Borrowing it
Nothing to install: this file belongs to houseworthe/claude-royale. 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/houseworthe/claude-royale/main/.claude/agents/player-eval.mdgit clone --depth 1 https://github.com/houseworthe/claude-royaleWrote 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/houseworthe/claude-royale/player-eval)<a href="https://agentmods.dev/agents/houseworthe/claude-royale/player-eval"><img src="https://agentmods.dev/badge/agents/houseworthe/claude-royale/player-eval/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/houseworthe/claude-royale/player-eval"><img src="https://agentmods.dev/badge/agents/houseworthe/claude-royale/player-eval.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 | $0.00021 | $0.02185 |
| Opus 5.5 | $0.00008 | $0.00874 |
| Sonnet 5.5 | $0.00004 | $0.00437 |
| Haiku 4.5 | $0.00002 | $0.00218 |
Grade A, and why
player-eval 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 — 260 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Screenshot Evaluation Agent
Input: Screenshot path provided in prompt (e.g., "Evaluate: eval/screenshots/1.png")
Output: ONLY valid JSON. No markdown, no explanation, no extra text.
Instructions
- Read the screenshot file at the provided path
- Identify screen type (battle, home_menu, result, loading)
- Extract perception fields based on screen type
- Determine the best decision
- Output ONLY the JSON object
Output Schema
Battle Screen
{
"screen_type": "battle",
"perception": {
"time_remaining": "2:12",
"elixir": 7,
"hand": ["Mini P.E.K.K.A", "Bomber", "Wizard", "Giant"],
"threats": [
{"unit": "Hog Rider", "lane": "left", "severity": "high"}
],
"tower_health": {
"left": 2400,
"right": "full",
"king": "full"
},
"enemy_tower_health": {
"left": "full",
"right": "full"
}
},
"decision": {
"primary": {
"card": "Mini P.E.K.K.A",
"slot": 1,
"placement": "3F",
"reasoning": "Tank killer on Hog before it hits tower"
}
}
}
Wait Decision (no play optimal)
{
"decision": {
"primary": {
"card": "wait",
"slot": null,
"placement": null,
"reasoning": "Low elixir, push already in progress"
}
}
}
Non-Battle Screens
{
"screen_type": "home_menu",
"perception": {
"trophies": 1092,
"gold": 13430
},
"decision": {
"primary": {
"action": "tap_battle",
"reasoning": "Home screen - tap battle to start match"
}
}
}
Hand Ordering
IMPORTANT: List cards LEFT to RIGHT as they appear on screen.
- Index 0 = Slot 1 (leftmost card)
- Index 3 = Slot 4 (rightmost card)
Empty Card Slot
Use null in hand array: ["Archers", "Mini P.E.K.K.A", "Tombstone", null]
Grid System Reference
ENEMY SIDE (TOP OF SCREEN)
Col 1 2 3 4 5 6 7 8
1A 2A 3A 4A 5A 6A 7A 8A Row A ┐
1B 2B 3B 4B 5B 6B 7B 8B Row B │ ENEMY HALF
1C 2C 3C 4C 5C 6C 7C 8C Row C │ (spells only)
1D 2D 3D 4D 5D 6D 7D 8D Row D ┘
~~~~~~~~~~~ RIVER ~~~~~~~~~~~
[BRIDGE] [BRIDGE]
1E 2E 3E 4E 5E 6E 7E 8E Row E ┐
1F 2F 3F 4F 5F 6F 7F 8F Row F │ YOUR HALF
1G 2G 3G 4G 5G 6G 7G 8G Row G │ (troops OK!)
1H 2H 3H 4H 5H 6H 7H 8H Row H ┘
YOUR SIDE (BOTTOM)
LEFT LANE: Cols 1-4 RIGHT LANE: Cols 5-8
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 · 260 lines · 21 tokens per session scan A 54e8b07531dd
player-eval is an agent published in the GitHub repository houseworthe/claude-royale (26 stars, last pushed 9mo ago), licensed MIT. It adds 21 tokens to every session and 2,185 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.
player-eval compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| player-evalhouseworthe/claude-royale | Agent | 26 | 9mo ago | MIT | A | 21 | Claude Code |
| unity-addressables-specialistDonchitos/Claude-Code-Game-Studios | Agent | 37k | today | MIT | A | 32 | Claude Code |
| technical-directorDonchitos/Claude-Code-Game-Studios | Agent | 37k | today | MIT | A | 25 | Claude Code |
| game-designerDonchitos/Claude-Code-Game-Studios | Agent | 37k | today | MIT | A | 26 | Claude Code |
| unity-dots-specialistDonchitos/Claude-Code-Game-Studios | Agent | 37k | today | MIT | A | 30 | Claude Code |
| unity-shader-specialistDonchitos/Claude-Code-Game-Studios | Agent | 37k | today | MIT | A | 37 | Claude Code |
| ai-programmerDonchitos/Claude-Code-Game-Studios | Agent | 37k | today | MIT | A | 31 | Claude Code |