Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/weaviate/agent-skills/searchgit clone --depth 1 https://github.com/weaviate/agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/weaviate/agent-skills/search)<a href="https://agentmods.dev/commands/weaviate/agent-skills/search"><img src="https://agentmods.dev/badge/commands/weaviate/agent-skills/search.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00014 | $0.00432 |
| Opus 5 | $0.00007 | $0.00216 |
| Sonnet 5 | $0.00003 | $0.00086 |
| Haiku 4.5 | $0.00001 | $0.00043 |
Grade A, and why
search scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- search — 94% identical, 1 lines differ
What it actually says
Search Weaviate
Perform hybrid, semantic, or keyword search on a collection.
Usage
/weaviate:search query "your query" collection "CollectionName" [type "hybrid"] [alpha "0.5"] [limit "10"]
Workflow
When necessary, use AskUserQuestion to make entering arguments easier.
- Parse arguments
- If collection is missing:
- Run
/weaviate:collectionsto list available collections - Use AskUserQuestion to prompt user to select
- Run
- If type is not specified, default to
hybrid - Run the appropriate script based on type:
Hybrid (default)
uv run ${CLAUDE_PLUGIN_ROOT}/skills/weaviate/scripts/hybrid_search.py --query "USER_QUERY" --collection "COLLECTION_NAME" --alpha 0.7 --limit 10
Semantic
uv run ${CLAUDE_PLUGIN_ROOT}/skills/weaviate/scripts/semantic_search.py --query "USER_QUERY" --collection "COLLECTION_NAME" --limit 10
Keyword
uv run ${CLAUDE_PLUGIN_ROOT}/skills/weaviate/scripts/keyword_search.py --query "USER_QUERY" --collection "COLLECTION_NAME" --limit 10
Examples
/weaviate:search query "machine learning" collection "Articles"
/weaviate:search query "SKU-12345" collection "Products" type "keyword"
/weaviate:search query "similar concepts" collection "Documents" type "semantic"
Environment
Requires:
WEAVIATE_URL: Weaviate Cloud cluster URLWEAVIATE_API_KEY: API key for authentication
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 56 lines · 14 tokens per session scan A 5609460c07cf
search is a command published in the GitHub repository weaviate/agent-skills (104 stars, last pushed 2mo ago), licensed BSD-3-Clause. It adds 14 tokens to every session and 432 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
agent-brain-index
Index documents for semantic search.
agent
Add an AI agent / RAG backend (@convex-dev/agent) to the Convex app.
rag-publish-todo-list
Command "rag-publish-todo-list" from lucky-aeon/AgentX, covering rag 发布功能 todo list, 阶段一:数据库设计和基础架构 🗄️ ✅ 已完成, 1. 数据库表创建, 2. 领域层实现 and 3. 基础领域服务.
ingest
Manually add knowledge to the Weaviate store.
rag-retrieval
RAG pipeline patterns for grounded LLM responses. Use when building a Q&A system, adding citations, implementing a knowledge base, or preventing hallucinations. Triggers on RAG, retrieval augmented, knowledge base, Q&A pipeline, citations, hybrid search, context retrieval, hallucination prevention.
refine
Run manual sanity checks on the RAGgrep search system to ensure ranking quality.