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 agentmods add skills/w693847022/memory_service/solution-designnpx skills add w693847022/memory_service --skill solution-designgit clone --depth 1 https://github.com/w693847022/memory_serviceWrote 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/w693847022/memory_service/solution-design)<a href="https://agentmods.dev/skills/w693847022/memory_service/solution-design"><img src="https://agentmods.dev/badge/skills/w693847022/memory_service/solution-design.svg" alt="Measured on agentmods" 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 | $0.00029 | $0.02914 |
| Opus 5 | $0.00015 | $0.01457 |
| Sonnet 5 | $0.00006 | $0.00583 |
| Haiku 4.5 | $0.00003 | $0.00291 |
Grade A, and why
solution-design 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 3d 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.
How it starts
The opening of the file, as written. The whole thing — 457 lines — stays where its author put it; the contents beside it link to each section on GitHub.
方案设计与选择技能 (增强版)
参数规范
| 参数 | 说明 | 处理方式 |
|---|---|---|
需求描述 |
功能/问题描述 | 创建 feature 记录 |
id |
已存在的 feature_id 或 fix_id | 查询已有记录 |
| 无参数 | - | 列出待处理项供选择 |
前置条件
必需前置条件
- 项目已注册到 memory_mcp
推荐前置条件
- 已完成相关性探索结果
⚠️ 重要指令
DO NOT ENTER PLAN MODE - 此技能要求直接执行,不进入计划模式
所有memory_mcp的操作使用子代理来处理,减少主窗口上下文
初始化
-
确定项目 ID
- 从 CLAUDE.md 读取项目名称
- 通过 memory_mcp 查询获取 project_id
-
获取或创建目标条目
情况A: 参数是已存在的 id (格式如 feat_YYYYMMDD_N 或 fix_YYYYMMDD_N)
- 直接查询该 id
- 获取条目详情
情况B: 参数是需求描述
- 使用子代理调用
project_add创建 feature 记录 - 获取新创建的 feature_id
情况C: 无参数
- 列出 features 分组中 status=pending/in_progress 的条目
- 列出 fixes 分组中 status=pending/in_progress 的条目
- 让用户选择一个
-
读取关联内容:
- 条目的 content 字段(需求/问题描述)
- 条目的 tags(了解上下文)
- 如果条目有 related 字段,读取关联的 note 内容
-
读取项目规范,确保方案符合规范要求
阶段 1: 代码库探索与需求分析
目标: 深入理解现有架构和需求
流程:
-
使用 Explore 代理探索代码库 (thoroughness: medium)
- 分析现有架构模式
- 识别相关模块和依赖
- 查找类似功能的实现参考
-
需求拆解
- 识别核心需求点
- 识别边界条件
- 识别约束条件(性能、安全、兼容性等)
-
输出探索摘要给用户确认
阶段 2: 方案设计与迭代
目标: 设计多个可行方案并迭代优化
2.1 初始方案设计
设计 2-3 个 不同方向的实现方案,每个方案包含:
方案格式:
## 方案 N: <方案名称>
### 核心思路
<用1-2句话描述方案的核心思想>
### 架构设计
<描述涉及的主要组件和它们的关系>
### 多维度评估
| 维度 | 评分 (1-5) | 说明 |
|------|-----------|------|
| 实现复杂度 | ⭐⭐⭐ | <说明> |
| 可维护性 | ⭐⭐⭐⭐ | <说明> |
| 性能影响 | ⭐⭐ | <说明> |
| 风险等级 | ⭐⭐ | <说明> |
| 扩展性 | ⭐⭐⭐⭐ | <说明> |
### 优点
- <优点1>
- <优点2>
- ...
### 缺点
- <缺点1>
- <缺点2>
- ...
### 技术选型
| 技术点 | 选择方案 | 备选方案 |
|--------|---------|---------|
| <技术点1> | <选择> | <备选> |
| <技术点2> | <选择> | <备选> |
### 实现步骤概要
1. <步骤1>
2. <步骤2>
...
### 影响范围
- **修改文件**: <文件列表>
- **新增文件**: <文件列表>
- **影响模块**: <模块列表>
### 风险识别
- <风险1>: <影响> → <缓解措施>
- <风险2>: <影响> → <缓解措施>
---
2.2 方案对比表格
向用户展示方案对比:
| 方案 | 复杂度 | 可维护性 | 性能 | 风险 | 推荐指数 |
|------|--------|----------|------|------|----------|
| 方案一 | ⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐ | ⭐⭐ | ⭐⭐⭐⭐ |
| 方案二 | ⭐⭐ | ⭐⭐⭐ | ⭐⭐⭐⭐ | ⭐⭐⭐ | ⭐⭐⭐ |
| 方案三 | ⭐⭐⭐⭐ | ⭐⭐ | ⭐⭐⭐ | ⭐ | ⭐⭐⭐⭐ |
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.
- 3d ago First seen · 457 lines · 29 tokens per session scan A 44f9399cfca2
solution-design is a skill published in the GitHub repository w693847022/memory_service (1 stars, last pushed 3mo ago), licensed MIT. It adds 29 tokens to every session and 2,914 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.
Other skills, from other repositories
systematic-debugging
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brainstorming
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auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
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