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Semantic Memory Boost
作者
bkes994408-cmd
· GitHub ↗
· v1.0.0
· MIT-0
231
总下载
0
收藏
1
当前安装
1
版本数
在 OpenClaw 中安装
/install semantic-memory-boost
功能描述
Enhances AI context relevance and accuracy by layered semantic retrieval and alignment for complex, multi-temporal decision-making and project planning.
安全使用建议
This skill appears to do what it says (semantic retrieval + saving summaries), but it leaves important questions unanswered. Before installing or enabling it: 1) Ask the developer where `[LONG_TERM_REF]` is stored and how the skill authenticates to it (what credentials or service it uses). 2) Ask where `[MEM_SUMMARIZATION]` files are written, who can read them, and how long they are retained. 3) Avoid using the skill with sensitive or confidential queries until storage and access controls are confirmed. 4) Prefer developers to declare any required config paths or environment variables and to provide a privacy/retention policy. If you cannot get satisfactory answers, treat the skill as potentially risky and do not grant it access to private data.
功能分析
Type: OpenClaw Skill
Name: semantic-memory-boost
Version: 1.0.0
The skill bundle consists of metadata and a Markdown instruction file (SKILL.md) defining a logical workflow for an AI agent to improve semantic memory retrieval and context management. There is no executable code, no network activity, and no evidence of malicious intent or prompt injection. The instructions are purely functional for organizing the agent's reasoning process.
能力评估
Purpose & Capability
Name/description and the SKILL.md align: the workflow describes intent parsing, tiered retrieval, alignment, synthesis, and saving a memory summary, which are expected for a 'semantic memory' enhancement. However, the instructions reference accessing `[LONG_TERM_REF]` (a database of historical specs) and saving `[MEM_SUMMARIZATION]` into 'memory files' while the skill declares no required config paths, storage locations, or credentials — a mismatch between claimed capabilities and declared requirements.
Instruction Scope
SKILL.md stays within the semantic-retrieval domain (intent mapping, retrieval, alignment, token limits, relevance thresholds). It instructs the agent to read session best-practices and long-term references and to write memory summaries. It does not explicitly request arbitrary system files or external endpoints, but the instructions are vague about where long-term data is read from and where memory files are stored, giving the agent broad discretion about persistence and data sources.
Install Mechanism
Instruction-only skill with no install spec and no code files; nothing is written to disk by an installer. This is the lowest-risk install mechanism.
Credentials
The skill declares no environment variables, credentials, or config paths. Yet the runtime instructions presume access to long-term databases and writable memory files. If the agent needs DB credentials or storage paths, those are not declared here — an omission that should be clarified. The current declaration (no creds) is minimal but may be incomplete for the described behavior.
Persistence & Privilege
The workflow explicitly calls for persisting a '[MEM_SUMMARIZATION]' into memory files after responses. Persisting user data is consistent with a memory skill, but the SKILL.md does not specify where data will be stored, retention policies, or access controls. 'always' is false (good), but the skill still requests durable storage implicitly — this is a privacy/persistence concern to confirm with the author.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install semantic-memory-boost - 安装完成后，直接呼叫该 Skill 的名称或使用
/semantic-memory-boost触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.0
Semantic Memory Boost 1.0.0 — Initial Release
- Introduces multi-layered semantic retrieval with intent analysis to improve context and historical data accuracy in AI responses.
- Supports structured workflows: intent parsing, tiered memory retrieval, semantic alignment, synthesis, and memory summarization.
- Enforces constraints such as context window limits and relevance thresholds for quality control.
- Provides a self-checklist and defines clear failure modes for robust operation.
元数据
常见问题
Semantic Memory Boost 是什么？
Enhances AI context relevance and accuracy by layered semantic retrieval and alignment for complex, multi-temporal decision-making and project planning. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 231 次。
如何安装 Semantic Memory Boost？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install semantic-memory-boost」即可一键安装，无需额外配置。
Semantic Memory Boost 是免费的吗？
是的，Semantic Memory Boost 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Semantic Memory Boost 支持哪些平台？
Semantic Memory Boost 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Semantic Memory Boost？
由 bkes994408-cmd（@bkes994408-cmd）开发并维护，当前版本 v1.0.0。
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