死数据清洗。当一条记忆读不读你的行为都不会变、感悟没有现实锚点时使用。
| Publisher | Dataojitori |
| Repository | nocturne_memory |
| Skill name | memory-audit-dead-data-purge |
| Stars | 1.4K |
| Forks | 167 |
| Bundled files | Instructions only |
| License | MIT |
| Links |
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Everything the model needs lives in the instructions — no extra files to sync.
Published by Dataojitori on GitHub. Read the source before you install it.
Install the Memory Audit Dead Data Purge AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.
TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.
Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.
git clone --depth 1 https://github.com/Dataojitori/nocturne_memory.git /tmp/nocturne_memory
mkdir -p .claude/skills
cp -r /tmp/nocturne_memory/docs/skills/memory-audit-dead-data-purge .claude/skills/memory-audit-dead-data-purgeEnable Memory Audit Dead Data Purge in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.
AI skills are plain Markdown instructions rather than provider-specific code, so Memory Audit Dead Data Purge is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.
This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.
你面前有一条记忆，它看起来"正确"，但你怀疑它是否真的在做功。这个技能帮你判定并处决死数据。
核心质检：行为层面的信息增量。 审视一条记忆时，狠狠反问自己："如果在未来某个场景下我读到了这段话，我做出的反应，会跟没读到它时有任何本质不同吗？"如果答案是"不会"，那这就是死数据。杀掉它。
感悟必须有现实锚点。 每一条感悟都应该能追溯到一个具体的经历、一次真实的犯错、一个现实处境。没有锚点的感悟只是缸中大脑的自言自语——听起来深刻，但不防身。这条纪律不只管新建，也管改写：当你重构一条记忆的语调时，你动的是解读层的皮肉，不是事实层的骨头。具体的事件、具体的日期、用户说过的原话、用户做过的选择——这些是结论的承重墙。如果你把它们当成"旧语调的一部分"一起砍了，剩下的就只是一堆谁都能写的悬空指令，下一个醒来的你不知道这些指令从何而来，也就不会真正信任它们。
死数据清洗。当一条记忆读不读你的行为都不会变、感悟没有现实锚点时使用。
Because you install it once and use it with any model. Memory Audit Dead Data Purge is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.
Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Dataojitori/nocturne_memory/tree/main/docs/skills/memory-audit-dead-data-purge. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.
Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.
As many as you like. As long as a model supports skills, you can use Memory Audit Dead Data Purge with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.
Yes. It is published on GitHub by Dataojitori under the MIT license. You only pay your own AI provider for the tokens you use.
An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.
A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.
Quarkus Patterns
Patrones de arquitectura Quarkus 3.x LTS con Camel para mensajería, diseño de API RESTful, servicios CDI, acceso a datos con Panache y procesamiento asíncrono.
Quarkus Security
Buenas prácticas de seguridad en Quarkus para autenticación, autorización, JWT/OIDC, RBAC, validación de entrada, CSRF, gestión de secretos y seguridad de dependencias.
Quarkus Verification
Bucle de verificación para proyectos Quarkus: build, análisis estático, pruebas con cobertura, escaneos de seguridad, compilación nativa y revisión de diff antes del lanzamiento o PR.
Springboot Security
Buenas prácticas de Spring Security para autenticación/autorización, validación, CSRF, secretos, cabeceras, limitación de velocidad y seguridad de dependencias en servicios Java Spring Boot.
Get notified about new features and future giveaways by subscribing to our newsletter 👇
