p-task-splitting

Rules for breaking a large software request into smaller tasks with clear inputs, outputs, dependencies, status markers, and acceptance criteria. They limit each task's size and require it to be independently verifiable.

In plain words
What is it for?
Use them to split work by feature or business process, write actionable task checklists, track progress, order dependent work, and define completion standards.
Why use it?
They make large pieces of work easier to estimate, review, track, and deliver without losing sight of what counts as complete.

Cursor rule

Install

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.

agentmods
npx agentmods add rules/xyzbit/ai-coding/p-task-splitting
Clone the repo
git clone --depth 1 https://github.com/xyzbit/AI-Coding
Per session 8 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 467 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00008 $0.00467
Opus 5 $0.00004 $0.00234
Sonnet 5 $0.00002 $0.00093
Haiku 4.5 $0.00001 $0.00047

Measured 2d ago against content hash 145bdbaa7560, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

p-task-splitting 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.

cursor/rules/plan/p-task-splitting.mdc · 68 lines

What it actually says

任务拆分规则 (Task Splitting Guidelines)

规则目的

本规则旨在指导如何科学、合理地将大型需求拆分为可管理和执行的任务单元。

任务拆分流程

1. 任务分析与拆分

  • 拆分维度 按照当前需求选择合适的拆分方式,参考下面两种:
    1. 功能模块维度
       - 核心流程功能点
       - 辅助功能点
       - 扩展功能点
    
    2. 业务流程维度
       - 上游数据处理
       - 核心业务逻辑
       - 下游数据输出
    

2. 任务描述规范

  • 任务格式
    [ ] 任务标题
        - 描述:具体的任务描述
        - 输入:任务的输入项
        - 输出:预期的输出结果
        - 依赖:其他任务的依赖关系
    
  • 示例
    [ ] 用户登录模块开发
        - 描述:实现用户名密码登录功能
        - 输入:用户名、密码
        - 输出:登录态token
        - 依赖:用户服务、认证服务
    

3. 任务确认流程

  • 确认步骤
    1. 任务评审
       - 与用户确认功能细节
    
    2. 任务状态更新
       - [ ] -> [x] 表示任务完成
    

4. 任务验收标准

  1. 确认功能和质量是否过关
  2. 同用户进行任务是否完成的确认

注意事项

  1. 任务粒度控制
    • 单个任务工作量不超过2人日
    • 可独立验证和交付
    • 有明确的完成标准
  2. 进度追踪
    • 定期更新任务状态
    • 按优先级调整任务顺序
Changes

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.

  1. 2d ago First seen · 68 lines · 8 tokens per session scan A 145bdbaa7560

Subscribe to this mod's changes

p-task-splitting is a cursor rule published in the GitHub repository xyzbit/AI-Coding (21 stars, last pushed 10mo ago), licensed Apache-2.0. It adds 8 tokens to every session and 467 once invoked, about $0.0000 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.