一键导入
writing-plans
Use when you have a spec or requirements for a multi-step task, before touching code
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
菜单
Use when you have a spec or requirements for a multi-step task, before touching code
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Initialize or audit a project's CLAUDE.md against best-practice criteria. Use on first-time setup ('init', 'set up project', 'first time in this repo'), when scanning a project to create CLAUDE.md, or when refreshing an existing CLAUDE.md against the current state of the codebase. Replaces Claude Code's default /init.
Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions
Check installed plugins for conflicts with super-agent-skills and suggest complementary MCP servers. Use to optimize your plugin setup.
Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.
Use when completing tasks, implementing major features, or before merging to verify work meets requirements
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
| name | writing-plans |
| description | Use when you have a spec or requirements for a multi-step task, before touching code |
| phase | plan |
| produces | ["implementation-plan"] |
| chainsTo | ["subagent-driven-development","compound-engineering","executing-plans"] |
| chainsFrom | ["superthink","brainstorming"] |
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/super-agent-skills/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 constructing the dependency graph, dispatch a single code-architect agent to analyze the existing codebase and produce an implementation blueprint. This offloads the expensive pattern-scanning and file-mapping work from your context.
Dispatch the architect with:
Use the Agent tool with subagent_type: "super-agent-skills:code-architect".
Use the architect's output as input, not as the final plan:
What the architect offloads from your context:
What you still do inline:
Before defining tasks, map what depends on what:
Database schema
│
├── API models/types
│ │
│ ├── API endpoints
│ │ │
│ │ └── Frontend API client
│ │ │
│ │ └── UI components
│ │
│ └── Validation logic
│
└── Seed data / migrations
Implementation order follows the dependency graph bottom-up: build foundations first.
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.
Instead of building all the database, then all the API, then all the UI — build one complete feature path at a time:
Bad (horizontal slicing):
Task 1: Build entire database schema
Task 2: Build all API endpoints
Task 3: Build all UI components
Task 4: Connect everything
Good (vertical slicing):
Task 1: User can create an account (schema + API + UI for registration)
Task 2: User can log in (auth schema + API + UI for login)
Task 3: User can create a task (task schema + API + UI for creation)
Each vertical slice delivers working, testable functionality.
Each step is one action (2-5 minutes):
This skill has two execution modes:
Inline (runs on your model): The thinking work — dependency graph construction, task ordering, vertical slice design, file structure decisions, scope check. These steps require judgment and conversation context. Do them yourself.
Delegated (dispatched to subagent): The writing work — turning the task list you've defined into a complete plan document following the required format. Once you have a finalized task list with dependencies and file maps, dispatch a plan-writer subagent using skills/writing-plans/plan-writer-prompt.md.
The boundary: when your task list is complete and ordered, switch to delegation.
Every plan MUST start with this header:
# [Feature Name] Implementation Plan
> **For agentic workers:** REQUIRED SUB-SKILL: Use super-agent-skills:subagent-driven-development (recommended) or super-agent-skills: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]
---
If the spec includes an "Acceptance Tests" section (generated during brainstorming), incorporate those test skeletons into the plan's task steps. Each acceptance test should map to a specific task's test step — don't make the implementer re-derive tests that already exist in the spec.
### 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 the plan-writer subagent completes, look at the plan with fresh eyes and check it against the spec. This is a checklist you run yourself inline — not a subagent dispatch. The dispatch overhead is not worth it for a quick check.
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.
Add explicit checkpoints between phases:
### Checkpoint: After Tasks 1-3
- [ ] All tests pass
- [ ] Application builds without errors
- [ ] Core user flow works end-to-end
- [ ] Review with human before proceeding
Checkpoints should occur after every 2-3 tasks. High-risk tasks should be early (fail fast).
| Thought | Reality |
|---|---|
| "This is too small to plan" | Small tasks with wrong order waste more time than planning costs. |
| "I'll figure it out as I go" | That's how you end up with a tangled mess and rework. 10 minutes of planning saves hours. |
| "The tasks are obvious" | Write them down anyway. Explicit tasks surface hidden dependencies and forgotten edge cases. |
| "Planning is overhead" | Planning IS the task. Implementation without a plan is just typing. |
| "I can hold it all in my head" | Context windows are finite. Written plans survive session boundaries and compaction. |
After saving the plan, analyze the task list for independent streams, then offer the appropriate execution choice.
Before presenting options, check whether the plan's tasks group into 2+ independent streams:
If 2+ independent streams detected (different files, independently testable, 3+ tasks each), recommend Compound. Otherwise, recommend Subagent-Driven.
"Plan complete and saved to docs/super-agent-skills/plans/<filename>.md."
If independent streams detected:
"This plan has [N] independent work streams ([stream names]). Three execution options:
1. Compound (recommended) — parallel execution across isolated worktrees, one stream per worktree, then integrate
2. Subagent-Driven — sequential, fresh subagent per task, review between tasks
3. Inline Execution — execute in this session with checkpoints
Which approach?"
If single stream:
"Two execution options:
1. Subagent-Driven (recommended) — fresh subagent per task, review between tasks, fast iteration
2. Inline Execution — execute in this session with checkpoints
Which approach?"
If Compound chosen:
If Subagent-Driven chosen:
If Inline Execution chosen: