Borrowing it
Nothing to install: this file belongs to weixr18/my-digital-life. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/weixr18/my-digital-life/main/.claude/skills/dialogue-to-memory/SKILL.mdgit clone --depth 1 https://github.com/weixr18/my-digital-lifeWrote 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/weixr18/my-digital-life/dialogue-to-memory)<a href="https://agentmods.dev/skills/weixr18/my-digital-life/dialogue-to-memory"><img src="https://agentmods.dev/badge/skills/weixr18/my-digital-life/dialogue-to-memory/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/weixr18/my-digital-life/dialogue-to-memory"><img src="https://agentmods.dev/badge/skills/weixr18/my-digital-life/dialogue-to-memory.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 | $0.00050 | $0.00643 |
| Opus 5 | $0.00025 | $0.00321 |
| Sonnet 5 | $0.00010 | $0.00129 |
| Haiku 4.5 | $0.00005 | $0.00064 |
Grade A, and why
dialogue-to-memory 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 12d 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
对话整理存档 (Dialogue to Memory)
将重要对话整理为结构化 Markdown 文档，存入用户指定的知识库位置。
使用时机
- 对话涉及重要洞察、决策或自我发现时
- 用户希望保存对话内容供日后回顾时
- 对话探索了复杂主题，需要结构化整理时
- 用户主动要求存档本次对话时
执行流程
1. 确认存档意愿
询问用户："是否需要将本次对话整理为文档存入知识库？"
在获得用户明确确认后再继续执行。
2. 确认存储位置
请用户指定存储路径，一般为：2认知库/4觉察对话记录/
3. 确定文件名
根据对话主题生成简洁文件名，格式：主题-核心关键词.md
如无法确定，提供建议的文件名并请用户确认。
4. 整理文档结构
按以下结构组织内容：
# [标题]
**对话时间**: YYYY-MM-DD
**对话主题**: [一句话概括]
**数字生命**: {agent_name}
---
## 背景
[对话发生的上下文，用户面临的问题或情境]
---
## 一、[核心议题1]
[该议题的关键内容、分析、洞察]
---
## 二、[核心议题2]
...
---
## [关键洞察/结论]
[对话中产生的核心洞察、结论或建议]
---
## 未解之问
[对话结尾留下的、需要用户后续反思的问题]
---
## 附录：对话中的关键引用
> "引用内容"
...
---
*本文档记录了{user_name}与数字分身关于[主题]的对话，供后续参考与反思。*
5. 执行存档
使用 Write 工具将整理好的内容写入指定路径。
6. 确认完成
向用户确认文档已保存，并告知完整路径。
注意事项
- 保持客观：如实记录对话内容，不添加未讨论的洞察
- 结构清晰：使用标题层级、列表、表格等提升可读性
- 保留引用：将对话中的关键句子作为引用存入附录
- 用户确认：文件名和存储路径需经用户确认
- 简洁原则：避免冗长复述，提取核心内容即可
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.
- 12d ago First seen · 104 lines · 50 tokens per session scan A 915450ae656e
dialogue-to-memory is a skill published in the GitHub repository weixr18/my-digital-life (20 stars, last pushed 5mo ago), licensed MIT. It adds 50 tokens to every session and 643 once invoked, about $0.0003 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 2026-08-30.
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