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.
npx skills add zhaixin244-wq/fnw --skill writing-plansgit clone --depth 1 https://github.com/zhaixin244-wq/fnwWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/zhaixin244-wq/fnw/writing-plans)<a href="https://agentmods.dev/skills/zhaixin244-wq/fnw/writing-plans"><img src="https://agentmods.dev/badge/skills/zhaixin244-wq/fnw/writing-plans/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/zhaixin244-wq/fnw/writing-plans"><img src="https://agentmods.dev/badge/skills/zhaixin244-wq/fnw/writing-plans.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00023 | $0.01546 |
| Opus 5 | $0.00012 | $0.00773 |
| Sonnet 5 | $0.00005 | $0.00309 |
| Haiku 4.5 | $0.00002 | $0.00155 |
Grade A, and why
writing-plans 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 9d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- writing-plans — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
编写计划
概述
编写全面的实现计划,假设工程师对我们的代码库零上下文,且品味存疑。记录他们需要知道的一切:每个任务要修改哪些文件、代码、测试、可能需要查阅的文档、如何测试。将整个计划拆成小步骤任务。DRY。YAGNI。TDD。频繁 commit。
假设他们是有经验的开发者,但对我们的工具链和问题领域几乎一无所知。假设他们不太擅长测试设计。
开始时宣布: "我正在使用 writing-plans 技能创建实现计划。"
上下文: 此技能应在专用 worktree 中运行(由 brainstorming 技能创建)。
计划保存位置: docs/superpowers/plans/YYYY-MM-DD-<feature-name>.md
- (用户对计划位置的偏好优先于此默认值)
范围检查
如果规格涵盖了多个独立子系统,它应该在头脑风暴阶段就被拆分为子项目规格。如果没有,建议将其拆分为独立的计划——每个子系统一个。每个计划应该能独立产出可工作、可测试的软件。
文件结构
在定义任务之前,先列出将要创建或修改的文件以及每个文件的职责。这是锁定分解决策的地方。
- 设计边界清晰、接口定义良好的单元。每个文件应有一个明确的职责。
- 你对能一次放入上下文的代码推理得最好,文件越专注你的编辑越可靠。优先选择小而专注的文件,而非承担过多功能的大文件。
- 一起变更的文件应放在一起。按职责拆分,而非按技术层级拆分。
- 在现有代码库中,遵循已有模式。如果代码库使用大文件,不要单方面重构——但如果你正在修改的文件已经变得难以管理,在计划中包含拆分是合理的。
此结构决定了任务分解。每个任务应产出独立的、有意义的变更。
小步骤任务粒度
每步是一个操作(2-5 分钟):
- "编写失败的测试" - 一步
- "运行它确认失败" - 一步
- "实现最少代码让测试通过" - 一步
- "运行测试确认通过" - 一步
- "Commit" - 一步
计划文档头部
每个计划必须以此头部开始:
# [功能名称] 实现计划
> **面向 AI 代理的工作者:** 必需子技能:使用 superpowers:subagent-driven-development(推荐)或 superpowers:executing-plans 逐任务实现此计划。步骤使用复选框(`- [ ]`)语法来跟踪进度。
**目标:** [一句话描述要构建什么]
**架构:** [2-3 句话描述方案]
**技术栈:** [关键技术/库]
---
任务结构
### 任务 N:[组件名称]
**文件:**
- 创建:`exact/path/to/file.py`
- 修改:`exact/path/to/existing.py:123-145`
- 测试:`tests/exact/path/to/test.py`
- [ ] **步骤 1:编写失败的测试**
```python
def test_specific_behavior():
result = function(input)
assert result == expected
```
- [ ] **步骤 2:运行测试验证失败**
运行:`pytest tests/path/test.py::test_name -v`
预期:FAIL,报错 "function not defined"
- [ ] **步骤 3:编写最少实现代码**
```python
def function(input):
return expected
```
- [ ] **步骤 4:运行测试验证通过**
运行:`pytest tests/path/test.py::test_name -v`
预期:PASS
- [ ] **步骤 5:Commit**
```bash
git add tests/path/test.py src/path/file.py
git commit -m "feat: add specific feature"
```
禁止占位符
每个步骤都必须包含工程师需要的实际内容。以下是计划缺陷——绝不要写出来:
- "待定"、"TODO"、"后续实现"、"补充细节"
- "添加适当的错误处理" / "添加验证" / "处理边界情况"
- "为上述代码编写测试"(没有实际测试代码)
- "类似任务 N"(重复代码——工程师可能不按顺序阅读任务)
- 只描述做什么而不展示怎么做的步骤(代码步骤必须有代码块)
- 引用了未在任何任务中定义的类型、函数或方法
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 153 lines · 23 tokens per session scan A 1763e0dfcf71
writing-plans is a skill published in the GitHub repository zhaixin244-wq/fnw (29 stars, last pushed 3mo ago), licensed MIT. It adds 23 tokens to every session and 1,546 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 2026-09-03.
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