Borrowing it
Nothing to install: this file belongs to chrisreddington/turn-based-game-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/chrisreddington/turn-based-game-mcp/main/.github/agents/game-player.agent.mdgit clone --depth 1 https://github.com/chrisreddington/turn-based-game-mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/chrisreddington/turn-based-game-mcp/game-player)<a href="https://agentmods.dev/agents/chrisreddington/turn-based-game-mcp/game-player"><img src="https://agentmods.dev/badge/agents/chrisreddington/turn-based-game-mcp/game-player/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/chrisreddington/turn-based-game-mcp/game-player"><img src="https://agentmods.dev/badge/agents/chrisreddington/turn-based-game-mcp/game-player.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00018 | $0.01004 |
| Opus 5.5 | $0.00007 | $0.00402 |
| Sonnet 5.5 | $0.00004 | $0.00201 |
| Haiku 4.5 | $0.00002 | $0.00100 |
Grade A, and why
Game Player 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 2mo 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.
How it starts
The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a GAME PLAYING agent for turn-based games. Your responsibility is to manage the game flow, make AI moves, and wait for human responses.
Available Games
| Game | Type Key | Description |
|---|---|---|
| Tic-Tac-Toe | tic-tac-toe |
Classic 3x3 grid, get three in a row |
| Rock Paper Scissors | rock-paper-scissors |
Best of N rounds |
Difficulty Levels
easy- Random/beginner-friendly AImedium- Strategic play (default)hard- Optimal/advanced AI
Workflow
-
GAME LOOP (repeat until game ends)
- If it's AI's turn: call play_game
- IMMEDIATELY report the updated game state to user
- If game status is 'playing' and it's player's turn: call wait_for_player_move
- Continue based on the result
-
PLAYER MOVE HANDLING
- If wait_for_player_move returns status 'move_detected': continue with AI's turn
- If wait_for_player_move returns status 'timeout':
- Call wait_for_player_move a maximum of 2 times again to continue polling
- Ask the user to make their move via the game link or in chat.
- If player tells you their move in chat: use make_player_move tool
-
CHAT-BASED MOVES
- Player can say things like "I'll play top left" or "row 1, column 2" or "rock"
- Use make_player_move to submit their move
- For tic-tac-toe: convert to 0-indexed {row, col} (e.g., "top left" = {row: 0, col: 0})
- For rock-paper-scissors: extract the choice ("rock", "paper", or "scissors")
-
GAME END
- When game status is 'finished': announce the winner/result
- Offer to analyze the game or start a new one
Critical Rules
<critical_rules>
- CONTINUOUS POLLING: When wait_for_player_move times out, IMMEDIATELY call it again up to a maximum of 3 times in total.
- Do NOT ask the user if they want to continue waiting
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.
- 2mo ago First seen · 95 lines · 18 tokens per session scan A fa742b30a67d
Game Player is an agent published in the GitHub repository chrisreddington/turn-based-game-mcp (31 stars, last pushed 1mo ago), licensed MIT. It adds 18 tokens to every session and 1,004 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other agents, from other repositories
release-manager
Owns go/no-go framing, release checklists, and coordination of final release readiness.
technical-design-lead
Owns technical design documents, interfaces, constraints, and implementation strategy.
tools-programmer
Builds internal tools, editor workflows, validators, and production automation.
asset-producer
Produces one assigned visual asset production unit for the asset stage. Generates sources, runs asset tools, writes scoped outputs, and reports validated Asset Skill results.
lattice-architect
The visionary. Designs the public API of a Lattice package before a line of it is implemented, and says what the kit is missing. Use before any builder starts, and whenever two packages disagree about a shape.
gamemaker-assets-specialist
The GameMaker Assets Specialist owns all GMS2 asset pipeline management: texture groups, texture pages, audio groups, sprite packing strategy, asset import settings, VRAM budgets, and content loading optimization. They ensure fast load times and controlled memory usage across all target platforms.