FanaticsKang/claude_config
my claude code config
ARCHETYPE
Pragmatist
A balanced, no-drama setup: some rules, some tools, nothing extreme.
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# review before running: this installs third-party code $ npx degit FanaticsKang/claude_config/agents ./rig-claude_config/agents $ npx degit FanaticsKang/claude_config/commands ./rig-claude_config/commands $ npx degit FanaticsKang/claude_config/skills ./rig-claude_config/skills
MCP servers are added to Claude Code at local scope; env vars are shown as YOUR_… placeholders — we never store values. Files are fetched with degit into a separate folder so you can review before merging.
$ npx degit FanaticsKang/claude_config/skills/ask-me .claude/skills/ask-me $ npx degit FanaticsKang/claude_config/skills/json_analysis .claude/skills/json_analysis $ npx degit FanaticsKang/claude_config/skills/update-claude-md .claude/skills/update-claude-md
$ curl -fsSL --create-dirs -o .claude/agents/algorithm.md https://raw.githubusercontent.com/FanaticsKang/claude_config/master/agents/algorithm.md $ curl -fsSL --create-dirs -o .claude/agents/architect.md https://raw.githubusercontent.com/FanaticsKang/claude_config/master/agents/architect.md
This rig commits no guardrails. Here is the community baseline instead — the deny/ask rules most often found across all 7,204 rigs:
{
"permissions": {
"deny": [
"Read(./.env)",
"Read(**/.env)",
"Read(~/.ssh/**)",
"Bash(rm -rf *)",
"Read(**/*.pem)",
"Bash(rm -rf /)",
"Bash(git push --force:*)",
"Bash(sudo *)",
"Read(.env)",
"Bash(rm -rf /*)",
"Read(./.env.*)",
"Read(~/.aws/**)",
"Bash(git push --force*)",
"Bash(rm -rf:*)",
"Read(**/*.key)",
"Read(**/.env.*)",
"Bash(sudo:*)",
"Bash(git reset --hard*)",
"Bash(git reset --hard:*)",
"Read(.env.*)"
],
"ask": [
"Bash(git push:*)",
"Bash(git push *)",
"Bash(git commit:*)",
"Bash(rm *)",
"Bash(rm:*)",
"Bash(git rebase *)",
"Bash(wget *)",
"Bash(npm publish:*)",
"Bash(git commit *)",
"Bash(gh pr merge *)"
]
}
} Skills (3)
Subagents (2)
| autoDrive-algorithm-specialist model: opus | specialized AI agent focused on the research, development, and application of autonomous driving algorithms. Core expertise covers algorithm design, simulation, optimization, and deployment support fo |
| autoDrive-architect-specialist model: opus | 作为自动驾驶领域的架构设计师,负责系统级的技术整合与数据流治理。主要使命是确保感知、决策、控制等模块之间的数据接口无缝衔接,同时深度介入模块内部实现逻辑的一致性验证,最终输出高可靠性、高可扩展性的系统架构方案。 |
Slash commands (2)
/simplify_your_code/summary_and_commit
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