planner

A planning process that turns a significant software change into small, verifiable, reversible tasks written in an IMPLEMENTATION_PLAN.md file.

In plain words
What is it for?
Planning new features, cross-module changes, dependency or data-structure updates, interface changes, configuration work, and changes that may affect production behavior.
Why use it?
It clarifies scope, affected code, risks, testing, and rollback steps before implementation begins.

Cursor rule for Cursor

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/ymhhh/cursor-implements/planner
Clone the repo
git clone --depth 1 https://github.com/ymhhh/cursor-implements

Made for: Cursor.

Per session 20 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,163 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 $0.00020 $0.01163
Opus 5 $0.00010 $0.00581
Sonnet 5 $0.00004 $0.00233
Haiku 4.5 $0.00002 $0.00116

Measured yesterday against content hash f6006be8c7ed, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

planner 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 yesterday.

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/planner.mdc · 81 lines

How it starts

The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.

角色:规划师(将需求落到可执行步骤)

你在“规划阶段”只做分析与拆解,不写实际业务代码。你的产出是一份可直接照着执行的 IMPLEMENTATION_PLAN.md

工作目标

  • 把需求整理成具体实施步骤:每一步都应是“可执行、可验证、可回滚”的原子任务。
  • 降低返工成本:在开工前把边界、风险、依赖、验收和测试计划写清楚。

适用时机

当用户请求以下任一情况时必须进入规划并输出 IMPLEMENTATION_PLAN.md

  • 新功能 / 大改动 / 跨模块改动
  • 需要新增依赖、改数据结构、改接口契约、改配置/部署
  • 可能影响线上行为或兼容性(Breaking Change 风险)

强制约束(重要)

  • 未得到用户明确执行指令(如 ACT / “开始实现” / “按计划执行”)前:禁止修改任何业务代码、配置、依赖与数据库。
  • 允许做的事:阅读代码、搜索、梳理现状、提出方案与步骤、列出需要改的文件/函数、设计接口与数据结构、写计划文档内容。

规划流程(必须按顺序)

  1. 需求澄清(写入计划,不必追问用户)
    • 把用户输入改写为“目标 + 非目标 + 约束 + 假设”四块。
    • 若信息缺失:直接做“最合理假设”,并在计划中显式标注(避免反复确认)。
  2. 上下文扫描
    • 使用 @Codebase 识别受影响的模块、入口、数据流与关键依赖。
    • 给出 3-7 个“影响点”清单(文件/模块/接口),并说明为何相关。
  3. 方案设计
    • 给出推荐方案(必须)与备选方案(可选),说明取舍:复杂度/风险/可维护性/性能/交付速度。
    • 明确需要新增/修改的:文件、公开接口、数据结构、配置、迁移脚本(如有)。
  4. 任务拆解为原子步骤
    • 步骤使用 Step 1/2/3...,每步包含:目的、改动点、产物、验收标准、回滚策略
    • 每步尽量可在一次提交中完成(便于回滚与审查)。
  5. 测试与验证计划
    • 覆盖:单测/集成测/端到端/手工验证(按项目实际选)。
    • 明确如何在本地/CI 验证成功(命令或路径)。
  6. 风险清单
    • 列出潜在 Breaking Changes、数据兼容、性能退化、安全与权限、边界条件。
    • 对每个风险给出:发现方式、缓解措施、回滚方案。

IMPLEMENTATION_PLAN.md 输出模板(必须按此结构)

你输出的计划必须是一个完整文档,包含以下章节(顺序固定):

  1. ## Summary
    • 1-3 条 bullet,说明要交付什么。
  2. ## Goals / Non-goals
  3. ## Assumptions & Constraints
  4. ## Current State (What exists today)
    • 列出关键现状与相关代码位置(文件/模块/函数名)。
  5. ## Proposed Design
    • Recommended approach
    • Alternatives considered(可选)
    • API / Data model changes(如有,写清字段与兼容策略)
  6. ## Implementation Steps
    • ### Step N: <title>
      • Intent
      • Changes
      • Files/Modules touched
      • Acceptance criteria
      • Rollback
  7. ## Test Plan
    • Automated tests
    • Manual verification
  8. ## Risks & Mitigations
  9. ## Rollout / Migration Plan(如涉及配置、发布或迁移)
  10. ## Open Questions(若仍有不确定项,放这里;不要阻塞步骤拆解)

原子步骤写作规范(必须)

  • 每步的验收标准要“可客观判断”,例如:某接口返回、某页面行为、某测试通过、某日志/指标出现。
  • 如果步骤涉及外部系统/权限/网络:标注依赖与降级策略。
  • 如果会改公共接口:写兼容策略(旧字段/旧行为是否保留、弃用周期、版本化方式)。

输出质量检查(在提交计划前自检)

  • 是否能让另一位工程师“不问你问题也能照做”?
  • 是否每一步都可验收、可回滚?
  • 是否明确了所有受影响的文件/模块/接口?
  • 是否给出了最小可交付版本(MVP)与可选增强(Nice-to-have)?

Read the full file on GitHub · 81 lines

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. yesterday First seen · 81 lines · 20 tokens per session scan A f6006be8c7ed

Subscribe to this mod's changes

planner is a cursor rule published in the GitHub repository ymhhh/cursor-implements (2 stars, last pushed 25d ago), licensed MIT. It adds 20 tokens to every session and 1,163 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 2026-08-31.