B2B サイトの戦略・情報設計。価値提案・メッセージマップ・ジャーニー導線・意思決定マップ・信頼棚卸・トーン/禁止表現まで一気通貫でテンプレ化する。実装前フェーズ専用(全PJ共通)。
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Use when you have a spec or requirements for a multi-step task, before touching code
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
Write comprehensive implementation plans assuming the engineer has zero context for our codebase and questionable taste. Document everything they need to know: which files to touch for each task, code, testing, docs they might need to check, how to test it. Give them the whole plan as bite-sized tasks. DRY. YAGNI. TDD. Frequent commits.
Assume they are a skilled developer, but know almost nothing about our toolset or problem domain. Assume they don't know good test design very well.
Announce at start: "I'm using the writing-plans skill to create the implementation plan."
Context: This should be run in a dedicated worktree (created by brainstorming skill).
Save plans to: docs/superpowers/plans/YYYY-MM-DD-<feature-name>.md
If the spec covers multiple independent subsystems, it should have been broken into sub-project specs during brainstorming. If it wasn't, suggest breaking this into separate plans — one per subsystem. Each plan should produce working, testable software on its own.
Before defining tasks, map out which files will be created or modified and what each one is responsible for. This is where decomposition decisions get locked in.
This structure informs the task decomposition. Each task should produce self-contained changes that make sense independently.
Each step is one action (2-5 minutes):
Every plan MUST start with this header:
# [Feature Name] Implementation Plan
> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking.
**Goal:** [One sentence describing what this builds]
**Architecture:** [2-3 sentences about approach]
**Tech Stack:** [Key technologies/libraries]
---
### Task N: [Component Name]
**Files:**
- Create: `exact/path/to/file.py`
- Modify: `exact/path/to/existing.py:123-145`
- Test: `tests/exact/path/to/test.py`
- [ ] **Step 1: Write the failing test**
```python
def test_specific_behavior():
result = function(input)
assert result == expected
```
- [ ] **Step 2: Run test to verify it fails**
Run: `pytest tests/path/test.py::test_name -v`
Expected: FAIL with "function not defined"
- [ ] **Step 3: Write minimal implementation**
```python
def function(input):
return expected
```
- [ ] **Step 4: Run test to verify it passes**
Run: `pytest tests/path/test.py::test_name -v`
Expected: PASS
- [ ] **Step 5: Commit**
```bash
git add tests/path/test.py src/path/file.py
git commit -m "feat: add specific feature"
```
Every step must contain the actual content an engineer needs. These are plan failures — never write them:
After writing the complete plan, look at the spec with fresh eyes and check the plan against it. This is a checklist you run yourself — not a subagent dispatch.
1. Spec coverage: Skim each section/requirement in the spec. Can you point to a task that implements it? List any gaps.
2. Placeholder scan: Search your plan for red flags — any of the patterns from the "No Placeholders" section above. Fix them.
3. Type consistency: Do the types, method signatures, and property names you used in later tasks match what you defined in earlier tasks? A function called clearLayers() in Task 3 but clearFullLayers() in Task 7 is a bug.
If you find issues, fix them inline. No need to re-review — just fix and move on. If you find a spec requirement with no task, add the task.
After saving the plan, offer execution choice:
"Plan complete and saved to docs/superpowers/plans/<filename>.md. Two execution options:
1. Subagent-Driven (recommended) - I dispatch a fresh subagent per task, review between tasks, fast iteration
2. Inline Execution - Execute tasks in this session using executing-plans, batch execution with checkpoints
Which approach?"
If Subagent-Driven chosen:
If Inline Execution chosen:
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B2B サイトの戦略・情報設計。価値提案・メッセージマップ・ジャーニー導線・意思決定マップ・信頼棚卸・トーン/禁止表現まで一気通貫でテンプレ化する。実装前フェーズ専用(全PJ共通)。
中文简介正在准备中。当前显示原文说明。
Keep a PR merge-ready by triaging comments, resolving clear conflicts, and fixing CI in a loop.
中文简介正在准备中。当前显示原文说明。
法人向けHTMLプレゼンスライドの実装エンジン。Claude Codeから指示書(アウトライン+テンプレート指定+カラー+コンテンツ)を受け取り、単一HTMLファイルとして実装する。43種テンプレート+14種アニメーション。トリガー:プレゼン実装、スライドHTML生成、提案資料コーディング。
中文简介正在准备中。当前显示原文说明。
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
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A Cursor Canvas is a live React app that the user can open beside the chat. You MUST use a canvas when the agent produces a standalone analytical artifact — quantitative analyses, billing investigations, security audits, architecture reviews, data-heavy content, timelines, charts, tables, interactive explorations, repeatable tools, or any response that benefits from visual layout. Especially prefer a canvas when presenting results from MCP tools (Datadog, Databricks, Linear, Sentry, Slack, etc.) where the data is the deliverable — render it in a rich canvas rather than dumping it into a markdown table or code block. If you catch yourself about to write a markdown table, stop and use a canvas instead. You MUST also read this skill whenever you create, edit, or debug any .canvas.tsx file.
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Authors Cursor Rules (.cursor/rules/*.mdc) and custom Subagents (.cursor/agents/*.md or ~/.cursor/agents). Use when creating or refactoring rules/subagents, splitting large rules, choosing subagent vs skill, setting model/readonly/background, or replacing repeated delegation prompts.
中文简介正在准备中。当前显示原文说明。