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Versus for Copilot

Versus for Copilot

Jasmine Moreira

| (0) | Free
IACDM (Iterative Adversarial Convergence Development Methodology) orchestrator for GitHub Copilot Agent Mode. After initializing a project, start a new Copilot chat session for the methodology to activate.
Installation
Launch VS Code Quick Open (Ctrl+P), paste the following command, and press enter.
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Versus for Copilot

IACDM (Iterative Adversarial Convergence Development Methodology) orchestrator for GitHub Copilot Agent Mode.

An original methodology created by Jasmine Moreira that transforms LLMs from reactive code generators into disciplined agents following a structured 8-phase process — from problem discovery to delivery with tests and post-review.

Why?

AI coding tools (Lovable, Cursor, Claude Code, ChatGPT) all share the same fundamental limitation: zero internal verification capability. They generate statistically plausible output without distinguishing correct code from incorrect code. The METR study (2025) showed experienced developers using AI tools were actually 19% slower — despite believing they were 20% faster.

The real distinction isn't between tools — it's between process and no process.

Versus implements the AG/AV (Generative Agent / Verification Agent) model: the AI generates, external agents (automated tests + human operator) verify at discrete gates. Errors are caught at the earliest possible phase, not in production.

Features

  • 8 sequential phases with verifiable exit criteria — no skipping steps
  • 8 safeguards (S0-S7) that prevent common AI agent errors (premature convergence, scope creep, reimplementation)
  • Convergence score (0-100) that gates advancement until the problem is truly understood
  • 15 MCP tools for state management, decision recording, and phase transitions
  • Persistent decision registry that survives context switches
  • Gateway guard that detects when models skip loading context
  • Adversarial critique with 7 universal + 8 conditional specialized lenses
  • VS Code sidebar showing methodology state in real time
  • Multi-session testing protocol for Phase 6 continuity across sessions
  • Meta-iteration (v1→v2): start_new_cycle() resets to Phase 0 preserving all decisions, specs/, and history

How It Works

Phase 0: Problem Discovery    → HSA 5-level exploration (score >= 90 to advance)
Phase 1: Architecture         → Define modules, interfaces, patterns
Phase 2: Adversarial Critique → Attack the architecture with specialized lenses
Phase 3: Simplification       → Address criticals, simplify (loops with Phase 2)
Phase 4: Convergence Gate     → Validate all exit criteria + safeguards
Phase 5: Implementation       → Code the final architecture
Phase 6: Tests                → 100% passing + exploratory testing
Phase 7: Post-Review          → Double-loop learning: evaluate product AND process

Phase 0: Hierarchical Semantic Analysis (HSA)

The most distinctive contribution. Structures problem exploration in 5 levels, each building on the previous:

Level Focus What is sought
1. Domain Universe where the problem exists Vocabulary, theoretical/technical field, tools, state of the art
2. Problem What needs to be solved 5W1H: who, what, when, where, why, how solved today
3. Elements Parts composing the problem Components, entities, actors, constraints
4. Processes How parts relate Flows, transformations, dependencies, feedback cycles
5. Product Expected outcome Deliverables, acceptance criteria, success metrics

Context Efficiency

The methodology maximizes E = I₀/C (relevant information / total context consumed) through granularization: each session focuses on one module with just its interface signatures, keeping context efficiency near 1.0 instead of degrading to 0.3+ in monolithic sessions.

Quick Start

  1. Install the extension
  2. Open the Command Palette (Ctrl+Shift+P) and run Versus Copilot: Initialize Project
  3. Enter a project name and description when prompted
  4. Open a new Copilot Agent Mode conversation
  5. Type start — the agent loads methodology state and begins Phase 0

Important: After initializing, always start a new conversation so Copilot picks up the MCP server and hooks. If the agent doesn't use MCP tools, run Developer: Reload Window from the Command Palette.

The 8 Safeguards

ID Name Protects Against
S0 Problem Convergence Advancing without understanding the problem
S1 Anti-Bug Simplification that introduces bugs
S2 Stopping Criterion AI deciding when to stop (user's decision)
S3 Premature Convergence Stopping iteration too early
S4 Explicit Verification Skipping human validation at gates
S5 Scope Preservation Scope creep during critique-simplification
S6 Do Not Reimplement Recreating what already exists
S7 Sequence Discipline Starting tangential discussions during implementation

The AG/AV Model

F₀ → G₀ → F₁ → G₁ → ... → Fₙ → Gₙ → delivery
      ↑              ↑                    ↑
  AV evaluates   AV evaluates        AV evaluates
  • AG (Generative Agent): The LLM. Produces artifacts without verification capability.
  • AV-automatic: Tests, linters, compilers — binary verdict on formalizable properties.
  • AV-human: The operator — evaluates semantic adequacy, usability, domain correctness.
  • Gate (Gₖ): Discrete point where progression requires AV approval. Rejection feeds concrete error information back to AG.

Requirements

Requirement Minimum Why
VS Code >= 1.99.0 Extension API compatibility
Node.js >= 18.0.0 Runs the MCP server (node .versus/server.js)
GitHub Copilot Latest Agent Mode for MCP tools and hooks

Warning: Node.js is mandatory. Without it, the MCP server cannot start and the agent will ignore the methodology entirely. Install from nodejs.org.

Companion Extension

Use Versus for Claude for Claude Code integration. Both extensions share the same .versus/state.json format.

License

MIT - Created by Jasmine Moreira.

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