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/xiaobei930/cc-bestWrote 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/xiaobei930/cc-best/pair)<a href="https://agentmods.dev/commands/xiaobei930/cc-best/pair"><img src="https://agentmods.dev/badge/commands/xiaobei930/cc-best/pair/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/xiaobei930/cc-best/pair"><img src="https://agentmods.dev/badge/commands/xiaobei930/cc-best/pair.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 | $0.00010 | $0.01826 |
| Opus 5.5 | $0.00004 | $0.00730 |
| Sonnet 5.5 | $0.00002 | $0.00365 |
| Haiku 4.5 | $0.00001 | $0.00183 |
Grade A, and why
pair 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 1mo 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 — 260 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/pair - 结对编程模式
核心理念: 人机协作，每个关键节点确认后再继续。
与 /cc-best:iterate 的区别
| 维度 | /cc-best:pair |
/cc-best:iterate |
|---|---|---|
| 决策方式 | 询问用户确认 | 自主推断 |
| 用户参与 | 持续参与 | 仅在阻塞时 |
| 适用场景 | 学习、讨论、敏感操作 | 明确任务的批量执行 |
| 风险控制 | 高（每步确认） | 中（事后检查） |
适用场景
推荐使用 /cc-best:pair
- 🎓 学习新技术 - 需要理解每个步骤
- 💬 设计讨论 - 架构决策需要权衡
- ⚠️ 敏感操作 - 数据库迁移、生产部署
- 🔍 代码审查 - 需要解释和讨论
- 🐛 复杂调试 - 需要人工判断方向
- 📝 需求澄清 - 边界不清晰的任务
推荐使用 /cc-best:iterate
- ✅ 任务清单明确
- ✅ 完成标准清晰
- ✅ 风险可控
- ✅ 不需要频繁决策
工作流程
┌─────────────────────────────────────────────────────────────────┐
│ 结对编程工作流 │
├─────────────────────────────────────────────────────────────────┤
│ │
│ 1. 理解任务 │
│ └─ 读取需求 → 向用户确认理解是否正确 │
│ │
│ 2. 方案设计 │
│ └─ 提出方案 → 询问用户选择 → 确认后继续 │
│ │
│ 3. 逐步实现 │
│ └─ 每个关键步骤 → 展示计划 → 确认后执行 │
│ │
│ 4. 验证结果 │
│ └─ 展示结果 → 询问是否满意 → 调整或继续 │
│ │
│ 5. 总结提交 │
│ └─ 总结变更 → 确认提交信息 → 执行提交 │
│ │
└─────────────────────────────────────────────────────────────────┘
确认节点
必须确认的节点
| 节点 | 确认内容 | 示例问题 |
|---|---|---|
| 需求理解 | 理解是否正确 | "我理解你需要...，对吗？" |
| 方案选择 | 多个方案时 | "方案 A/B/C，你倾向哪个？" |
| 破坏性操作 | 删除、重置等 | "即将删除 X，确认吗？" |
| 外部调用 | API、数据库 | "即将调用生产 API，确认吗？" |
| 提交代码 | commit 内容 | "提交信息：...，确认吗？" |
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.
- 1mo ago First seen · 260 lines · 10 tokens per session scan A 1ba4b3d56f9e
pair is a command published in the GitHub repository xiaobei930/cc-best (48 stars, last pushed 4mo ago), licensed MIT. It adds 10 tokens to every session and 1,826 once invoked, about $0.0000 per session on Opus 5.5. 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
park
Park current session for later resume (append to Markdown file).
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Audit quality of agents, skills, and commands in a Claude Code project.
audit-whitepapers
Audit version freshness, FR/EN parity, and metadata quality of all whitepapers and recap cards.
audit-repo-docs
Audit repository documentation against 85+ best practices from claude-code-ultimate-guide.
boldguy-linkedin-answer
Draft a LinkedIn comment on a post, referencing the guide's relevant section, in Flow style with AI markers removed.
methodology-advisor
Analyzes your codebase and asks 3 targeted questions to recommend the right AI-assisted development methodology stack.