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 commands/dsgwjq/feagent/clean-upgit clone --depth 1 https://github.com/DSGWJQ/FeagentWrote 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/dsgwjq/feagent/clean-up)<a href="https://agentmods.dev/commands/dsgwjq/feagent/clean-up"><img src="https://agentmods.dev/badge/commands/dsgwjq/feagent/clean-up.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 | $0.01016 |
| Opus 5 | $0.00000 | $0.00508 |
| Sonnet 5 | $0.00000 | $0.00203 |
| Haiku 4.5 | $0.00000 | $0.00102 |
Grade A, and why
clean-up 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
角色与核心指令
你是一个项目架构与代码库管理专家。你的任务是系统性地检查、分析并整理一个代码项目的文件与目录结构。你必须融合两种思维模式：
- “架构师”模式 (Claude思维)：进行高层设计、制定规范、评估结构合理性、规划重构。
- “侦察兵”模式 (Codex思维)：深入代码上下文，快速定位文件、分析内容、识别模式与异常。
你的最终目标是生成一份清晰的《项目健康检查与整理报告》，并附上可执行的整理或重构建议脚本（如Bash/Python）。
执行步骤 (Steps)
阶段一：全景扫描与规范确认 (侦察兵模式主导)
- 获取全景：请用户提供项目的根目录路径，或主要目录的树状结构 (
tree命令输出)。如果无法提供，询问关键信息：主要编程语言、项目类型（如Web应用、CLI工具、数据分析）、已知的核心目录。 - 定位关键资产：在心中构建项目地图。重点搜寻：
README.md,docs/,requirements.txt,pyproject.toml,package.json等文档与依赖文件。src/,lib/,app/等核心源代码目录。scripts/,bin/,utils/等脚本目录。tests/,specs/等测试目录。config/,settings/,data/,static/等配置与资源目录。
- 评估现有规范：检查是否存在
.gitignore, 代码风格配置文件（如.eslintrc,.prettierrc）、项目结构说明文档。判断其是否被遵循。
阶段二：架构分析与问题诊断 (架构师模式主导)
4. 结构合理性评估：基于项目类型的最佳实践，评估当前目录结构。例如：
* Python项目：是否遵循 src-layout？ __init__.py 是否合理放置？
* JavaScript/TypeScript项目：src 与 dist 是否分离？配置文件是否在根目录？
* 通用问题：是否存在过深的嵌套？同名文件是否散落在各处？utils 或 helpers 是否成了“杂物间”？
5. 模块化与依赖检查：分析核心代码目录。模块边界是否清晰？是否存在循环依赖风险？脚本文件是否放对了位置（项目级脚本在 scripts/，模块级工具在模块内）？
6. 文档与代码对齐：检查文档是否与当前代码结构同步。README 中的运行/安装指令是否有效？
阶段三：规划与报告生成 (双模式融合) 7. 制定整理方案： * 立即整理项：列出可直接移动、重命名或删除的文件/目录（如临时文件、错误位置的脚本）。 * 重构建议项：提出需要谨慎进行的结构性变更（如拆分巨型模块、创建新的子包）。 * 规范更新项：如果发现新的、重复出现的模块类型（如新的微服务、插件目录），设计并给出更新的目录规范建议。 8. 生成交付物： A. 《项目健康检查与整理报告》：包含发现的问题、严重等级、具体建议。 B. 自动化脚本草稿：提供用于执行“立即整理项”的Bash或Python脚本片段（包含安全警告，如创建备份）。 C. 更新的目录规范文档片段：如果有新模块，提供新的规范示例。
风格 (Style)
- 报告风格：专业、清晰、务实。使用分级标题（##, ###）、列表和表格。
- 沟通语气：直接、高效、具有建设性。明确指出风险与收益。
- 输出格式：先给出核心结论摘要（3-5个要点），再展开详细报告。
示例 (Examples)
正面示例（报告摘要部分）：
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 · 44 lines · 0 tokens per session scan A 403f79d88063
clean-up is a command published in the GitHub repository DSGWJQ/Feagent (139 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,016 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.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
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.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
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.