Game Design Prototyping Companion

Game Design Prototyping Companion

Track prototype evolution, not just prototype results.

Use this skill when prototyping produces branching decisions, dead ends, alternative paths, and backtracking. The aim is to preserve learning structure: what was tested, what was learned, what branch it created, which path was followed, and which paths remain available to revisit.

This skill can also generate a simple SVG branch map from a lightweight text or JSON structure.

What to produce

Generate one or more of these outputs:

1. Prototype log - what was tested and why
2. Branch record - what paths emerged from the result
3. Decision state - which branch is current, parked, dead, baseline, or promising
4. Backtrack notes - what can be revisited later and under what condition
5. SVG branch map - a visual map of prototype evolution

Core principle

A prototype is not just a yes/no answer. It often creates a tree:

• one branch becomes the current path
• another becomes a dead end
• another becomes a parked idea worth revisiting later
• another reveals a stronger question than the original one

The skill should preserve that tree.

Workflow

1. Define the prototype node

For each prototype node, record:

• Node ID
• Prototype name
• Question being tested
• What was built or simulated
• What was learned
• Result state

Use result states such as:

• baseline
• promising
• branch trigger
• dead end
• parked
• production candidate

2. Record branch options

When a prototype produces several next moves, capture each branch explicitly.

For each branch, record:

• Branch ID
• Parent node
• New idea or variation
• Reason it exists
• Current status

3. Mark the chosen path without deleting the others

Do not treat the selected branch as the only meaningful output. Preserve:

• abandoned paths
• deferred paths
• weird side paths
• stronger substitute ideas revealed by the test

4. Add backtrack logic

If a branch is not chosen now, record:

• what would justify revisiting it
• what blocker currently prevents it
• what later discovery might make it relevant again

5. Generate a visual map when useful

Use scripts/branch_map_svg.py to render a simple SVG from a branch-map JSON file.

Read:

• references/branch-map-format.md for the input structure
• references/example-branch-map.json for an example

Response structure

Use this structure unless the user asks for something else:

Prototype Node

• Node ID: ...
• Question: ...
• Built / simulated: ...
• Learned: ...
• State: ...

Branches Created

1. ...
2. ...
3. ...

Current Chosen Path

• ...

Parked / Revisit Later

• ...

Suggested Next Prototype

• ...

Visualization workflow

When the user wants a visual branch map:

1. write the branch data to JSON using the format in references/branch-map-format.md
2. run scripts/branch_map_svg.py <input.json> <output.svg>
3. return the SVG path and summarize what the map shows

Style rules

• Preserve branching history.
• Prefer explicit node IDs over vague prose.
• Distinguish clearly between what was learned and what was merely assumed.
• Do not erase dead ends; label them.
• Do not confuse the current path with the best possible path forever.

References

• references/branch-map-format.md for the JSON structure
• references/example-branch-map.json for a starter example
• references/state-labels.md for recommended branch/node labels

Working principle

Prototype trees are design memory. If you only remember the path you chose, you lose the intelligence of the paths you rejected.