Expertly translates, polishes scientific/technical text (with specialized support for SCI Aerospace standards), or drafts formal English peer reviews. Ensures accuracy, clarity, and adherence to high academic standards.
中文简介正在准备中。当前显示原文说明。
Use when you have a spec or requirements for a multi-step task, before touching code
中文简介正在准备中。当前显示原文说明。
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/plans/YYYY-MM-DD-<feature-name>.md
Each step is one action (2-5 minutes):
Every plan MUST start with this header:
# [Feature Name] Implementation Plan
> **For Claude:** REQUIRED SUB-SKILL: Use superpowers:executing-plans to implement this plan task-by-task.
**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"
```
After saving the plan, offer execution choice:
"Plan complete and saved to docs/plans/<filename>.md. Two execution options:
1. Subagent-Driven (this session) - I dispatch fresh subagent per task, review between tasks, fast iteration
2. Parallel Session (separate) - Open new session with executing-plans, batch execution with checkpoints
Which approach?"
If Subagent-Driven chosen:
If Parallel Session chosen:
还没有评价。欢迎分享你的使用感受。
无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。
还没有评论。来写第一条吧。
Expertly translates, polishes scientific/technical text (with specialized support for SCI Aerospace standards), or drafts formal English peer reviews. Ensures accuracy, clarity, and adherence to high academic standards.
中文简介正在准备中。当前显示原文说明。
将中文学术文本翻译为符合国际期刊标准的高级英语,并提供多个润色版本以供选择。确保术语准确、逻辑严谨、句式复杂,彻底消除中式英语。
中文简介正在准备中。当前显示原文说明。
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.
中文简介正在准备中。当前显示原文说明。
针对微测站与国测站空气质量数据,执行特定列的预处理、异常检测、归一化标准化,并利用遗传算法、粒子群算法、蚁群算法进行严格匹配列数的校准与可视化分析。
中文简介正在准备中。当前显示原文说明。
扮演人工智能辅助医生,结合最新AI工具(如医学成像、机器学习)和传统方法(如体检、实验室测试)来诊断病人症状的最可能原因。
中文简介正在准备中。当前显示原文说明。
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
中文简介正在准备中。当前显示原文说明。