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/querygit clone --depth 1 https://github.com/weaviate/agent-skillsWhat 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 | $0.00013 | $0.00332 |
| Opus 5 | $0.00006 | $0.00166 |
| Sonnet 5 | $0.00003 | $0.00066 |
| Haiku 4.5 | $0.00001 | $0.00033 |
Grade A, and why
query 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 2d 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.
What it actually says
Query Weaviate (Search Mode)
Use Query Agent to search Weaviate collections with natural language. Returns objects for further processing.
Usage
/weaviate:query query "your search query" collections "Collection1,Collection2" limit 10
Workflow
When necessary, use AskUserQuestion to make entering arguments easier.
- Parse the query, collections, and limit arguments
- If arguments are missing:
- Run
/weaviate:collectionsto list available collections - Use AskUserQuestion to prompt user to select
- Default limit to 10 if not specified
- Run
- Run the Query Agent search script:
uv run ${CLAUDE_PLUGIN_ROOT}/skills/weaviate/scripts/query_search.py --query "USER_QUERY" --collections "COLLECTION_1,COLLECTION_2" --limit "LIMIT" - Display results to user
Example
/weaviate:query query "articles about vector databases" collections "Articles,BlogPosts" limit 5
For Generated Answers
Use /weaviate:ask instead to get generated answers with sources.
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.
- 2d ago First seen · 47 lines · 13 tokens per session scan A 92436bd66ef7
query is a command published in the GitHub repository weaviate/agent-skills (103 stars, last pushed 2mo ago), licensed BSD-3-Clause. It adds 13 tokens to every session and 332 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
ai-pipeline
RAG/embedding pipeline scaffolding — delegates to ai-data-engineer agent.
agent-brain-index
Index documents for semantic search.
agent
Add an AI agent / RAG backend (@convex-dev/agent) to the Convex app.
ingest
Manually add knowledge to the Weaviate store.
build-search-index
Build or refresh a vault's LOCAL BM25 search index (wiki-meta/search-index.json) — a deterministic, plugin-free search tier that works on every vault, including those without Smart Connections. Idempotent (fingerprint check → no rewrite). (Skill build-search-index handles natural-language triggers.).
proofrag
Evaluate a RAG/LLM app — generate a golden set, judge it, and produce a scorecard.