managing-chroma

name	managing-chroma
description	Use when working with Chroma — chroma vector database management, collection inspection, embedding analysis, and query performance monitoring. Covers collection metadata, document counts, distance metrics, index health, and tenant/database configuration. Read this skill before any Chroma operations.
connection_type	chroma
preload	false

Chroma Management Skill

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

MANDATORY: Discovery-First Pattern

Always check server health and list collections before any query operations. Never assume collection names or embedding dimensions.

Phase 1: Discovery

#!/bin/bash

CHROMA_URL="${CHROMA_URL:-http://localhost:8000}"

echo "=== Server Health ==="
curl -s "$CHROMA_URL/api/v1/heartbeat"

echo ""
echo "=== Version ==="
curl -s "$CHROMA_URL/api/v1/version"

echo ""
echo "=== Collections ==="
curl -s "$CHROMA_URL/api/v1/collections" | python3 -c "
import sys, json
data = json.load(sys.stdin)
for c in data:
    meta = c.get('metadata', {}) or {}
    print(f\"Collection: {c['name']} | ID: {c['id'][:12]}... | Distance: {meta.get('hnsw:space', 'l2')}\")
" 2>/dev/null

echo ""
echo "=== Collection Details ==="
for coll_id in $(curl -s "$CHROMA_URL/api/v1/collections" 2>/dev/null | python3 -c "
import sys, json
for c in json.load(sys.stdin):
    print(c['id'])
" 2>/dev/null); do
    count=$(curl -s "$CHROMA_URL/api/v1/collections/$coll_id/count" 2>/dev/null)
    name=$(curl -s "$CHROMA_URL/api/v1/collections/$coll_id" 2>/dev/null | python3 -c "import sys,json; print(json.load(sys.stdin).get('name','?'))" 2>/dev/null)
    echo "  $name: $count documents"
done

Phase 1 outputs: Server health, version, collection list with doc counts and distance metrics.

Phase 2: Analysis

#!/bin/bash

CHROMA_URL="${CHROMA_URL:-http://localhost:8000}"
COLLECTION="${1:-my_collection}"

echo "=== Collection Info ==="
COLL_ID=$(curl -s "$CHROMA_URL/api/v1/collections" | python3 -c "
import sys, json
for c in json.load(sys.stdin):
    if c['name'] == '$COLLECTION':
        print(c['id'])
        break
" 2>/dev/null)

curl -s "$CHROMA_URL/api/v1/collections/$COLL_ID" | python3 -c "
import sys, json
c = json.load(sys.stdin)
meta = c.get('metadata', {}) or {}
print(f\"Name: {c['name']}\")
print(f\"ID: {c['id']}\")
print(f\"Distance function: {meta.get('hnsw:space', 'l2')}\")
print(f\"HNSW construction EF: {meta.get('hnsw:construction_ef', 'default')}\")
print(f\"HNSW M: {meta.get('hnsw:M', 'default')}\")
print(f\"HNSW search EF: {meta.get('hnsw:search_ef', 'default')}\")
" 2>/dev/null

echo ""
echo "=== Document Count ==="
curl -s "$CHROMA_URL/api/v1/collections/$COLL_ID/count"

echo ""
echo "=== Sample Documents ==="
curl -s -X POST "$CHROMA_URL/api/v1/collections/$COLL_ID/get" \
    -H "Content-Type: application/json" \
    -d '{"limit": 3, "include": ["metadatas", "documents"]}' | python3 -c "
import sys, json
data = json.load(sys.stdin)
ids = data.get('ids', [])
docs = data.get('documents', [])
metas = data.get('metadatas', [])
for i, id in enumerate(ids[:3]):
    doc = docs[i][:80] if docs and i < len(docs) and docs[i] else '?'
    meta = metas[i] if metas and i < len(metas) else {}
    print(f\"  {id}: {doc}... | meta={meta}\")
" 2>/dev/null

Output Format

CHROMA ANALYSIS
===============
Server: [healthy/unhealthy] | Version: [version]
Collections: [count] | Total Documents: [count]

ISSUES FOUND:
- [issue with affected collection]

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