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/luohaothu/everything-codex/plangit clone --depth 1 https://github.com/Luohaothu/everything-codexWhat 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 | $0.00026 | $0.00863 |
| Opus 5 | $0.00013 | $0.00432 |
| Sonnet 5 | $0.00005 | $0.00173 |
| Haiku 4.5 | $0.00003 | $0.00086 |
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 2d 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 — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
计划命令
此命令调用 planner 代理，在编写任何代码之前创建一个全面的实施计划。
此命令的作用
- 重新阐述需求 - 明确需要构建什么
- 识别风险 - 揭示潜在问题和阻碍
- 创建分步计划 - 将实施分解为多个阶段
- 等待确认 - 必须获得用户批准才能继续
何时使用
在以下情况下使用 /plan：
- 开始新功能时
- 进行重大架构变更时
- 处理复杂重构时
- 多个文件/组件将受到影响时
- 需求不明确或存在歧义时
工作原理
planner 代理将：
- 分析请求 并用清晰的术语重新阐述需求
- 分解为多个阶段，每个阶段包含具体、可操作的步骤
- 识别组件之间的依赖关系
- 评估风险和潜在阻碍
- 估算复杂度（高/中/低）
- 展示计划并等待您明确的确认
使用示例
User: /plan I need to add real-time notifications when markets resolve
Agent (planner):
# Implementation Plan: Real-Time Market Resolution Notifications
## Requirements Restatement
- Send notifications to users when markets they're watching resolve
- Support multiple notification channels (in-app, email, webhook)
- Ensure notifications are delivered reliably
- Include market outcome and user's position result
## Implementation Phases
### Phase 1: Database Schema
- Add notifications table with columns: id, user_id, market_id, type, status, created_at
- Add user_notification_preferences table for channel preferences
- Create indexes on user_id and market_id for performance
### Phase 2: Notification Service
- Create notification service in lib/notifications.ts
- Implement notification queue using BullMQ/Redis
- Add retry logic for failed deliveries
- Create notification templates
### Phase 3: Integration Points
- Hook into market resolution logic (when status changes to "resolved")
- Query all users with positions in market
- Enqueue notifications for each user
### Phase 4: Frontend Components
- Create NotificationBell component in header
- Add NotificationList modal
- Implement real-time updates via Supabase subscriptions
- Add notification preferences page
## Dependencies
- Redis (for queue)
- Email service (SendGrid/Resend)
- Supabase real-time subscriptions
## Risks
- HIGH: Email deliverability (SPF/DKIM required)
- MEDIUM: Performance with 1000+ users per market
- MEDIUM: Notification spam if markets resolve frequently
- LOW: Real-time subscription overhead
## Estimated Complexity: MEDIUM
- Backend: 4-6 hours
- Frontend: 3-4 hours
- Testing: 2-3 hours
- Total: 9-13 hours
**WAITING FOR CONFIRMATION**: Proceed with this plan? (yes/no/modify)
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.
- 2d ago First seen · 116 lines · 26 tokens per session scan A 22d03c7937af
plan is a command published in the GitHub repository Luohaothu/everything-codex (24 stars, last pushed 21d ago), licensed MIT. It adds 26 tokens to every session and 863 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.