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Semantic Memory Boost
by
bkes994408-cmd
· GitHub ↗
· v1.0.0
· MIT-0
231
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0
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1
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1
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Install in OpenClaw
/install semantic-memory-boost
Description
Enhances AI context relevance and accuracy by layered semantic retrieval and alignment for complex, multi-temporal decision-making and project planning.
Usage Guidance
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.
Capability Analysis
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.
Capability Assessment
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.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install semantic-memory-boost - After installation, invoke the skill by name or use
/semantic-memory-boost - Provide required inputs per the skill's parameter spec and get structured output
Version History
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.
Metadata
Frequently Asked Questions
What is Semantic Memory Boost?
Enhances AI context relevance and accuracy by layered semantic retrieval and alignment for complex, multi-temporal decision-making and project planning. It is an AI Agent Skill for Claude Code / OpenClaw, with 231 downloads so far.
How do I install Semantic Memory Boost?
Run "/install semantic-memory-boost" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Semantic Memory Boost free?
Yes, Semantic Memory Boost is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Semantic Memory Boost support?
Semantic Memory Boost is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Semantic Memory Boost?
It is built and maintained by bkes994408-cmd (@bkes994408-cmd); the current version is v1.0.0.
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