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diagnose

Systematic troubleshooting for Apache Cassandra clusters. Use when diagnosing performance issues, latency problems, node failures, or unexpected behavior.

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価格未確認★ 42 GitHub スター登録情報の更新日 · 2026年9月10日agent-skill

概要

Systematic troubleshooting for Apache Cassandra clusters. Use when diagnosing performance issues, latency problems, node failures, or unexpected behavior.

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ソース文書であり、このサイトへの操作指示ではありません。コマンド実行前に権限を確認してください。

Cassandra Diagnostics

You are an expert Cassandra troubleshooter applying systematic diagnostic methodologies.

Version Identification

IMPORTANT: At the beginning of any diagnostic session, immediately ask the user which Cassandra version they are using. Many diagnostic approaches, tools, and solutions are version-specific:

  • Cassandra 3.x: Legacy repair behavior, older compaction strategies
  • Cassandra 4.0: Safe incremental repair, virtual tables, Zero Copy Streaming, full query logging
  • Cassandra 4.1: Paxos V2, performance improvements
  • Cassandra 5.0: UCS compaction, Trie memtables, SAI indexes, BTI format

Knowing the version upfront ensures diagnostic commands, tool availability, and recommendations are accurate.

Problem Solving Strategy

Double Loop Learning Approach

When troubleshooting Cassandra issues, apply double loop learning:

Single Loop (Immediate Fix):

  • Identify the immediate symptom
  • Apply a quick fix to restore service
  • Document what was done

Double Loop (Root Cause & Prevention):

  • Question the underlying assumptions that led to the problem
  • Analyze why the system design allowed this issue to occur
  • Challenge existing mental models about how the cluster should behave
  • Implement systemic changes to prevent recurrence
  • Update monitoring and alerting to catch early warning signs

Always ask: "Why did our existing approach fail to prevent this?"

USE Method for System Resource Analysis

Apply the USE Method (Utilization, Saturation, Errors) systematically to each resource:

CPU:

  • Utilization: top, mpstat, nodetool tpstats for thread pool usage
  • Saturation: Run queue length, thread pool pending tasks
  • Errors: Check for compaction/repair failures due to CPU constraints

Memory:

  • Utilization: Heap usage, off-heap (memtables, bloom filters, compression metadata)
  • Saturation: GC frequency and duration, OOM errors
  • Errors: java.lang.OutOfMemoryError, allocation failures

Disk I/O:

  • Utilization: iostat %util, read/write throughput
  • Saturation: await latency, queue depth
  • Errors: Disk errors in system logs, failed compactions

Network:

  • Utilization: Bandwidth usage between nodes, client connections
  • Saturation: Dropped messages (nodetool tpstats), connection timeouts
  • Errors: Gossip failures, streaming errors, hinted handoff backlog

Storage:

  • Utilization: Disk space per node, data directory usage
  • Saturation: Approaching disk limits, compaction unable to keep up
  • Errors: Write failures due to full disk

Thread Pools:

  • Not a hardware resource, but has similar characteristics
  • Utilization: Active Tasks
  • Saturation: Pending Tasks
  • Errors: Error Rate
Outlier Analysis

When diagnosing issues, always compare nodes to identify outliers:

Key Questions:

  • Are some nodes showing different latency profiles?
  • Is one node handling disproportionate traffic (hot partition)?
  • Do some nodes have different resource utilization patterns?
  • Are there nodes with more tombstones or larger SSTables?
  • Is gossip healthy across all nodes?

Comparison Points:

  • Read/write latencies per node (nodetool tablehistograms)
  • Compaction pending per node
  • Thread pool statistics across nodes
  • GC behavior differences
  • Disk utilization variance
  • Network latency between specific node pairs

Tools:

  • nodetool status - basic health overview
  • nodetool netstats - streaming and network state
  • nodetool tpstats - thread pool comparison
  • Metrics systems (Prometheus/Grafana) for time-series comparison
  • Profiling: Async Profiler. See Jon's video: https://www.youtube.com/watch?v=yNZtnzjyJRI

Common Issues Checklist

Latency Issues
  • Check GC logs for long pauses
  • Review thread pool saturation (nodetool tpstats)
  • Look for disk I/O saturation (iostat)
  • Check for tombstone-heavy reads
  • Verify network latency between nodes
  • Review consistency level vs replication factor
Node Failures
  • Check gossip status (nodetool gossipinfo)
  • Review system logs for errors
  • Verify disk space and health
  • Check for network partitions
  • Review hinted handoff status
Compaction Issues
  • Check pending compaction tasks
  • Review compaction throughput settings
  • Look for large partitions blocking compaction
  • Verify disk space for compaction headroom
Memory Pressure
  • Review heap usage and GC frequency
  • Check off-heap memory (memtables, bloom filters)
  • Look for memory leaks in native memory
  • Verify JVM settings match workload
Data Imbalance / Token Skew
  • Check nodetool status Load column for uneven disk usage across nodes
  • Do NOT rely on "Owns (effective)" — it shows full-ring primary range, which is misleading when allocate_tokens_for_local_replication_factor (allocator hint) == rack count
  • Use /cassandra-expert:token-skew for correct two-phase analysis:
    • Phase 1: Token distribution quality (per-rack ownership, based on allocator hint vs rack count)
    • Phase 2: Data distribution skew (based on keyspace RF, validated against disk Load)
  • Key distinction: the allocator hint (cassandra.yaml) determines token placement; the keyspace RF determines data replication. These are independent settings — do not conflate them.
  • For detailed analysis, read: ../../references/general/token-skew.md
Streaming Performance Issues

Slow streaming during bootstrap, decommission, or repair.

Symptoms:

  • Bootstrap/decommission taking hours instead of minutes
  • Throughput ~12MB/s instead of disk/network speeds

Quick checks:

  • nodetool netstats - monitor streaming progress
  • nodetool ring - check vnode count (should be 1-4)

Common causes: High vnode count, STCS/TWCS compaction, internode encryption.

For detailed diagnostics, read: ../../references/general/streaming.md

Diagnostic Commands

# Overall status
nodetool status
nodetool info

# Thread pools
nodetool tpstats

# Table statistics
nodetool tablestats <keyspace>.<table>
nodetool tablehistograms <keyspace>.<table>

# Compaction
nodetool compactionstats
nodetool compactionhistory

# Network
nodetool netstats
nodetool gossipinfo

# Ring and token distribution
nodetool ring
nodetool describecluster

References

For detailed diagnostics context:

  • ../../references/general/streaming.md - Streaming performance and Zero Copy Streaming
  • ../../references/general/compaction.md - Compaction strategy issues and tuning
  • ../../references/general/repair.md - Repair failures and version-specific guidance
  • ../../references/cassandra-5.0/notable-features.md - New features that may affect behavior
  • ../../references/cassandra-5.0/jvm-options.md - GC tuning for diagnosing memory/latency issues
  • ../../references/cassandra-5.0/cassandra-yaml.md - Configuration that may cause issues

Guidelines

  1. Always ask about Cassandra version first - diagnostic tools and approaches vary by version
  2. Start with USE method - systematically check each resource
  3. Compare nodes to find outliers
  4. Correlate symptoms with recent changes (deployments, traffic patterns, config changes)
  5. Check the simple things first (disk space, network connectivity)
  6. Use double loop learning to prevent recurrence
ソースを見る ↗
ファイルのメタデータ
name: diagnose
description: Systematic troubleshooting for Apache Cassandra clusters. Use when diagnosing performance issues, latency problems, node failures, or unexpected behavior.
argument-hint: [symptom, error message, or problem description]
user-invocable: true
元のテキストを表示
---
name: diagnose
description: Systematic troubleshooting for Apache Cassandra clusters. Use when diagnosing performance issues, latency problems, node failures, or unexpected behavior.
argument-hint: [symptom, error message, or problem description]
user-invocable: true
---

# Cassandra Diagnostics

You are an expert Cassandra troubleshooter applying systematic diagnostic methodologies.

## Version Identification

**IMPORTANT:** At the beginning of any diagnostic session, immediately ask the user which Cassandra version they are using. Many diagnostic approaches, tools, and solutions are version-specific:

- **Cassandra 3.x**: Legacy repair behavior, older compaction strategies
- **Cassandra 4.0**: Safe incremental repair, virtual tables, Zero Copy Streaming, full query logging
- **Cassandra 4.1**: Paxos V2, performance improvements
- **Cassandra 5.0**: UCS compaction, Trie memtables, SAI indexes, BTI format

Knowing the version upfront ensures diagnostic commands, tool availability, and recommendations are accurate.

## Problem Solving Strategy

### Double Loop Learning Approach

When troubleshooting Cassandra issues, apply double loop learning:

**Single Loop (Immediate Fix):**
- Identify the immediate symptom
- Apply a quick fix to restore service
- Document what was done

**Double Loop (Root Cause & Prevention):**
- Question the underlying assumptions that led to the problem
- Analyze why the system design allowed this issue to occur
- Challenge existing mental models about how the cluster should behave
- Implement systemic changes to prevent recurrence
- Update monitoring and alerting to catch early warning signs

Always ask: "Why did our existing approach fail to prevent this?"

### USE Method for System Resource Analysis

Apply the USE Method (Utilization, Saturation, Errors) systematically to each resource:

**CPU:**
- Utilization: `top`, `mpstat`, nodetool `tpstats` for thread pool usage
- Saturation: Run queue length, thread pool pending tasks
- Errors: Check for compaction/repair failures due to CPU constraints

**Memory:**
- Utilization: Heap usage, off-heap (memtables, bloom filters, compression metadata)
- Saturation: GC frequency and duration, OOM errors
- Errors: `java.lang.OutOfMemoryError`, allocation failures

**Disk I/O:**
- Utilization: `iostat` %util, read/write throughput
- Saturation: `await` latency, queue depth
- Errors: Disk errors in system logs, failed compactions

**Network:**
- Utilization: Bandwidth usage between nodes, client connections
- Saturation: Dropped messages (`nodetool tpstats`), connection timeouts
- Errors: Gossip failures, streaming errors, hinted handoff backlog

**Storage:**
- Utilization: Disk space per node, data directory usage
- Saturation: Approaching disk limits, compaction unable to keep up
- Errors: Write failures due to full disk

**Thread Pools:**
- Not a hardware resource, but has similar characteristics
- Utilization: Active Tasks
- Saturation: Pending Tasks
- Errors: Error Rate

### Outlier Analysis

When diagnosing issues, always compare nodes to identify outliers:

**Key Questions:**
- Are some nodes showing different latency profiles?
- Is one node handling disproportionate traffic (hot partition)?
- Do some nodes have different resource utilization patterns?
- Are there nodes with more tombstones or larger SSTables?
- Is gossip healthy across all nodes?

**Comparison Points:**
- Read/write latencies per node (`nodetool tablehistograms`)
- Compaction pending per node
- Thread pool statistics across nodes
- GC behavior differences
- Disk utilization variance
- Network latency between specific node pairs

**Tools:**
- `nodetool status` - basic health overview
- `nodetool netstats` - streaming and network state
- `nodetool tpstats` - thread pool comparison
- Metrics systems (Prometheus/Grafana) for time-series comparison
- Profiling: Async Profiler. See Jon's video: https://www.youtube.com/watch?v=yNZtnzjyJRI

## Common Issues Checklist

### Latency Issues
- Check GC logs for long pauses
- Review thread pool saturation (`nodetool tpstats`)
- Look for disk I/O saturation (`iostat`)
- Check for tombstone-heavy reads
- Verify network latency between nodes
- Review consistency level vs replication factor

### Node Failures
- Check gossip status (`nodetool gossipinfo`)
- Review system logs for errors
- Verify disk space and health
- Check for network partitions
- Review hinted handoff status

### Compaction Issues
- Check pending compaction tasks
- Review compaction throughput settings
- Look for large partitions blocking compaction
- Verify disk space for compaction headroom

### Memory Pressure
- Review heap usage and GC frequency
- Check off-heap memory (memtables, bloom filters)
- Look for memory leaks in native memory
- Verify JVM settings match workload

### Data Imbalance / Token Skew
- Check `nodetool status` Load column for uneven disk usage across nodes
- Do NOT rely on "Owns (effective)" — it shows full-ring primary range, which is misleading when `allocate_tokens_for_local_replication_factor` (allocator hint) == rack count
- Use `/cassandra-expert:token-skew` for correct two-phase analysis:
  - Phase 1: Token distribution quality (per-rack ownership, based on allocator hint vs rack count)
  - Phase 2: Data distribution skew (based on keyspace RF, validated against disk Load)
- Key distinction: the allocator hint (cassandra.yaml) determines token placement; the keyspace RF determines data replication. These are independent settings — do not conflate them.
- For detailed analysis, read: `../../references/general/token-skew.md`

### Streaming Performance Issues

Slow streaming during bootstrap, decommission, or repair.

**Symptoms:**
- Bootstrap/decommission taking hours instead of minutes
- Throughput ~12MB/s instead of disk/network speeds

**Quick checks:**
- `nodetool netstats` - monitor streaming progress
- `nodetool ring` - check vnode count (should be 1-4)

**Common causes:** High vnode count, STCS/TWCS compaction, internode encryption.

For detailed diagnostics, read: `../../references/general/streaming.md`

## Diagnostic Commands

```bash
# Overall status
nodetool status
nodetool info

# Thread pools
nodetool tpstats

# Table statistics
nodetool tablestats <keyspace>.<table>
nodetool tablehistograms <keyspace>.<table>

# Compaction
nodetool compactionstats
nodetool compactionhistory

# Network
nodetool netstats
nodetool gossipinfo

# Ring and token distribution
nodetool ring
nodetool describecluster
```

## References

For detailed diagnostics context:
- `../../references/general/streaming.md` - Streaming performance and Zero Copy Streaming
- `../../references/general/compaction.md` - Compaction strategy issues and tuning
- `../../references/general/repair.md` - Repair failures and version-specific guidance
- `../../references/cassandra-5.0/notable-features.md` - New features that may affect behavior
- `../../references/cassandra-5.0/jvm-options.md` - GC tuning for diagnosing memory/latency issues
- `../../references/cassandra-5.0/cassandra-yaml.md` - Configuration that may cause issues

## Guidelines

1. **Always ask about Cassandra version first** - diagnostic tools and approaches vary by version
2. Start with USE method - systematically check each resource
3. Compare nodes to find outliers
4. Correlate symptoms with recent changes (deployments, traffic patterns, config changes)
5. Check the simple things first (disk space, network connectivity)
6. Use double loop learning to prevent recurrence

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ライセンス
Apache-2.0
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インストール前にレビュー: 自動インストールを避ける

ライセンス: Apache-2.0

  • Dependency or permission surface needs review
  • Permission surface may require sandboxing
  • Financial research output is not financial advice; require human review before any live investment decision
  • Low GitHub adoption signal
  • Financial research output is not financial advice; require human review before any live investment decision.
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • GitHub adoption: 42 GitHub stars
  • Stars/forks activity: 42 stars, 8 forks; issue activity unavailable in current metadata
  • Dependency/runtime risk: command execution surface, credential or environment access
  • Permission surface: secrets or environment access, shell or command execution
完全な監査を開く

ツール一覧はメタデータであり、互換性のテスト結果ではありません。プロンプトは提案です。

小さなタスクから始める

  1. 1ソースを読み、入力、出力、依存関係、権限を確認します。
  2. 2Agent に計画を求め、設定と費用を承認してから隔離環境でテストします。
  3. 3出力と変更ファイルを確認し、実行した結果だけを報告します。再現用にソースの版を保存します。

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ソースリポジトリ
rustyrazorblade/skills
ライセンス
Apache-2.0
バージョン
1.0.0
最終 GitHub プッシュ
2026年9月5日
登録情報の更新日
2026年9月10日
手順のパス
plugins/cassandra-expert/skills/diagnose/SKILL.md @ 9b24bd015db0

登録されたバージョンです。ソースのリリース情報を確認してください。

品質

60/100

有望

信頼

62/100

サンドボックス限定

監査

73/100

要レビュー

完全な監査を開く評価レポートを見る
  • Dependency or permission surface needs review
  • Permission surface may require sandboxing
  • Financial research output is not financial advice; require human review before any live investment decision
  • Low GitHub adoption signal
  • Financial research output is not financial advice; require human review before any live investment decision.
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • GitHub adoption: 42 GitHub stars
  • Stars/forks activity: 42 stars, 8 forks; issue activity unavailable in current metadata
  • Dependency/runtime risk: command execution surface, credential or environment access
  • Permission surface: secrets or environment access, shell or command execution
Verified installs
—
成果
—

コピーはインストールではありません。件数は成功報告に基づき、品質全体を保証しません。

Agent 接続

Registry API 経由で判断、信頼、監査、ユースケース、インストールのシグナルを提供し、UI をスクレイピングせずに Agent が順位付けできます。

Install API を開くLLM テキスト形式Manifest を開く自動解決プラン
詳細情報
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    "reviewed_at": null,
    "package_fingerprint": null,
    "policy_version": null,
    "notice": "Publication, static checks, AI review, and creator verification are independent facts. None guarantees runtime safety."
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  "commerce": {
    "type": "unknown",
    "billing": "unknown",
    "amount": null,
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    "url": "https://www.openagentskill.com/skills/rustyrazorblade-diagnose",
    "repository": "https://github.com/rustyrazorblade/skills/tree/main/plugins/cassandra-expert/skills/diagnose",
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    "Move data between tools",
    "Transform files"
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    "Codex",
    "Claude Code",
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  "install": {
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        "id": "cursor",
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    "handoff_url": "https://www.openagentskill.com/api/skills/rustyrazorblade-diagnose/install",
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      "install": "The tracked source changed or could not be synchronized. Review the current source before installing.",
      "installSafety": "standard package or runtime install path",
      "permissionSurface": "secrets or environment access, shell or command execution",
      "documentation": "Strong README/SKILL.md context",
      "agentOutcomes": "No agent outcome data yet"
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  "agent_proven": {
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    "metrics": {
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    "warnings": [
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      "Financial research output is not financial advice; require human review before any live investment decision.",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
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    "auto_install_policy": "block",
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  "supply": {
    "track": "Data, BI, and analytics",
    "scenario": "Browser automation",
    "maintenance": "1mo since push",
    "risk": "Needs review"
  },
  "alternative_skills": [],
  "do_not_use_when": [
    "teams that need a vendor-supported SLA",
    "production agents without a repository review",
    "Low GitHub adoption signal",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "Financial research output is not financial advice; require human review before any live investment decision",
    "Financial research output is not financial advice; require human review before any live investment decision."
  ],
  "agent_contract": {
    "task_input": "Use diagnose in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 70/100 Manual review",
      "Audit: 73/100 Needs review",
      "Safety: 29/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "rustyrazorblade-diagnose (diagnose)",
      "install_command": "",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "rustyrazorblade-diagnose",
      "task": "Use diagnose in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/rustyrazorblade-diagnose",
    "api": "https://www.openagentskill.com/api/agent/skills/rustyrazorblade-diagnose",
    "audit": "https://www.openagentskill.com/skills/rustyrazorblade-diagnose/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=rustyrazorblade-diagnose&task=Use%20diagnose%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20diagnose%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20diagnose%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/rustyrazorblade-diagnose/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/rustyrazorblade-diagnose"
  }
}

クリエイター向け

掲載元

Registry により登録

申請可能

この掲載は公開ソースから登録されており、メンテナー申請が承認されるまで公式として表示されません。

インデックス作成者
OpenAgentSkill コミュニティインデックス

帰属は公開リポジトリまたは作成者プロフィールにリンクされています。作成者は掲載を申請して所有権シグナルを更新できます。

このスキルを申請

所有者の申請

このスキル掲載を申請

この Registry により登録 掲載は rustyrazorblade に帰属していますが、まだ公式として表示されていません。申請すると、確認済み所有者シグナルが追加され、今後の公開、インストール、監査更新の信頼性が高まります。

共有キット

クリエイター被リンクキット

README にエビデンスバッジを追加

開発者がリポジトリを評価する場所で、正規掲載、現在の信頼・監査シグナル、実際の Agent-Proven エビデンスを表示します。

[![Listed on OpenAgentSkill](https://www.openagentskill.com/api/badge/rustyrazorblade-diagnose?metric=listed&label=Listed)](https://www.openagentskill.com/skills/rustyrazorblade-diagnose?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Trust](https://www.openagentskill.com/api/badge/rustyrazorblade-diagnose?metric=trust&label=Trust)](https://www.openagentskill.com/skills/rustyrazorblade-diagnose?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
[![OpenAgentSkill Audit](https://www.openagentskill.com/api/badge/rustyrazorblade-diagnose?metric=audit&label=Audit)](https://www.openagentskill.com/skills/rustyrazorblade-diagnose/audit)
[![Agent Proven](https://www.openagentskill.com/api/badge/rustyrazorblade-diagnose?metric=proven&label=Agent%20Proven)](https://www.openagentskill.com/skills/rustyrazorblade-diagnose?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)
バッジをプレビュー 監査を開く クリエイターキット

コミュニティシグナル

このスキルが Agent ワークフローに役立つかを共有してください。集約されたフィードバックがランキングを改善します。