Cloudflare GraphQL Analytics for zone traffic, firewall events, Workers metrics, and schema exploration. Use when querying Cloudflare analytics data or exploring the GraphQL API.
日本語の概要は準備中です。原文の説明を表示しています。
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.
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
Monitor, analyze, and optimize Chroma vector database instances safely.
Always check server health and list collections before any query operations. Never assume collection names or embedding dimensions.
#!/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: $count documents"
done
Phase 1 outputs: Server health, version, collection list with doc counts and distance metrics.
#!/bin/bash
CHROMA_URL="${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
CHROMA ANALYSIS
===============
Server: [healthy/unhealthy] | Version: [version]
Collections: [count] | Total Documents: [count]
ISSUES FOUND:
- [issue with affected collection]
RECOMMENDATIONS:
- [actionable recommendation]
--help output.| 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 |
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Cloudflare GraphQL Analytics for zone traffic, firewall events, Workers metrics, and schema exploration. Use when querying Cloudflare analytics data or exploring the GraphQL API.
日本語の概要は準備中です。原文の説明を表示しています。
Use when working with Alloydb — google AlloyDB instance analysis, query insights, columnar engine optimization, maintenance windows, and cluster health.
日本語の概要は準備中です。原文の説明を表示しています。
Use when working with Aqua — aqua Security platform analysis. Covers container runtime protection, image assurance policies, compliance frameworks, vulnerability management, workload protection, and registry scanning. Use when analyzing container security posture, reviewing image compliance, investigating runtime alerts, or auditing security policies.
日本語の概要は準備中です。原文の説明を表示しています。
Use when working with Bigquery — google BigQuery job analysis, slot utilization, cost analysis, dataset management, and query optimization.
日本語の概要は準備中です。原文の説明を表示しています。
Use when working with Cassandra — apache Cassandra keyspace analysis, compaction strategies, repair status, nodetool operations, and cluster health monitoring.
日本語の概要は準備中です。原文の説明を表示しています。
Use when working with Checkov — checkov infrastructure-as-code security scanning. Covers Terraform, CloudFormation, Kubernetes, and Dockerfile scanning, policy management, custom checks, compliance frameworks, and suppression management. Use when scanning IaC for security misconfigurations, evaluating compliance, managing custom policies, or reviewing scan results.
日本語の概要は準備中です。原文の説明を表示しています。