Enhanced Search Service

Enhances memory search by combining co-occurrence graph analysis and semantic similarity for improved contextual relevance and ranking.

Security Scan

The skill's code and documentation mostly match its stated purpose, but there are inconsistencies and a risky absolute import path that warrant review before installing.

Purpose & Capability

The code implements co-occurrence + semantic scoring as described. However SKILL.md lists additional files and an adapter (integration/adapter/enhanced_search_adapter.py and other docs) that are not present in the packaged files — an inconsistency between claimed surface and provided artifacts.

Instruction Scope

The runtime script inserts an absolute path ('/root/.openclaw/workspace/integration/adapter') into sys.path and attempts to import adapters from there. That design is plausible for an adapter architecture, but it allows the skill to load code from the agent's workspace root (other adapters/plugins). The SKILL.md does not explicitly instruct the agent to access unrelated system paths, yet the code does so. Review of the adapters that will be imported is required because they may perform network I/O or access credentials.

Install Mechanism

There is no install spec (instruction-only), which is low risk, but the package actually includes a Python implementation file. Because no install occurs, nothing is written by an installer, yet the presence of runtime code means you must review that code and any adapters it imports.

Credentials

The skill declares no required environment variables, credentials, or config paths. The code itself does not read environment secrets. That is proportionate to the stated search-enhancement purpose.

Persistence & Privilege

always is false and the skill does not request elevated or persistent platform privileges. It does attempt to import adapters at runtime, but does not modify other skills' configs or force installation.

What to consider before installing

This skill appears to implement the advertised enhancement logic, but two things need attention before installing or enabling it: (1) SKILL.md references adapter and integration files that are not included in the package — ask the publisher for the missing adapter files or confirm where the adapters will come from. (2) The Python code inserts an absolute workspace path and imports adapters from there, which means the skill will execute code from your agent's workspace (other adapters). You should: review the adapter implementations that will be imported (co_occurrence_adapter and semantic_vector_adapter) to ensure they don't make unexpected network calls or access credentials; run the skill in a sandboxed environment if possible; and verify that no adapter will exfiltrate content. If you cannot inspect the adapters, treat this as higher risk and avoid enabling it in sensitive environments.

Description

Provides enhanced memory search by combining co-occurrence graph analysis and semantic vector similarity. This plugin sits between memory storage and query interfaces, offering improved relevance ranking through contextual relationships and semantic understanding.

Core Capabilities

• Unified Search: Combines co-occurrence graph expansion with semantic vector similarity
• Relevance Ranking: Multi-factor scoring (text match, co-occurrence strength, semantic similarity)
• Context Awareness: Leverages memory relationships to surface relevant but non-obvious connections
• Plugin Architecture: Independent service that can be upgraded/replaced without affecting other components

Dependencies

• Co-occurrence Engine (co-occurrence-engine): Provides relationship graph for contextual expansion
• Semantic Vector Store (semantic-vector-store): Provides semantic similarity scoring
• Memory Integration (memory-integration): Optional, for direct memory access if needed

Usage

As a Plugin User

from enhanced_search_adapter import EnhancedSearchAdapter

adapter = EnhancedSearchAdapter()
results = adapter.enhance_search("query about memory sync", max_results=10)

As a System Integrator

The plugin provides an adapter that implements the standard memory adapter interface with additional enhancement methods.

Skill Files

enhanced-search-service/
├── SKILL.md (this file)
├── scripts/
│   └── enhanced_search_service.py  # Core service implementation
├── integration/
│   └── adapter/
│       └── enhanced_search_adapter.py  # Adapter for star architecture
└── references/
    ├── api.md           # API documentation
    └── architecture.md  # Design and integration notes

Configuration

Default configuration (can be overridden via adapter initialization):

search:
  co_occurrence_weight: 0.3
  semantic_weight: 0.5
  text_match_weight: 0.2
  max_expansion: 5
  min_relevance_threshold: 0.1

Integration with Star Architecture

This plugin connects to the Memory Sync Enhanced (MSE) hub through its adapter. It consumes data from:

• Co-occurrence engine (for relationship data)
• Semantic vector store (for similarity data)

It produces enhanced search results for:

• Memory Integration system
• Direct user queries
• Other plugins needing sophisticated search

Health Checks

The adapter provides health monitoring for:

• Dependency availability (co-occurrence engine, semantic vector store)
• Search performance metrics
• Result quality indicators

Version History

• v0.1.0 (initial): Basic enhancement combining co-occurrence scores with semantic similarity
• v0.2.0 (planned): Advanced fusion algorithms and caching
• v0.3.0 (planned): Learning-based weighting adaptation

Development Notes

This is a Phase 3 split from the original memory-integration plugin. The goal is to create a single-function plugin focused solely on search enhancement, following the star architecture principle of separation of concerns.