped — 6 plugins
5 Pech What did it cost? (spend tracking) Exponential Smoothing, Budget Forecasting Not started

Milestone: 5 plugins shipped

  • Each plugin is a standalone Claude Code marketplace
  • Each follows @enchanter-ai brand standard
  • Each has named algorithms, managed agents, self-learning
  • Users install individually: /plugin marketplace add enchanter-ai/<name>

Phase 2: MCP Client POC (Unification)

Build enchanted-mcp — a Model Context Protocol client that connects all 5 plugins into a single orchestration layer.

What the MCP Client Does

enchanted-mcp
├── Connects to all installed enchanter-ai via MCP
├── Unified dashboard: prompts + tokens + changes + security + costs
├── Cross-plugin intelligence:
│   ├── Wixie detects bad prompt → Emu shows token waste from it
│   ├── Crow flags risky change → Hydra scans it for vulnerabilities
│   ├── Pech shows cost spike → traces to which plugin/session caused it
│   └── All learnings shared across plugins (Gauss Accumulation network)
└── Single install: `npx enchanted-mcp` or Docker container

Architecture

┌──────────────────────────────────────────────┐
│              enchanted-mcp (client)           │
│                                              │
│  ┌─────────┐ ┌─────────┐ ┌─────────┐       │
│  │  Wixie   │ │  Emu  │ │  Crow  │  ...  │
│  │  (MCP)  │ │  (MCP)  │ │  (MCP)  │       │
│  └────┬────┘ └────┬────┘ └────┬────┘       │
│       │           │           │              │
│  ┌────▼───────────▼───────────▼────┐        │
│  │     Cross-Plugin Intelligence    │        │
│  │     Shared learnings.json        │        │
│  │     Unified event bus            │        │
│  └──────────────────────────────────┘        │
│                                              │
│  ┌──────────────────────────────────┐        │
│  │     Dashboard (localhost:3000)    │        │
│  │     Real-time session overview    │        │
│  └──────────────────────────────────┘        │
└──────────────────────────────────────────────┘

Milestone: POC MCP client

  • Connects to Wixie + Emu + Crow + Hydra + Pech
  • Shared event bus for cross-plugin signals
  • Basic web dashboard showing unified session view
  • Cross-plugin learnings (Gauss Accumulation network)

Phase 3: 10 Plugins (Full Coverage)

Add 5 more plugins covering code quality, testing, DevOps, documentation, and API design.

# Plugin Question Algorithm Category
6 Lich Is this code good? Cousot Interval + Falleri Structural Diff + Zheng Pairwise Code review
7 Crucible Do the tests catch bugs? Genetic Mutation Testing Testing/QA
8 Assembler Can this deploy? Critical Path DAG Optimization DevOps/CI
9 Scribe Is the docs up to date? TF-IDF Extractive Summarization Documentation
10 Schema Is the API contract valid? Semantic Version Diffing API design

Retired: Athena (originally planned for slot #6) was retired before implementation. Lich replaces it with a more rigorous algorithm stack (Cousot Interval Analysis + Falleri Structural Diff + Zheng Pairwise Comparison) that provides static-analysis-grade code review rather than heuristic AST diff alone.

Milestone: 10 plugins + enhanced MCP

  • All 10 plugins connected to enchanted-mcp
  • Dashboard shows full development lifecycle
  • Cross-plugin intelligence covers: prompt → code → test → security → deploy → docs
  • Plugin-to-plugin event triggers (Crow flags change → Lich auto-reviews → Crucible tests)

Phase 4: Production MCP (Developer Adoption)

15 More Plugins

# Plugin Algorithm Category
11 Beacon Isolation Forest Anomaly Detection Observability
12 Nexus Topological Sort + Dependency DAG Multi-repo
13 Comply SPDX License Graph Resolver Compliance
14 Prism WCAG Rule Engine + axe-core Accessibility
15 Tempo Statistical Flame Graph Sampling Performance
16 Rosetta Levenshtein Fuzzy Deduplication i18n
17 Onboard Spaced Repetition (SM-2) Learning
18 Synapse CRDT Knowledge Merging Collaboration
19 Vault Three-Way Merge Diffing Database
20 Relay Event Sourcing + Saga Pattern Webhooks
21 Sylph Jaccard-Cosine Boundary Segmentation + Myers-Diff Conventional Classifier Git workflow (shipped early — v0.0.1, 9 plugins)

Production MCP Features

  • Real-time web dashboard with WebSocket updates
  • Team mode: shared learnings across developers
  • Cost alerts and budget enforcement
  • Plugin marketplace within the MCP (install/remove from dashboard)
  • API for external integrations (Slack, Linear, Jira)
  • Telemetry and analytics (opt-in)
  • Plugin SDK for third-party developers

Milestone: 21 plugins + production MCP

  • Full developer operating system
  • Every stage of AI-assisted development covered
  • Algorithm-driven, agent-managed, self-learning at every layer
  • Active developer community
  • Third-party plugin ecosystem

Timeline

Phase Milestone Plugins Target
1 Foundation 5 (Wixie, Emu, Crow, Hydra, Pech) — 4/5 shipped (Pech not started) Q2 2026
2 MCP POC 5 + MCP client Q3 2026
3 Full Coverage 10 + enhanced MCP Q4 2026
4 Production 21 + production MCP — Sylph (#21) shipped early Q1 2027

Naming Convention

Every plugin is named after a game entity that metaphorically describes its function.

Plugin Entity Game Why
Wixie Enchantment Orbs Minecraft XP orbs that power the enchantment table — enchanting prompts
Emu Emu Mob Minecraft Flying creature that collects items and brings them to you — collecting tokens
Crow Crow Hollow Knight Ravenant protector who watches, tests, and judges from the shadows — watching changes
Hydra Hydra Leviathan Subnautica You hear it before you see it. Hunts in the dark. Relentless. Nothing gets past it — security scanning
Pech Tom Pech Animal Crossing Merchant-banker who tracks every bell you owe — cost accounting
Athena Athena Hades Goddess of wisdom who judges your combat quality and grants boons for excellence — code review
Crucible Crucible Terraria Endgame crafting station forged in hellfire — tests things to destruction — mutation testing
Assembler Assembling Machine Factorio Takes parts in, produces artifacts out, chains into automated pipelines — CI/CD building
Sylph Sylphs Hollow Knight Silk-spinners and Crow's ancestral kin who weave threads into coherent patterns — weaving branches, commits, and PRs into one history

Brand Standard (All Plugins)

Every @enchanter-ai product must:

  1. Name every engine after a formal algorithm
  2. Delegate background work to managed agents (Opus/Sonnet/Haiku)
  3. Persist learning across sessions (Gauss Accumulation)
  4. Report honest numbers — never inflate claims
  5. Use atomic operations and handle race conditions
  6. Maintain zero external dependencies (bash + jq for hooks, Python stdlib for scripts)
  7. Include tests, dark-themed PDF reports, and comprehensive documentation
  8. Follow the Emu-style plugin marketplace structure

Algorithm Registry

Every named algorithm across the ecosystem:

ID Name Product Engine
F1 Gauss Convergence Wixie Standard deviation minimization
F2 Boolean SAT Overlay Wixie Hybrid SAT + continuous optimization
F3 Cross-Domain Adaptation Wixie Constraint-preserving model translation
F4 Game-Theoretic Security Wixie Zero-sum adversarial robustness
F5 Static-Dynamic Verification Wixie Structure + behavior dual testing
F6 Gauss Accumulation Wixie Cross-session knowledge persistence
A1 Markov Drift Detection Emu Hidden state transition recognition
A2 Linear Runway Forecasting Emu Token consumption prediction
A3 Shannon Compression Emu Information-theoretic output reduction
A4 Atomic State Serialization Emu Bounded checkpoint persistence
A5 Content-Addressable Dedup Emu Hash-based read deduplication
H1 Semantic Diff Compression Crow Multi-file change clustering
H2 Bayesian Trust Scoring Crow Prior-posterior change risk assessment
H3 Information-Gain Decision Crow Review prioritization by uncertainty reduction
H4 Session Continuity Graph Crow Decision-causal relationship persistence
H5 Adversarial Self-Review Crow Specific concern generation for risky changes
H6 Gauss Learning (Crow) Crow Developer preference accumulation
R1 Aho-Corasick Pattern Hydra Multi-pattern secret scanning
R2 Shannon Entropy Analysis Hydra High-entropy string detection
R3 OWASP Vulnerability Graph Hydra Vulnerability pattern detection
R4 Markov Action Classification Hydra Dangerous command classification
R5 Config Poisoning Detection Hydra Malicious config interception at SessionStart
R6 Phantom Dependency Detection Hydra Slopsquatting / dependency confusion detection
R7 Subcommand Overflow Hydra Subcommand injection and overflow detection
R8 EMA Posture Decay Hydra Cross-hook EMA threat-rate decay (α=0.3; Roberts 1959)
L1 Exponential Smoothing Pech Cost forecasting
L2 Budget Boundary Detection Pech Spend threshold alerting
W1 Myers-Diff Conventional Classifier Sylph Diff-to-Conventional-Commits classification
W2 Jaccard-Cosine Boundary Segmentation Sylph Task-boundary clustering from edit-event stream (defining engine)
W3 Workflow-Pattern Classifier Sylph Repo-signal → branching-model inference
W4 Path-History Reviewer Routing Sylph Blame-graph reviewer suggestion
W5 Gauss Learning (Sylph) Sylph Developer workflow-preference accumulation

This is a living document. Update as plugins ship and algorithms evolve. Sylph W1–W5 are seed names from prompts/sylph-architecture/ — final names emerge from the architecture prompt's output.