Semantic Search Cwicr
Semantic search in DDC CWICR construction database using vector embeddings. Find similar work items and resources for cost estimation.
Why use this skill?
Use semantic AI search for construction cost estimation. Find work items across 9 languages using DDC CWICR and vector embeddings for 90% faster lookup.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/datadrivenconstruction/semantic-search-cwicrWhat This Skill Does
The Semantic Search Cwicr skill provides an intelligent, vector-based search interface for the DDC CWICR construction database. Unlike traditional keyword matching, this skill leverages OpenAI's text-embedding-3-large model to interpret the intent and context of construction-related queries. It allows users to query over 55,000 work items in nine different languages, bridging the gap between natural language descriptions and technical database entries. By transforming natural language requests into high-dimensional vectors, the agent can surface relevant resources and work items even when specific industry terminology differs from the user's input.
Installation
To integrate this skill, use the following command in your terminal: clawhub install openclaw/skills/skills/datadrivenconstruction/semantic-search-cwicr
Ensure that you have your OpenAI API key configured in your environment variables, as the skill requires it to generate embeddings for real-time queries. You will also need a running Qdrant instance as outlined in the prerequisite setup documentation.
Use Cases
This skill is designed for cost estimators, project managers, and construction engineers. Typical scenarios include: identifying appropriate resource items for budget estimates, finding equivalent work items in international contexts, and quickly navigating massive construction item databases without requiring exact database schema knowledge.
Example Prompts
- "Find me the most relevant work items for 'installing reinforced concrete foundation' in the database."
- "Search for resources related to 'structural steel beam fireproofing' with a similarity threshold of at least 0.75."
- "Show me all masonry work items that match the concept of 'high-durability exterior brick facade' across the database."
Tips & Limitations
To get the best results, provide descriptive input rather than short keywords; the semantic engine performs better with full sentences. Be aware that the min_score parameter acts as a filter, so setting it too high might yield zero results. Always verify the similarity score provided in the output to ensure the relevance of the matched items. This tool relies on external API calls for embedding generation; ensure your internet connection is stable and your API quotas are sufficient for high-volume searching.
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-datadrivenconstruction-semantic-search-cwicr": {
"enabled": true,
"auto_update": true
}
}
}Tags(AI)
Flags: network-access, external-api
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