Studio Copilot Overview

Studio Copilot is the built-in AI assistant for ED5 MMO Studio. It understands the engine, the editor, and your project data, then uses real tools to help you build.

Where It Appears

Studio Copilot can appear in:

• Studio Web.
• The Admin editor.
• The desktop Studio app.
• External MCP clients through Creator MCP.

What Makes It Different

Generic AI can describe a game idea. Studio Copilot can operate the Studio tool layer.

It can:

• Search and read your project records.
• Create and update structured game content.
• Generate assets and link them to entities.
• Validate content after changes.
• Run playtest simulations for selected scenarios.
• Remember project-specific style and lore notes.

What Context It Uses

Studio Copilot is designed to be both engine-aware and project-aware.

Depending on the task, it can ground itself with:

• Engine docs and schema knowledge.
• Your current project records such as items, quests, mobs, NPCs, zones, and media.
• The page or editor surface you are currently on.
• Prior thread context and project memory such as style rules, lore, naming conventions, or banned content.
• Validation feedback from previous runs.

The goal is not just to answer from model memory, but to act from current project truth.

The Run Flow

Most requests follow this flow:

• You give a goal.
• The assistant gathers context from your current project.
• It plans tool-backed steps.
• Risky work is gated by approval or your autopilot policy.
• Tools run through the gateway.
• Results, IDs, artifacts, and validation summaries are returned.

In practice, a strong run usually looks like this:

1. You describe the outcome you want. 2. Copilot inspects the relevant records, screen context, or docs. 3. It proposes a short plan. 4. You approve the writes, or let autopilot continue within your rules. 5. Copilot creates or updates records, imports assets, or runs validations. 6. It closes with concrete proof: what changed, what was created, what validation passed, and what still needs review.

What A Good Result Looks Like

A useful Studio Copilot answer should not end at vague prose. It should leave you with evidence.

Typical run outputs include:

• Record names, IDs, or linked entities that were created.
• A summary of fields that changed.
• Imported asset names or generated media candidates.
• Validation results or playtest findings.
• Follow-up options for iteration.

If a run changes nothing, the assistant should still tell you why: missing permission, invalid target, model/provider issue, or a validation failure.

Risk Classes

For the operating model around approvals and autopilot, see Approvals, Autopilot & Safety.

Public Versus Internal AI Tools

Creator tools are user-facing and project-scoped. Platform tools are internal and used by ED5 developers for testing, admin, database checks, and deployment validation.

External clients such as Claude only receive the Creator MCP tool list.

Best-Fit Tasks For Copilot

Studio Copilot is strongest when the task has a clear target and can be checked afterward. Good examples:

• Draft a new item family from an existing biome or faction theme.
• Review an NPC dialogue tree for missing branches or reward links.
• Create a starter quest chain and validate the NPC references.
• Generate item icon variants and link the chosen one.
• Inspect a zone and report missing spawn, objective, or loot coverage.
• Summarize how a system works using your current project as examples.

Less effective prompts are broad and underconstrained, such as "make my whole game better" without naming the area, audience, or success criteria.

Project Memory

Project memory is where Copilot stores durable context that should outlive a single chat run.

Useful memory examples include:

• World lore and canon rules.
• Naming patterns for factions, towns, or items.
• Art direction notes.
• Balance rules such as rarity targets or low-level stat ceilings.
• Content that must be avoided.

Use project memory for stable rules. Use the chat thread for one-off tasks.

In-App Copilot Versus Creator MCP

Use the built-in copilot when you want the assistant anchored to the page you are actively editing.

Use Creator MCP when you want to work from Claude or another external client and still call the same project-safe tool surface.

Both paths are meant to converge on the same core behavior: inspect, plan, ask when needed, act through tools, and return proof.

Privacy Notes

The assistant should send only the context needed for the current task to model providers. API keys are verified server-side and are not exposed to browser JavaScript after creation.

Review generated content before shipping your live game.

Next: Approvals, Autopilot & Safety and Providers & AI Credits.