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 skills add cookieMonsterDev/agents-skills --skill weaviate-docsgit clone --depth 1 https://github.com/cookieMonsterDev/agents-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/skills/cookiemonsterdev/agents-skills/weaviate-docs)<a href="https://agentmods.dev/skills/cookiemonsterdev/agents-skills/weaviate-docs"><img src="https://agentmods.dev/badge/skills/cookiemonsterdev/agents-skills/weaviate-docs/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/cookiemonsterdev/agents-skills/weaviate-docs"><img src="https://agentmods.dev/badge/skills/cookiemonsterdev/agents-skills/weaviate-docs.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00093 | $0.01236 |
| Opus 5.5 | $0.00037 | $0.00494 |
| Sonnet 5.5 | $0.00019 | $0.00247 |
| Haiku 4.5 | $0.00009 | $0.00124 |
Grade A, and why
weaviate-docs 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Weaviate questions are easy to answer from stale memory or from patterns borrowed from a different vector database. Use this skill to ground answers in the official Weaviate documentation and return the closest authoritative page instead of generic vector-search advice.
When to Use
Use this skill when the request is about:
- Weaviate concepts: collections, objects, properties, and vector indexes
- Creating and managing collections, schema design, and CRUD operations on objects
- Similarity search, hybrid search (vector plus keyword), and generative search (RAG)
- Filtering, aggregations, and the REST, GraphQL, or gRPC APIs
- Model provider integrations (embedding and generative modules) and vectorizer configuration
- Multi-tenancy, replication, and sharding architecture
- Client libraries (Python, TypeScript/JavaScript, Java, Go)
- Deployment: Docker, Kubernetes, embedded Weaviate, and Weaviate Cloud
- Performance tuning, vector quantization, and best practices
Do not use this skill for:
- Qdrant-specific concepts (payload indexes, collection-level shard keys). Use
qdrant-docsinstead. - Pinecone-specific concepts (serverless index architecture, namespaces-as-tenants). Use
pinecone-docsinstead. - MongoDB Atlas Vector Search or Redis vector sets. Use
mongodb-docsorredis-docsinstead. - General embedding model selection or RAG architecture unless the question is specifically about Weaviate configuration or behavior.
Workflow
1. Classify the request
Decide which bucket the question belongs to before searching:
- Getting started, quickstart, and starter guides
- Concepts and architecture
- Managing collections and objects (schema, CRUD)
- Search: similarity, hybrid, generative, and filtering
- Model provider integrations
- Configuration: replication, multi-tenancy, quantization
- Client libraries and API reference
- Deployment: Docker, Kubernetes, embedded, or Weaviate Cloud
If you need a quick starting point, load references/topic-map.md and jump to the closest section.
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 101 lines · 93 tokens per session scan A 580c32bfde5b
weaviate-docs is a skill published in the GitHub repository cookieMonsterDev/agents-skills (6 stars, last pushed today), licensed MIT. It adds 93 tokens to every session and 1,236 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-08-31.
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