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Managing Solr

BSecurity

Use when working with Solr — apache Solr collection management, core administration, query performance tuning, and schema analysis. Covers SolrCloud cluster health, shard states, replica placement, config sets, commit strategies, and cache hit ratios. Read this skill before any Solr operations.

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  • Added September 8, 2026
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  • cli
  • api

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Scanned September 8, 2026

npx -y skills add cloudthinker-ai/CloudSkills --skill managing-solr --agent claude-code

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SKILL.md
---
name: managing-solr
description: |
  Use when working with Solr — apache Solr collection management, core
  administration, query performance tuning, and schema analysis. Covers
  SolrCloud cluster health, shard states, replica placement, config sets, commit
  strategies, and cache hit ratios. Read this skill before any Solr operations.
connection_type: solr
preload: false
---

# Solr Management Skill

Monitor, analyze, and optimize Apache Solr instances and SolrCloud clusters safely.

## MANDATORY: Discovery-First Pattern

**Always check cluster status and list collections before any query or config operations. Never assume collection or field names.**

### Phase 1: Discovery

```bash
#!/bin/bash

SOLR_URL="${SOLR_URL:-http://localhost:8983/solr}"

echo "=== System Info ==="
curl -s "$SOLR_URL/admin/info/system?wt=json" | python3 -c "
import sys, json
d = json.load(sys.stdin)
print(f\"Solr Version: {d.get('lucene',{}).get('solr-spec-version','?')}\")
print(f\"JVM: {d.get('jvm',{}).get('version','?')}\")
print(f\"Uptime: {d.get('jvm',{}).get('jmx',{}).get('upTimeMS',0)//86400000}d\")
" 2>/dev/null

echo ""
echo "=== Collections ==="
curl -s "$SOLR_URL/admin/collections?action=LIST&wt=json" | python3 -c "
import sys, json
data = json.load(sys.stdin)
for c in data.get('collections', []):
    print(f\"  {c}\")
" 2>/dev/null

echo ""
echo "=== Cluster Status ==="
curl -s "$SOLR_URL/admin/collections?action=CLUSTERSTATUS&wt=json" | python3 -c "
import sys, json
data = json.load(sys.stdin)
cluster = data.get('cluster', {})
live = cluster.get('live_nodes', [])
print(f\"Live nodes: {len(live)}\")
for name, coll in cluster.get('collections', {}).items():
    shards = coll.get('shards', {})
    print(f\"Collection: {name} | Shards: {len(shards)} | RF: {coll.get('replicationFactor','?')}\")
" 2>/dev/null

echo ""
echo "=== Core Status ==="
curl -s "$SOLR_URL/admin/cores?action=STATUS&wt=json" | python3 -c "
import sys, json
data = json.load(sys.stdin)
for name, core in data.get('status', {}).items():
    idx = core.get('index', {})
    print(f\"Core: {name} | Docs: {idx.get('numDocs',0)} | Size: {idx.get('sizeInBytes',0)//1048576}MB\")
" 2>/dev/null
```

**Phase 1 outputs:** Solr version, collection list, cluster topology, core doc counts and sizes.

### Phase 2: Analysis

```bash
#!/bin/bash

SOLR_URL="${SOLR_URL:-http://localhost:8983/solr}"
COLLECTION="${1:-my_collection}"

echo "=== Schema Fields for $COLLECTION ==="
curl -s "$SOLR_URL/$COLLECTION/schema/fields?wt=json" | python3 -c "
import sys, json
for f in json.load(sys.stdin).get('fields', []):
    print(f\"  {f['name']}: {f.get('type','?')} indexed={f.get('indexed','?')} stored={f.get('stored','?')}\")
" 2>/dev/null | head -20

echo ""
echo "=== Cache Stats ==="
curl -s "$SOLR_URL/$COLLECTION/admin/mbeans?cat=CACHE&stats=true&wt=json" | python3 -c "
import sys, json
data = json.load(sys.stdin)
beans = data.get('solr-mbeans', [])
i = 0
while i < len(beans)-1:
    if isinstance(beans[i+1], dict):
        for name, info in beans[i+1].items():
            stats = info.get('stats', {})
            if stats:
                print(f\"{name}: hits={stats.get('hits','?')} lookups={stats.get('lookups','?')} hitratio={stats.get('hitratio','?')}\")
    i += 2
" 2>/dev/null

echo ""
echo "=== Query Handler Stats ==="
curl -s "$SOLR_URL/$COLLECTION/admin/mbeans?cat=QUERYHANDLER&stats=true&wt=json" | python3 -c "
import sys, json
data = json.load(sys.stdin)
beans = data.get('solr-mbeans', [])
i = 0
while i < len(beans)-1:
    if isinstance(beans[i+1], dict):
        for name, info in beans[i+1].items():
            stats = info.get('stats', {})
            if stats and stats.get('requests',0) > 0:
                print(f\"{name}: requests={stats.get('requests')} avgTime={stats.get('avgTimePerRequest','?')}ms errors={stats.get('errors',0)}\")
    i += 2
" 2>/dev/null | head -10
```

## Output Format

```
SOLR ANALYSIS
=============
Version: [version] | Mode: [standalone/SolrCloud]
Collections: [count] | Live Nodes: [count]

ISSUES FOUND:
- [issue with affected collection/core]

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 |

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