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.
npx agentmods add rules/wangqiqi/cursor-ai-rules/platform_adapter_pathsgit clone --depth 1 https://github.com/wangqiqi/cursor-ai-rulesWrote 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/rules/wangqiqi/cursor-ai-rules/platform_adapter_paths)<a href="https://agentmods.dev/rules/wangqiqi/cursor-ai-rules/platform_adapter_paths"><img src="https://agentmods.dev/badge/rules/wangqiqi/cursor-ai-rules/platform_adapter_paths.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00381 |
| Opus 5 | $0.00000 | $0.00191 |
| Sonnet 5 | $0.00000 | $0.00076 |
| Haiku 4.5 | $0.00000 | $0.00038 |
Grade A, and why
platform_adapter_paths scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
📁 跨平台路径处理 (Path Handling)
由 platform_adapter 引用，处理路径相关的跨平台逻辑
路径规范化 (Path Normalization)
class PathNormalizer {
private platform: string;
normalize(path: string): string {
const normalized = path.replace(/[/\\]+/g, this.getSeparator());
return this.handleSpecialPaths(normalized);
}
private getSeparator(): string {
return this.platform === 'windows' ? '\\' : '/';
}
private handleSpecialPaths(path: string): string {
const replacements = {
'~': this.getHomeDirectory(),
'$HOME': this.getHomeDirectory(),
'%USERPROFILE%': this.getHomeDirectory(),
'/c/': 'C:\\', // WSL路径转换
};
for (const [pattern, replacement] of Object.entries(replacements)) {
if (path.includes(pattern)) path = path.replace(pattern, replacement);
}
return path;
}
private getHomeDirectory(): string {
return process.env.HOME || process.env.USERPROFILE || '.';
}
}
路径操作 (Path Operations)
| 操作 | Linux | Windows |
|---|---|---|
| 拼接 | path1/path2 | path1\path2 |
| 解析 | realpath | Resolve-Path |
| 相对 | realpath --relative-to | 自定义逻辑 |
实现时使用 path.join()、path.resolve()、path.relative() 或平台特定命令。
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.
- 4d ago First seen · 55 lines · 0 tokens per session scan A 333daac0ca82
platform_adapter_paths is a cursor rule published in the GitHub repository wangqiqi/cursor-ai-rules (15 stars, last pushed 3mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 381 tokens. 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.
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