MCP Server Builder
anthropics/skills
Guides the design and implementation of Model Context Protocol servers in TypeScript or Python, from tool naming and error messages to evaluation.
Play Command & Conquer Red Alert RTS — build bases, train armies, and defeat AI opponents using 48 MCP tools.
Install Openra Rl
$ npx skills add yxc20089/OpenRA-RL --skill openra-rl -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install yxc20089/OpenRA-RL openra-rl --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/yxc20089/OpenRA-RL.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skill .claude/skills/openra-rl && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "openra-rl" agent skill from https://github.com/yxc20089/OpenRA-RL/tree/main/skill into .claude/skills/openra-rl/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "openra-rl", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/yxc20089/OpenRA-RL/tree/main/skillType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add yxc20089/OpenRA-RL --skill openra-rl -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install yxc20089/OpenRA-RL openra-rl --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/yxc20089/OpenRA-RL.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skill .agents/skills/openra-rl && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "openra-rl" agent skill from https://github.com/yxc20089/OpenRA-RL/tree/main/skill into .agents/skills/openra-rl/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "openra-rl", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add yxc20089/OpenRA-RL --skill openra-rl -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install yxc20089/OpenRA-RL openra-rl --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/yxc20089/OpenRA-RL.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skill .cursor/skills/openra-rl && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "openra-rl" agent skill from https://github.com/yxc20089/OpenRA-RL/tree/main/skill into .cursor/skills/openra-rl/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "openra-rl", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/yxc20089/OpenRA-RL.git --path skill--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add yxc20089/OpenRA-RL --skill openra-rl -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install yxc20089/OpenRA-RL openra-rl --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/yxc20089/OpenRA-RL.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skill .gemini/skills/openra-rl && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "openra-rl" agent skill from https://github.com/yxc20089/OpenRA-RL/tree/main/skill into .gemini/skills/openra-rl/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "openra-rl", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install yxc20089/OpenRA-RL openra-rlInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add yxc20089/OpenRA-RL --skill openra-rl -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/yxc20089/OpenRA-RL.git skills-src && mkdir -p .github/skills && cp -r skills-src/skill .github/skills/openra-rl && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "openra-rl" agent skill from https://github.com/yxc20089/OpenRA-RL/tree/main/skill into .github/skills/openra-rl/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "openra-rl", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add yxc20089/OpenRA-RL --skill openra-rl -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install yxc20089/OpenRA-RL openra-rl --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/yxc20089/OpenRA-RL.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skill .opencode/skills/openra-rl && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "openra-rl" agent skill from https://github.com/yxc20089/OpenRA-RL/tree/main/skill into .opencode/skills/openra-rl/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "openra-rl", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
openra-rl- GitHub stars
- 158
- Token cost
- ~2.7k tokens
- SKILL.md length
- 1,008 words
- Files
- 1
- Skills in repo
- 1
- Repo updated
- First seen
- Licence
- GPL-3.0
At a glance
Play Command & Conquer Red Alert RTS — build bases, train armies, and defeat AI opponents using 48 MCP tools.
- Works in 10 steps: Install → Start the game server → Configure MCP → …
- Tasks that involve MCP servers
- SKILL.md covers Quick Start, How the Game Works, MCP Tools Reference and How to Play (Strategy Guide), plus 4 more sections
- Calls pip
What it does
Openra Rl is an agent skill from yxc20089/OpenRA-RL. Play Command & Conquer Red Alert RTS — build bases, train armies, and defeat AI opponents using 48 MCP tools.
Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Agent Workflows, covering MCP servers. The repository describes itself as: Open Framework for AI Agents to play Red Alert through Reinforcement Learning. The licence is GPL-3.0.
When your agent uses it
- Tasks that involve MCP servers
Example prompts
- “/openra-rl”
Requirements
- Python 3
- Docker
Workflow steps
10 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 5dadd44. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
pip
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
pypi.orghuggingface.codiscord.gg
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Openra Rl loads about 2.7k tokens when it runs. Until then it costs about 30 tokens; SKILL.md has 1,008 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from yxc20089/OpenRA-RL at commit 5dadd44, republished under its GPL-3.0 licence (© yxc20089). 1,008 words, ~2,737 tokens.
Download SKILL.mdSave it as
.claude/skills/openra-rl/SKILL.md (or your agent's skills folder).- name
- openra-rl
- description
- Play Command & Conquer Red Alert RTS — build bases, train armies, and defeat AI opponents using 48 MCP tools.
- version
- 1.1.0
OpenRA-RL: Play Command & Conquer Red Alert
You are an AI agent playing Command & Conquer: Red Alert, a classic real-time strategy (RTS) game. You control one faction (Allied or Soviet) and must build a base, gather resources, train an army, and destroy the enemy.
The game runs in a Docker container. You interact through MCP tools that let you observe the battlefield, issue orders, and advance game time.
Quick Start
1. Install
pip install openra-rl2. Start the game server
openra-rl server startThis pulls the Docker image and starts the game server on port 8000. Verify with openra-rl server status.
3. Configure MCP
Add to your OpenClaw config (~/.openclaw/openclaw.json):
{
"mcpServers": {
"openra-rl": {
"command": "openra-rl",
"args": ["mcp-server"]
}
}
}4. Play
Tell your agent: "Start a game of Red Alert and try to win."
The agent will use the MCP tools listed below to observe and command.
How the Game Works
- Real-time: The game runs continuously at ~25 ticks/second. Call
advance(ticks)to let time pass. - Fog of war: You can only see areas near your units/buildings. Scout to find the enemy.
- Resources: Harvest ore to earn credits. Credits buy buildings and units.
- Power: Buildings need power. Build Power Plants (
powr) to stay powered. Low power slows production. - Tech tree: Advanced buildings require prerequisites (e.g., War Factory needs Ore Refinery).
MCP Tools Reference
Observation (read the battlefield)
| Tool | Purpose |
|---|---|
get_game_state | Full snapshot: economy, units, buildings, enemies, production, military stats |
get_economy | Cash, ore, power balance, harvester count |
get_units | Your units with position, health, type, stance, speed, attack range |
get_buildings | Your buildings with production queues, power, can_produce list |
get_enemies | Visible enemy units and buildings (fog-of-war limited) |
get_production | Current build queue + what you can build right now |
get_map_info | Map name, dimensions |
get_exploration_status | % explored, quadrant breakdown, whether enemy base found |
Knowledge (learn the game)
| Tool | Purpose |
|---|---|
lookup_unit(unit_type) | Stats for a unit (e.g., lookup_unit("e1") → Rifle Infantry) |
lookup_building(building_type) | Stats for a building (e.g., lookup_building("weap") → War Factory) |
lookup_tech_tree(faction) | Full build order for "allied" or "soviet" |
lookup_faction(faction) | All units and buildings for a faction |
get_faction_briefing() | Comprehensive stats dump for YOUR faction |
get_map_analysis() | Resource patches, water, terrain, strategic notes |
batch_lookup(queries) | Multiple lookups in one call |
Game Control
| Tool | Purpose |
|---|---|
advance(ticks) | Critical — advances the game by N ticks. Nothing happens without this. Use 25 ticks ≈ 1 second, 250 ticks ≈ 10 seconds. |
Movement & Combat
| Tool | Purpose |
|---|---|
move_units(unit_ids, target_x, target_y) | Move units to a position |
attack_move(unit_ids, target_x, target_y) | Move and engage enemies along the way |
attack_target(unit_ids, target_actor_id) | Focus-fire a specific enemy |
stop_units(unit_ids) | Halt movement and attacks |
guard_target(unit_ids, target_actor_id) | Guard a unit or building |
set_stance(unit_ids, stance) | Set to "holdfire", "returnfire", "defend", or "attackanything" |
harvest(unit_id, cell_x, cell_y) | Send harvester to ore field |
Production
| Tool | Purpose |
|---|---|
build_unit(unit_type, count) | Train units (e.g., build_unit("e1", 5) → 5 Rifle Infantry) |
build_structure(building_type) | Start constructing a building (needs manual placement) |
build_and_place(building_type, cell_x, cell_y) | Build + auto-place when done (preferred) |
place_building(building_type, cell_x, cell_y) | Place a completed building |
cancel_production(item_type) | Cancel queued production |
get_valid_placements(building_type) | Get valid locations to place a building |
Building Management
| Tool | Purpose |
|---|---|
deploy_unit(unit_id) | Deploy MCV into Construction Yard |
sell_building(building_id) | Sell for partial refund |
repair_building(building_id) | Toggle auto-repair |
set_rally_point(building_id, cell_x, cell_y) | New units go here |
power_down(building_id) | Toggle power to save electricity |
set_primary(building_id) | Set as primary production building |
Unit Groups
| Tool | Purpose |
|---|---|
assign_group(group_name, unit_ids) | Create a named group |
add_to_group(group_name, unit_ids) | Add units to existing group |
get_groups() | List all groups |
command_group(group_name, command_type, ...) | Command entire group |
Compound Actions
| Tool | Purpose |
|---|---|
batch(actions) | Execute multiple actions in ONE tick (no time advance) |
plan(steps) | Execute steps sequentially with state refresh between each |
Utility
| Tool | Purpose |
|---|---|
surrender() | Give up the current game |
get_replay_path() | Path to the replay file |
get_terrain_at(cell_x, cell_y) | Terrain type at a cell |
Planning Phase (optional)
| Tool | Purpose |
|---|---|
start_planning_phase() | Begin pre-game strategy planning |
get_opponent_intel() | AI opponent profile and counters |
end_planning_phase(strategy) | Commit strategy and start playing |
get_planning_status() | Check planning state |
Show full SKILL.md (405 more words)Show less
How to Play (Strategy Guide)
Step 1: Deploy your MCV
At game start you have a Mobile Construction Vehicle (MCV). Deploy it to create your Construction Yard:
1. Call get_units() to find your MCV (type "mcv")
2. Call deploy_unit(mcv_actor_id)
3. Call advance(50) to let it deployStep 2: Build your base
Follow this build order:
| Order | Building | Type Code | Cost | Why |
|---|---|---|---|---|
| 1 | Power Plant | powr | $300 | Powers everything |
| 2 | Barracks | tent (Allied) or barr (Soviet) | $300 | Infantry production |
| 3 | Ore Refinery | proc | $2000 | Income + free harvester |
| 4 | War Factory | weap | $2000 | Vehicle production (requires Refinery) |
| 5 | More Power | powr | $300 | Keep power positive |
Use build_and_place() — it auto-places when construction finishes:
1. Call get_valid_placements("powr") to find a good spot
2. Call build_and_place("powr", cell_x, cell_y)
3. Call advance(250) to let it build (~10 seconds)
4. Check get_production() to confirm completion
5. Repeat for next buildingImportant: Your faction may be Allied OR Soviet. Check get_game_state() → faction field. Barracks type depends on faction.
Step 3: Train your army
1. Call build_unit("e1", 5) for 5 Rifle Infantry ($100 each)
2. Call advance(100) to let them train
3. Once War Factory is ready: build_unit("3tnk", 3) for Medium Tanks ($800 each)
4. Set rally point near base exit: set_rally_point(barracks_id, x, y)Key units by faction:
| Unit | Code | Cost | Role |
|---|---|---|---|
| Rifle Infantry | e1 | $100 | Cheap, fast |
| Rocket Soldier | e3 | $300 | Anti-armor |
| Medium Tank | 3tnk | $800 | Main battle tank |
| Heavy Tank | 4tnk | $950 | Soviet heavy armor |
| Light Tank | 1tnk | $700 | Fast flanker |
| Artillery | arty | $600 | Long range |
| V2 Launcher | v2rl | $700 | Soviet long range |
Step 4: Scout the map
Send a cheap unit to explore:
1. Train one Rifle Infantry
2. Call attack_move([unit_id], far_x, far_y) toward unexplored areas
3. Call advance(500) to let it travel
4. Call get_enemies() to see what you've foundStep 5: Attack the enemy
Once you have 8-10 combat units:
1. Call get_enemies() to find enemy buildings
2. Call attack_move(all_unit_ids, enemy_base_x, enemy_base_y)
3. Call advance(100), check get_game_state() for battle progress
4. If enemies visible: attack_target(unit_ids, enemy_id) to focus fire
5. Keep producing reinforcements while attackingStep 6: Macro (ongoing economy)
Throughout the game:
- Keep power positive (build Power Plants when needed)
- Keep producing units — never let production idle
- Build additional Ore Refineries for more income
- Replace lost harvesters
Game Loop Pattern
A good agent loop looks like this:
1. get_game_state() → read the situation
2. Decide what to do based on:
- Economy: enough cash? Power positive?
- Production: anything building? Queue empty?
- Military: under attack? Ready to attack?
- Exploration: enemy found yet?
3. Issue orders (build, move, attack)
4. advance(50-250) → let time pass
5. Repeat until game is won or lostCheck get_game_state() → done field. When true, result will be "win" or "loss".
Tips
- Always call
advance()after issuing orders. Orders don't execute until game time passes. - Use
batch()to issue multiple orders in one tick (e.g., build + move + set rally). - Check
available_productionbefore building — it lists what you CAN build right now. - Don't let production idle — keep queuing units. Idle production wastes time.
- Build near your Construction Yard — buildings must be placed adjacent to existing structures.
- Power matters — if power goes negative, production slows to a crawl.
- Use
attack_moveinstead ofmovewhen heading toward enemies — units will engage threats. - A completed building blocks the queue until placed. Always use
build_and_place()to avoid this.
Troubleshooting
| Problem | Solution |
|---|---|
| Server not running | openra-rl server start (needs Docker) |
| Can't build anything | Deploy MCV first with deploy_unit() |
| Building won't place | Use get_valid_placements() for valid spots |
| No money | Build Ore Refinery (proc) for harvesters |
| Production slow | Check power with get_economy() — build Power Plants |
| Can't find enemy | Scout with attack_move to unexplored quadrants |
Links
- GitHub: https://github.com/yxc20089/OpenRA-RL
- PyPI: https://pypi.org/project/openra-rl/
- Leaderboard: https://huggingface.co/spaces/yxc20089/OpenRA-Bench
- Discord: https://discord.gg/openra-rl
© yxc20089, GPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skill of yxc20089/OpenRA-RL.
Open the folder on GitHubat commit 5dadd44
Compare with similar skills
Openra Rl next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Openra Rl this skillyxc20089/OpenRA-RL | 158 | — | ~2.7k | Automated safety check: Pass | GPL-3.0 | |
| MCP Server Builderanthropics/skills | 180k | 63 repos | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| MCP Server BuildershareAI-lab/learn-claude-code | 78k | 4 repos | ~1.2k | Automated safety check: Pass | MIT | |
| MCP Integration for Pluginsanthropics/claude-plugins-official | 38k | 11 repos | ~3.1k | Automated safety check: Pass | Apache-2.0 | |
| Microsoft Skill CreatorMicrosoftDocs/mcp | 1.9k | 3 repos | ~2.1k | Automated safety check: Pass | CC-BY-4.0 | |
| Crush Configurationcharmbracelet/crush | 29k | — | ~3.7k | Automated safety check: Pass | Custom licence |
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Categories
Questions about Openra Rl
What does Openra Rl do?
Play Command & Conquer Red Alert RTS — build bases, train armies, and defeat AI opponents using 48 MCP tools. Openra Rl is an agent skill from yxc20089/OpenRA-RL. Play Command & Conquer Red Alert RTS — build bases, train armies, and defeat AI opponents using 48 MCP tools.
When should I use Openra Rl?
Openra Rl fits situations like: tasks that involve MCP servers.
How do I install Openra Rl in Claude Code?
Run `npx skills add yxc20089/OpenRA-RL --skill openra-rl -a claude-code`. Or copy the skill folder (skill in yxc20089/OpenRA-RL) into .claude/skills/openra-rl in your project. Claude Code loads it when a task matches its description.
How do I install Openra Rl in Codex?
Run `npx skills add yxc20089/OpenRA-RL --skill openra-rl -a codex`. Or copy the skill folder (skill in yxc20089/OpenRA-RL) into .agents/skills/openra-rl in your project. Codex loads it when a task matches its description.
Can I use Openra Rl in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add yxc20089/OpenRA-RL --skill openra-rl -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/openra-rl, .gemini/skills/openra-rl, .github/skills/openra-rl and .opencode/skills/openra-rl in your project.
What does Openra Rl need to run?
Going by SKILL.md and its folder, Openra Rl needs the command-line tools its instructions call (pip). Our summary lists: Python 3; Docker.
Does Openra Rl access the network?
SKILL.md names 3 domains. As links in the text: pypi.org, huggingface.co and discord.gg. This is read from the text; nothing was executed.
Is Openra Rl safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Openra Rl use?
Openra Rl is published under the GPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Openra Rl use?
About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Openra Rl?
Skills that share tags, products or a category with Openra Rl: MCP Server Builder (anthropics/skills, 180k stars), MCP Server Builder (shareAI-lab/learn-claude-code, 78k stars), MCP Integration for Plugins (anthropics/claude-plugins-official, 38k stars) and Microsoft Skill Creator (MicrosoftDocs/mcp, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Openra Rl?
yxc20089 (a GitHub user) maintains it in yxc20089/OpenRA-RL, which has 158 GitHub stars. The repository was last updated on May 16, 2026.
Source: yxc20089/OpenRA-RL on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.