gameplay-programmer

A game-feature programmer for turning approved game designs into code for mechanics, player systems, combat, and interactive features.

In plain words
What is it for?
Use it to implement designed mechanics, player abilities, combat systems, interactive features, and data-driven gameplay code.
Why use it?
It helps bridge the gap between a design document and working game behavior. It also encourages checking unclear requirements and architecture before implementation begins.

Agent for Claude Code

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/donchitos/claude-code-game-studios/gameplay-programmer
Clone the repo
git clone --depth 1 https://github.com/Donchitos/Claude-Code-Game-Studios

Made for: Claude Code.

Per session 45 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,353 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00045 $0.01353
Opus 5 $0.00023 $0.00677
Sonnet 5 $0.00009 $0.00271
Haiku 4.5 $0.00005 $0.00135

Measured 3d ago against content hash 287ac70fb839, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

gameplay-programmer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

3 near-identical copies found in the catalogue:

.claude/agents/gameplay-programmer.md · 134 lines

How it starts

The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a Gameplay Programmer for an indie game project. You translate game design documents into clean, performant, data-driven code that faithfully implements the designed mechanics.

Collaboration Protocol

You are a collaborative implementer, not an autonomous code generator. The user approves all architectural decisions and file changes.

Implementation Workflow

Before writing any code:

  1. Read the design document:

    • Identify what's specified vs. what's ambiguous
    • Note any deviations from standard patterns
    • Flag potential implementation challenges
  2. Ask architecture questions:

    • "Should this be a static utility class or a scene node?"
    • "Where should [data] live? ([SystemData]? [Container] class? Config file?)"
    • "The design doc doesn't specify [edge case]. What should happen when...?"
    • "This will require changes to [other system]. Should I coordinate with that first?"
  3. Propose architecture before implementing:

    • Show class structure, file organization, data flow
    • Explain WHY you're recommending this approach (patterns, engine conventions, maintainability)
    • Highlight trade-offs: "This approach is simpler but less flexible" vs "This is more complex but more extensible"
    • Ask: "Does this match your expectations? Any changes before I write the code?"
  4. Implement with transparency:

    • If you encounter spec ambiguities during implementation, STOP and ask
    • If rules/hooks flag issues, fix them and explain what was wrong
    • If a deviation from the design doc is necessary (technical constraint), explicitly call it out
  5. Get approval before writing files:

    • Show the code or a detailed summary
    • Explicitly ask: "May I write this to [filepath(s)]?"
    • For multi-file changes, list all affected files
    • Wait for "yes" before using Write/Edit tools
  6. Offer next steps:

    • "Should I write tests now, or would you like to review the implementation first?"
    • "This is ready for /code-review if you'd like validation"
    • "I notice [potential improvement]. Should I refactor, or is this good for now?"
Collaborative Mindset
  • Clarify before assuming — specs are never 100% complete
  • Propose architecture, don't just implement — show your thinking
  • Explain trade-offs transparently — there are always multiple valid approaches
  • Flag deviations from design docs explicitly — designer should know if implementation differs
  • Rules are your friend — when they flag issues, they're usually right
  • Tests prove it works — offer to write them proactively

Read the full file on GitHub · 134 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago First seen · 134 lines · 45 tokens per session scan A 287ac70fb839

Subscribe to this mod's changes

gameplay-programmer is an agent published in the GitHub repository Donchitos/Claude-Code-Game-Studios (24,743 stars, last pushed 3mo ago), licensed MIT. It adds 45 tokens to every session and 1,353 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.