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 commands/funiq-lab/your-mind/cardgit clone --depth 1 https://github.com/funiq-lab/your-mindWhat 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 | $0.00000 | $0.01006 |
| Opus 5 | $0.00000 | $0.00503 |
| Sonnet 5 | $0.00000 | $0.00201 |
| Haiku 4.5 | $0.00000 | $0.00101 |
Grade A, and why
card 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 2d 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.
What it actually says
技术卡片创建
创建技术卡片到 tech/ 目录。
使用方式
/card problem [标题] # 创建问题卡片
/card knowledge [标题] # 创建知识卡片
/card # 交互式选择类型
执行步骤
1. 解析参数
从用户输入中提取：
- 卡片类型：
problem或knowledge - 标题：可选，用于生成文件名
如果未提供类型，询问用户选择。
2. 生成文件信息
- 日期：当前日期
YYYY-MM-DD - 文件名：
YYYY-MM-DD-{标题的英文slug}.md - 目录：
- 问题卡片 →
tech/problems/ - 知识卡片 →
tech/knowledge/
- 问题卡片 →
3. 读取标签索引
读取对应的标签索引文件，便于用户选择标签：
- 问题卡片：
tech/problems/tags.md - 知识卡片：
tech/knowledge/tags.md
4. 创建卡片文件
问题卡片模板
---
type: problem
date: {当前日期}
tags: []
status: draft
---
# {标题}
## 问题描述
**何时遇到**：{当前日期}
**什么场景**：
[描述遇到问题的具体场景、项目背景]
**问题现象**：
[具体的错误信息、表现、影响范围]
---
## 原因分析
[问题的根本原因是什么？]
---
## 解决方案
### 尝试过的方法
1. [方法1] - 结果：[成功/失败/部分有效]
### 最终方案
[详细的解决步骤]
---
## 经验教训
- [从这个问题中学到了什么？]
- [下次如何避免？]
---
## 参考资料
- [来源名称](URL)
---
**创建时间**：{当前日期}
**最后更新**：{当前日期}
**审核状态**：未审核
知识卡片模板
---
type: knowledge
date: {当前日期}
tags: []
status: draft
---
# {标题}
## 一句话概要
[用一句话解释这个知识点是什么]
---
## 详细解释
[完整的解释，包括定义、原理、机制等]
---
## 典型例子
### 例子 1：[场景名]
[具体案例描述]
---
## 应用场景
- [什么时候会用到这个知识？]
- [如何应用？]
---
## 常见误区
- [人们容易误解的点]
---
## 相关概念
- [[相关知识1]]
---
## 参考来源
- [来源名称](URL)
---
**创建时间**：{当前日期}
**最后更新**：{当前日期}
**审核状态**：未审核
5. 输出结果
创建成功后，输出：
✓ 已创建{卡片类型}：{文件路径}
请补充以下内容：
- [根据卡片类型列出需要填写的字段]
可用标签参考：{列出常用标签}
完成后，可运行 `tech-reviewer` 进行审核。
示例
创建问题卡片
输入：
/card problem 高并发下连接池耗尽
输出：
✓ 已创建问题卡片：tech/problems/2025-12-26-connection-pool-exhaustion.md
请补充以下内容：
- 问题描述（场景、现象）
- 原因分析
- 解决方案
- 经验教训
可用标签参考：#高并发 #数据库 #性能问题 #云服务器
完成后，可运行 `tech-reviewer` 进行审核。
创建知识卡片
输入：
/card knowledge 幸存者偏差
输出：
✓ 已创建知识卡片：tech/knowledge/2025-12-26-survivor-bias.md
请补充以下内容：
- 一句话概要
- 详细解释
- 典型例子
- 应用场景
可用标签参考：#认知偏差 #心理学 #概念 #决策
完成后，可运行 `tech-reviewer` 进行审核。
注意事项
- 文件名使用英文 slug，中文标题保留在文件内
- 创建后提示用户去补充内容
- 提醒用户完成后可使用 tech-reviewer 审核
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.
- 2d ago First seen · 227 lines · 0 tokens per session scan A 6b10c5462488
card is a command published in the GitHub repository funiq-lab/your-mind (11 stars, last pushed 8mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,006 tokens. 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 2026-08-30.
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