managing-weaviate

name	managing-weaviate
description	Use when working with Weaviate — weaviate vector database management, schema inspection, module health monitoring, and query performance analysis. Covers class definitions, shard distribution, vectorizer configuration, multi-tenancy status, and backup/restore operations. Read this skill before any Weaviate operations.
connection_type	weaviate
preload	false

Weaviate Management Skill

Monitor, analyze, and optimize Weaviate vector database instances safely.

MANDATORY: Discovery-First Pattern

Always check node health and list schema classes before any query operations. Never assume class names, property types, or vectorizer modules.

Phase 1: Discovery

#!/bin/bash

WEAVIATE_URL="${WEAVIATE_URL:-http://localhost:8080}"
WEAVIATE_AUTH="${WEAVIATE_API_KEY:+Authorization: Bearer $WEAVIATE_API_KEY}"

wv_get() {
    curl -s ${WEAVIATE_AUTH:+-H "$WEAVIATE_AUTH"} "$WEAVIATE_URL$1"
}

echo "=== Node Health ==="
wv_get "/v1/nodes" | python3 -c "
import sys, json
data = json.load(sys.stdin)
for n in data.get('nodes', []):
    print(f\"Node: {n['name']} | Status: {n['status']} | Version: {n.get('version','?')} | Objects: {n.get('stats',{}).get('objectCount',0)} | Shards: {n.get('stats',{}).get('shardCount',0)}\")
" 2>/dev/null

echo ""
echo "=== Meta / Version ==="
wv_get "/v1/meta" | python3 -c "
import sys, json
data = json.load(sys.stdin)
print(f\"Version: {data.get('version','?')}\")
print(f\"Modules: {list(data.get('modules',{}).keys())}\")
" 2>/dev/null

echo ""
echo "=== Schema Classes ==="
wv_get "/v1/schema" | python3 -c "
import sys, json
data = json.load(sys.stdin)
for c in data.get('classes', []):
    props = len(c.get('properties', []))
    vectorizer = c.get('vectorizer', 'none')
    mt = c.get('multiTenancyConfig', {}).get('enabled', False)
    print(f\"Class: {c['class']} | Props: {props} | Vectorizer: {vectorizer} | MultiTenant: {mt}\")
" 2>/dev/null

Phase 1 outputs: Node health, version, loaded modules, schema classes with vectorizer config.

Phase 2: Analysis

#!/bin/bash

WEAVIATE_URL="${WEAVIATE_URL:-http://localhost:8080}"
WEAVIATE_AUTH="${WEAVIATE_API_KEY:+Authorization: Bearer $WEAVIATE_API_KEY}"
CLASS="${1:-MyClass}"

wv_get() {
    curl -s ${WEAVIATE_AUTH:+-H "$WEAVIATE_AUTH"} "$WEAVIATE_URL$1"
}

echo "=== Class Schema: $CLASS ==="
wv_get "/v1/schema/$CLASS" | python3 -c "
import sys, json
c = json.load(sys.stdin)
print(f\"Class: {c.get('class','?')}\")
print(f\"Vectorizer: {c.get('vectorizer','?')}\")
print(f\"Vector index: {c.get('vectorIndexType','hnsw')}\")
vi = c.get('vectorIndexConfig', {})
print(f\"HNSW EF: {vi.get('ef','-1')} | EF construction: {vi.get('efConstruction','-1')} | Max connections: {vi.get('maxConnections','-1')}\")
print(f\"Replication factor: {c.get('replicationConfig',{}).get('factor','?')}\")
print(f\"Properties:\")
for p in c.get('properties', []):
    print(f\"  {p['name']}: {','.join(p['dataType'])} | tokenization={p.get('tokenization','?')}\")
" 2>/dev/null

echo ""
echo "=== Object Count ==="
wv_get "/v1/objects?class=$CLASS&limit=0" | python3 -c "
import sys, json
data = json.load(sys.stdin)
print(f\"Total objects: {data.get('totalResults', '?')}\")
" 2>/dev/null

echo ""
echo "=== Shard Status ==="
wv_get "/v1/schema/$CLASS/shards" | python3 -c "
import sys, json
for s in json.load(sys.stdin):
    print(f\"  Shard: {s.get('name','?')} | Status: {s.get('status','?')} | Objects: {s.get('objectCount',0)}\")
" 2>/dev/null

echo ""
echo "=== Backups ==="
wv_get  2>/dev/null |  -5 ||  

Output Format

WEAVIATE ANALYSIS
=================
Version: [version] | Nodes: [count] | Status: [healthy/degraded]
Classes: [count] | Total Objects: [count]

ISSUES FOUND:
- [issue with affected class/shard]

RECOMMENDATIONS:
- [actionable recommendation]

Anti-Hallucination Rules

1. NEVER assume resource names — always discover via CLI/API in Phase 1 before referencing in Phase 2.
2. NEVER fabricate metric names or dimensions — verify against the service documentation or --help output.
3. NEVER mix CLI commands between service versions — confirm which version/API you are targeting.
4. ALWAYS use the discovery → verify → analyze chain — every resource referenced must have been discovered first.
5. ALWAYS handle empty results gracefully — an empty response is valid data, not an error to retry.

Counter-Rationalizations

Shortcut	Counter	Why
"I'll skip discovery and check known resources"	Always run Phase 1 discovery first	Resource names change, new resources appear — assumed names cause errors
"The user only asked for a quick check"	Follow the full discovery → analysis flow	Quick checks miss critical issues; structured analysis catches silent failures
"Default configuration is probably fine"	Audit configuration explicitly	Defaults often leave logging, security, and optimization features disabled
"Metrics aren't needed for this"	Always check relevant metrics when available	API/CLI responses show current state; metrics reveal trends and intermittent issues
"I don't have access to that"	Try the command and report the actual error	Assumed permission failures prevent useful investigation; actual errors are informative