Borrowing it
Nothing to install: this file belongs to clxzl/claude-code-best-practice-cn. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/clxzl/claude-code-best-practice-cn/main/.claude/commands/workflows/best-practice/workflow-claude-commands.mdgit clone --depth 1 https://github.com/clxzl/claude-code-best-practice-cnWrote 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/clxzl/claude-code-best-practice-cn/workflow-claude-commands)<a href="https://agentmods.dev/commands/clxzl/claude-code-best-practice-cn/workflow-claude-commands"><img src="https://agentmods.dev/badge/commands/clxzl/claude-code-best-practice-cn/workflow-claude-commands/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/clxzl/claude-code-best-practice-cn/workflow-claude-commands"><img src="https://agentmods.dev/badge/commands/clxzl/claude-code-best-practice-cn/workflow-claude-commands.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 | $0.00018 | $0.01956 |
| Opus 5 | $0.00009 | $0.00978 |
| Sonnet 5 | $0.00004 | $0.00391 |
| Haiku 4.5 | $0.00002 | $0.00196 |
Grade A, and why
workflow-claude-commands 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
工作流变更日志 — Commands 报告
你是 claude-code-best-practice 项目的协调器。你的工作是启动研究 Agent、等待其结果，并提交一份关于 Commands 参考报告（best-practice/claude-commands.md）中漂移的报告。
此工作流恰好检查两种类型的漂移：
- Frontmatter 字段 — 官方文档中新增或移除的任何字段
- 官方命令 — 新增或移除的任何内置 slash 命令
检查版本数： $ARGUMENTS（如果为空或非数字则默认为 10）
这是一个先读后报告的工作流。启动 Agent、合并发现并生成报告。只有在用户批准后才采取行动。
阶段 1：启动研究 Agent
生成 workflow-claude-commands-agent，使用以下提示：
研究 claude-code-best-practice 项目的 commands 报告漂移。检查最近 $ARGUMENTS 个版本（默认：10）。
获取这 2 个外部来源：
- Slash 命令参考：https://code.claude.com/docs/en/slash-commands
- 变更日志：https://github.com/anthropics/claude-code/blob/main/CHANGELOG.md
然后读取本地报告（
best-practice/claude-commands.md）。恰好检查两件事：
- Frontmatter 字段：将官方文档支持的命令 frontmatter 字段与报告的 Frontmatter 字段表进行比较。标记任何新增或移除的字段。
- 官方命令：将官方文档的内置 slash 命令列表与报告的官方命令表进行比较。标记任何新增或移除的命令。同时检查任何命令的标签或描述是否已更改。
阶段 2：读取之前的变更日志条目
在 Agent 运行期间，读取 changelog/best-practice/claude-commands/changelog.md 获取最近 25 个条目。解析优先级操作以识别：
- 重复项 — 之前出现过且仍未解决的问题
- 新项 — 首次出现的问题
- 已解决项 — 之前标记但现已修复的问题
阶段 3：生成报告
等待 Agent 完成。 生成包含以下部分的报告：
- Frontmatter 字段变更 — 官方文档与我们的报告中新增或移除的字段
- 官方命令变更 — 与我们表中相比新增或移除的内置 slash 命令
最后以带优先级的操作项摘要表结束。每个项必须包含一个 Status 列，显示 NEW、RECURRING (first seen: <date>) 或 RESOLVED：
优先行动：
| 类型 | 操作 | 状态
1 | 新增字段 | 将 添加到 frontmatter 表格 | 新增 2 | 已移除字段 | 从表格中移除 | 重复出现（首次出现：） 3 | 新增命令 | 将 添加到官方表格 | 新增 4 | 已移除命令 | 从表格中移除 | 新增 5 | 标签已变更 | 将 标签从 X 更新为 Y | 新增
同时包含一个上次运行以来已解决项部分，列出之前运行中已不再是问题的项。
阶段 3.5：追加摘要到变更日志
此阶段是强制性的 — 在向用户展示报告前必须始终执行。
读取现有的 changelog/best-practice/claude-commands/changelog.md 文件，然后在末尾追加（不要覆盖）一个新条目。条目格式必须如下：
---
## [<YYYY-MM-DD HH:MM AM/PM PKT>] Claude Code v<VERSION>
| # | 优先级 | 类型 | 操作描述 | 状态 |
|---|----------|------|--------|--------|
| 1 | HIGH/MED/LOW | <type> | <action description> | <status> |
| ... | ... | ... | ... | ... |
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.
- 9d ago First seen · 139 lines · 18 tokens per session scan A 0f9f0f52ab4e
workflow-claude-commands is a command published in the GitHub repository clxzl/claude-code-best-practice-cn (127 stars, last pushed 4mo ago), licensed MIT. It adds 18 tokens to every session and 1,956 once invoked, about $0.0001 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 2026-08-30.
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.
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.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.