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.
git clone --depth 1 https://github.com/an8079/take-skillsWrote 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/commands/an8079/take-skills/takes-import)<a href="https://agentmods.dev/commands/an8079/take-skills/takes-import"><img src="https://agentmods.dev/badge/commands/an8079/take-skills/takes-import/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/commands/an8079/take-skills/takes-import"><img src="https://agentmods.dev/badge/commands/an8079/take-skills/takes-import.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 | $0.00030 | $0.00552 |
| Opus 5 | $0.00015 | $0.00276 |
| Sonnet 5 | $0.00006 | $0.00110 |
| Haiku 4.5 | $0.00003 | $0.00055 |
Grade A, and why
takes-import 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 8d 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
/import - 导入现有项目
导入现有项目到 CLAUDE-STUDIO 管理系统，分析项目结构并建立开发边界。
使用方式
/import [项目路径]
场景说明
本命令用于处理以下生产环境关键场景：
- 用户已有完整项目，只需 CLAUDE-STUDIO 负责部分功能开发
- 需要在现有项目基础上进行增量开发
- 需要分析项目架构但不确定从哪里开始
工作流程
-
扫描项目结构
- 分析目录结构
- 识别技术栈（语言、框架、构建工具）
- 检测包管理器和依赖
-
生成架构报告
- 输出项目结构概览
- 识别关键模块和入口点
- 标记可编辑区域和锁定区域
-
建立开发边界
- 自动创建
.claude/scope.yaml边界文件 - 定义可修改的文件/目录
- 锁定禁止修改的区域
- 自动创建
导入类型
| 类型 | 说明 | 边界设置 |
|---|---|---|
| 全量导入 | 整个项目由 CLAUDE-STUDIO 负责 | 全部可编辑 |
| 部分导入 | 只负责部分模块开发 | 只开放指定目录 |
| 只读分析 | 只分析，不修改任何文件 | 全部锁定 |
导入后
导入完成后，系统会：
- 显示项目架构分析
- 提示可编辑范围
- 建议下一步操作（如
/analyze或/scope）
/analyze # 深入分析项目架构
/scope # 查看/修改开发边界
/code # 开始编码（仅限边界内）
注意事项
- 导入不会修改任何现有文件
- 开发边界可以通过
/scope命令调整 - 首次导入建议先运行
/analyze了解项目
示例
/import # 导入当前目录项目
/import /path/to/project # 导入指定路径项目
/import --type=partial # 部分导入（交互式选择目录）
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.
- 8d ago First seen · 76 lines · 30 tokens per session scan A c5a2d3c24f39
takes-import is a command published in the GitHub repository an8079/take-skills (4 stars, last pushed 5mo ago), licensed MIT. It adds 30 tokens to every session and 552 once invoked, about $0.0002 per session on Opus 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 2026-08-31.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.