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/zhukunpenglinyutong/ai-maxWrote 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/zhukunpenglinyutong/ai-max/plan)<a href="https://agentmods.dev/commands/zhukunpenglinyutong/ai-max/plan"><img src="https://agentmods.dev/badge/commands/zhukunpenglinyutong/ai-max/plan/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/zhukunpenglinyutong/ai-max/plan"><img src="https://agentmods.dev/badge/commands/zhukunpenglinyutong/ai-max/plan.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 | $0.00024 | $0.00942 |
| Opus 5 | $0.00012 | $0.00471 |
| Sonnet 5 | $0.00005 | $0.00188 |
| Haiku 4.5 | $0.00002 | $0.00094 |
Grade A, and why
plan 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 10d 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
Plan 命令
此命令调用 planner 代理,在编写任何代码之前创建全面的实施计划。
此命令的功能
- 重述需求 - 明确需要构建的内容
- 识别风险 - 发现潜在问题和阻碍因素
- 创建步骤计划 - 将实施分解为多个阶段
- 等待确认 - 必须在继续之前获得用户批准
何时使用
在以下情况使用 /aimax:plan:
- 开始新功能开发
- 进行重大架构变更
- 处理复杂的重构工作
- 多个文件/组件将受到影响
- 需求不清楚或有歧义
工作原理
planner 代理将:
- 分析请求并以清晰的术语重述需求
- 分解为阶段,包含具体、可执行的步骤
- 识别组件之间的依赖关系
- 评估风险和潜在阻碍因素
- 估算复杂度(高/中/低)
- 展示计划并等待您的明确确认
使用示例
用户:/aimax:plan 我需要在市场结算时添加实时通知功能
代理(planner):
# 实施计划:实时市场结算通知
## 需求重述
- 当用户关注的市场结算时向其发送通知
- 支持多种通知渠道(应用内、邮件、webhook)
- 确保通知可靠送达
- 包含市场结果和用户持仓结果
## 实施阶段
### 阶段 1:数据库架构
- 添加 notifications 表,包含列:id, user_id, market_id, type, status, created_at
- 添加 user_notification_preferences 表用于渠道偏好设置
- 在 user_id 和 market_id 上创建索引以提高性能
### 阶段 2:通知服务
- 在 lib/notifications.ts 中创建通知服务
- 使用 BullMQ/Redis 实现通知队列
- 添加失败投递的重试逻辑
- 创建通知模板
### 阶段 3:集成点
- 接入市场结算逻辑(当状态变更为 "resolved" 时)
- 查询所有在该市场有持仓的用户
- 为每个用户加入通知队列
### 阶段 4:前端组件
- 在页头创建 NotificationBell 组件
- 添加 NotificationList 弹窗
- 通过 Supabase 订阅实现实时更新
- 添加通知偏好设置页面
## 依赖项
- Redis(用于队列)
- 邮件服务(SendGrid/Resend)
- Supabase 实时订阅
## 风险
- 高:邮件送达率(需要 SPF/DKIM)
- 中:每个市场超过 1000+ 用户时的性能
- 中:如果市场频繁结算可能导致通知泛滥
- 低:实时订阅的开销
## 预估复杂度:中等
- 后端:4-6 小时
- 前端:3-4 小时
- 测试:2-3 小时
- 总计:9-13 小时
**等待确认**:继续执行此计划?(是/否/修改)
重要说明
关键:planner 代理在您明确确认计划(使用 "是"、"继续" 或类似肯定回复)之前不会编写任何代码。
如果您想要更改,请回复:
- "修改:[您的更改]"
- "换个方案:[替代方案]"
- "跳过阶段 2,先做阶段 3"
与其他命令的集成
计划完成后:
- 使用
/aimax:tdd通过测试驱动开发实施 - 如果出现构建错误,使用
/aimax:build-fix - 使用
/aimax:code-review审查已完成的实施
相关代理
此命令调用位于以下位置的 planner 代理:
~/.claude/agents/planner.md
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.
- 10d ago First seen · 114 lines · 24 tokens per session scan A b7fae2a8440a
plan is a command published in the GitHub repository zhukunpenglinyutong/ai-max (335 stars, last pushed 7mo ago), licensed MIT. It adds 24 tokens to every session and 942 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.