weaviate

weaviate is a skill for Claude Code, Codex from ashish7802/awesome-api-skills. It costs 0 tokens per session (571 once invoked), scanned A, original, MIT.

A vector search database for finding related content by meaning, including text and other media. It supports semantic search, keyword-plus-vector search, and retrieval-augmented generation (RAG), where retrieved documents provide context to an AI model.

In plain words
What is it for?
Use it to create collections, turn content into searchable vectors, run semantic or hybrid searches, and supply matching documents to AI-generated answers.
Why use it?
It removes the need to build storage and search for embedding-based content yourself. This helps an AI application retrieve relevant information instead of relying only on what the model already knows.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to create collections, turn content into searchable vectors, run semantic or hybrid searches, and supply matching documents to AI-generated answers.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ashish7802/awesome-api-skills/weaviate
Install

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.

Any agent
npx skills add ashish7802/awesome-api-skills --skill weaviate
Clone the repo
git clone --depth 1 https://github.com/ashish7802/awesome-api-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for weaviate

README.md
[![agentmods](https://agentmods.dev/badge/skills/ashish7802/awesome-api-skills/weaviate/github.svg)](https://agentmods.dev/skills/ashish7802/awesome-api-skills/weaviate)
Your own site
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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.

agentmods 80×15 button for weaviate

Your own site · 80×15
<a href="https://agentmods.dev/skills/ashish7802/awesome-api-skills/weaviate"><img src="https://agentmods.dev/badge/skills/ashish7802/awesome-api-skills/weaviate.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 571 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00000 $0.00571
Opus 5 $0.00000 $0.00285
Sonnet 5 $0.00000 $0.00114
Haiku 4.5 $0.00000 $0.00057

Measured yesterday against content hash 23477243690e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

weaviate 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 yesterday.

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.

skills/weaviate/SKILL.md · 74 lines

How it starts

The opening of the file, as written. The whole thing — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Weaviate Vector Database API Skill

Overview

Weaviate is an open-source AI vector search engine designed for scalable semantic search, multi-modal embeddings, and Retrieval-Augmented Generation (RAG).

Installation

npm install weaviate-client
pip install weaviate-client

Connecting to Weaviate

import weaviate, { type WeaviateClient } from 'weaviate-client';

const client: WeaviateClient = await weaviate.connectToWeaviateCloud(
  process.env.WEAVIATE_URL!,
  {
    authCredentials: new weaviate.ApiKey(process.env.WEAVIATE_API_KEY!),
    headers: {
      'X-OpenAI-Api-Key': process.env.OPENAI_API_KEY!,
    },
  }
);

Core API Operations

1. Create Collection with Vectorizer

const articles = await client.collections.create({
  name: 'Article',
  vectorizers: weaviate.configure.vectorizer.text2vecOpenAI({
    model: 'text-embedding-3-small',
  }),
  generative: weaviate.configure.generative.openAI(),
});

2. Hybrid Search (Vector + BM25 Keyword)

const myCollection = client.collections.get('Article');

const response = await myCollection.query.hybrid('neural search and indexing', {
  limit: 5,
  alpha: 0.75, // 0.75 vector, 0.25 keyword BM25
  returnProperties: ['title', 'content', 'category'],
});

for (const obj of response.objects) {
  console.log(obj.properties.title, 'Score:', obj.metadata?.score);
}

3. Generative Search (RAG in single query)

const ragResponse = await myCollection.generate.nearText('distributed vector database', {
  singlePrompt: 'Summarize key benefits of {title} in two sentences.',
  limit: 3,
});

AI Pitfalls & Anti-Hallucination Guidelines

  • v3 Collections API: Modern weaviate-client uses client.collections.get('Name') instead of client.graphql.get().
  • Alpha Parameter: In hybrid queries, alpha=0 performs pure BM25 search, alpha=1 performs pure vector search, and alpha=0.5 balances both equally.

Production Verification Checklist

  • Connect credentials validated against Weaviate Cloud cluster
  • Hybrid search alpha tuned for domain terminology
  • API key headers passed for text2vec/generative providers

Read the full file on GitHub · 74 lines

Files

What ships with it

1 file 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.

Changes

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.

  1. yesterday First seen · 74 lines · 0 tokens per session scan A 23477243690e

Subscribe to this mod's changes

weaviate is a skill published in the GitHub repository ashish7802/awesome-api-skills (13 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 571 tokens. 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 2026-09-10.

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