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/context)<a href="https://agentmods.dev/commands/xiaobei930/cc-best/context"><img src="https://agentmods.dev/badge/commands/xiaobei930/cc-best/context/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/context"><img src="https://agentmods.dev/badge/commands/xiaobei930/cc-best/context.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 | $0.00028 | $0.00575 |
| Opus 5.5 | $0.00011 | $0.00230 |
| Sonnet 5.5 | $0.00006 | $0.00115 |
| Haiku 4.5 | $0.00003 | $0.00057 |
Grade A, and why
context 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.
What it actually says
/context - 上下文管理
管理 AI 对话上下文，确保信息连续性。
上下文层级
1. 项目上下文（固定）
始终需要了解的信息:
- 项目目标和核心功能
- 技术栈选型
- 关键约束条件
2. 阶段上下文（阶段内固定）
当前阶段需要的信息:
- 当前 Phase 和 Step
- 阶段目标和验收标准
- 相关的设计文档
3. 任务上下文（任务内）
当前任务需要的信息:
- 具体任务描述
- 相关代码文件
- 依赖和接口
新会话启动流程
1. 读取 memory-bank/progress.md
→ 了解当前状态、已完成工作和下一步任务
2. 读取当前任务相关文件（按需）
→ 代码文件、设计文档
3. 确认任务并继续
→ 更新 TodoWrite
上下文文件清单
必读（每次会话）
| 文件 | 内容 | 优先级 |
|---|---|---|
memory-bank/progress.md |
状态和进度 | P0 |
CLAUDE.md |
项目说明 | P1 |
按需读取
| 文件 | 何时读取 |
|---|---|
memory-bank/architecture.md |
涉及架构设计时 |
memory-bank/tech-stack.md |
技术决策时 |
上下文压缩策略
长会话时
- 定期同步状态到 progress.md
- 完成的任务只保留摘要
- 相关代码只保留接口定义
会话切换时
- 保存当前状态到 progress.md
- 记录未完成任务
- 记录关键决策
命令
/cc-best:context load- 加载项目上下文/cc-best:context save- 保存当前状态/cc-best:context show- 显示当前上下文范围
记住: 上下文是 AI 协作的核心资产，花时间维护上下文就是在为未来的效率投资。
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 · 87 lines · 28 tokens per session scan A fa03c6fb7eb0
context is a command published in the GitHub repository xiaobei930/cc-best (48 stars, last pushed 4mo ago), licensed MIT. It adds 28 tokens to every session and 575 once invoked, about $0.0001 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.
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