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SkillAtlasSkill 详情
clickhouse-performance-tuning
A model-agnostic agent-skills platform.
审核状态：已审核Quality 72Security 60
项目 README
来源文件：README.md
Tons of Skills
A model-agnostic agent-skills platform. The canonical layer is harness-free by construction; Claude Code is currently the verified-native harness. Other harnesses remain engineering candidates until their native-path integration is verified; source research alone is never presented as public support.
Version semantics: the release badge is this marketplace's display version. npm packages, including the
ccpiCLI and publishable plugins, retain their own package versions; they are intentionally not expected to equal the display version. The version-surface checker governs the display surfaces without rewriting package semver.
Install
Inside Claude Code, one command installs the whole marketplace:
/plugin marketplace add jeremylongshore/claude-code-plugins
Or use the CLI:
pnpm add -g @intentsolutionsio/ccpi
ccpi install devops-automation-pack
Browse the marketplace · Explore plugins · Download bundles
Killer Skill of the Week — no-ai-slop by Peter Yang
Strip AI slop from any draft — named-pattern edits that keep the writer's real voice
no-ai-slop does two jobs and refuses to fake a third. In Edit mode it makes the minimum effective edit — cutting throat-clearing, weak verbs, and abstract nouns while deliberately preserving the writer's cadence, bluntness, humor, and honest admissions, so a rough draft still sounds like the same person afterward. In Detect mode it names each AI-slop pattern it finds, quotes the offending line, and gives the fix in a few words — and pointedly does NOT score the draft or guess whether an AI wrote it. That restraint is the whole point: AI detectors guess; named patterns are evidence the reader can check. MIT-licensed, single focused skill, actively maintained by Peter Yang.
"AI detectors guess. Named patterns are evidence the user can check." — Peter Yang
Grade: A | Week of July 22, 2026 (W30) | View on GitHub
Previous picks: tonone, mnemos, databricks-pack, kobiton-automate, skyvern, code-cleanup, web-analytics, token-optimizer, executive-assistant-skills, skill-creator, cursor-pack, crypto-portfolio-tracker. See all at tonsofskills.com.
Scale, labeled
Every number below names the cohort it counts and the command that reproduces it — an unlabeled count is how a corpus ends up with five contradictory answers to "how many skills."
| Count | Cohort | Reproduce with |
|---|---|---|
| 442 | catalog plugins (catalog-entry cohort) | node scripts/generate-readme-toc.mjs over marketplace.extended.json |
| 3,067 | marketplace-visible skills (distinct) | node -e "import('./scripts/corpus-resolver.mjs').then(m=>console.log(m.resolveCorpus('marketplace-visible').length))" |
| 347 | agent definitions in plugins | git ls-files 'plugins/**' | grep '/agents/.*\.md' |
| 19 | plugin categories | ls -d plugins/*/ |
📦 Live npm Downloads
Across 396 published packages in the claude-code-plugins namespace. Updated daily by GitHub Actions.
| Window | All packages | Established (>30d) |
|---|---|---|
| Last 24 hours | 962 | 962 |
| Last 7 days | 2,920 | 2,916 |
| Last 30 days | 12,868 | 12,779 |
"Established" excludes packages first published within the last 30 days, so a bulk-publish event doesn't dominate the headline.
Top 10 by last 30 days:
Last refreshed 2026-08-19T03:03:05.709Z.
Ways in
Five real questions, five doors — each resolves to a live, generated surface, never a hand-maintained list:
- By category — the table below, regenerated from the catalog on every sync.
- By plugin — tonsofskills.com/explore, the full browsable catalog.
- By skill — tonsofskills.com/skills, searchable across the whole corpus.
- By job to be done — tonsofskills.com/cowork, curated bundles as one-click downloads.
- By certification tier — the Certification section below, rendered from the live report.
Browse by category
The 19 categories below link into the live marketplace. Plugin counts are the catalog-entry cohort — regenerated from marketplace.extended.json by this generator; the catalog itself lives on tonsofskills.com, never in this file (§ 6A of the platform blueprint).
| Category | Plugins | |
|---|---|---|
| 🤖 | AI & Machine Learning | 36 |
| 🎭 | AI Agents & Agency | 10 |
| 🔌 | API Development | 26 |
| 💼 | Business Tools | 6 |
| 👥 | Community | 21 |
| ₿ | Crypto & Web3 | 27 |
| 💾 | Database | 26 |
| 🎨 | Design | 2 |
| 🔧 | DevOps & Infrastructure | 36 |
| 📚 | Examples & Templates | 5 |
| 🧩 | MCP Servers | 16 |
| 📦 | Packages | 5 |
| ⚡ | Performance | 25 |
| ✅ | Productivity | 30 |
| 🎁 | SaaS Skill Packs | 106 |
| 🔐 | Security | 27 |
| ✨ | Skill Enhancers | 9 |
| 🧪 | Testing | 28 |
| 📁 | Analytics | 1 |
What the classes mean
Four artifact classes live in this repository, distinguished on sight and never blurred — provenance is a truth requirement here, not a UX nicety:
| Class | What it is | How the reader can tell |
|---|---|---|
| Canonical skill | First-party, harness-free, the source of truth | No .source.json in its plugin directory |
| Generated adapter | A thin, machine-produced harness projection | Lives under a generated path with a "generated — do not edit" header |
| First-party package | An Intent Solutions distribution (npm, cowork zip) | @intentsolutionsio scope, IS-authored license |
| Upstream mirror | Somebody else's work, hosted mirror-by-default | .source.json present — upstream author, license, and pinned commit recorded |
Certification
Not yet certified. The certification program (tiers T0–T4 with retained, hash-matched evidence) is a later epic of the platform blueprint; until its report exists, no artifact on this surface claims a tier. This line is rendered from the absence of certification-report.json — honestly, not cosmetically.
Contribute
Start with the contribution guide, then the intake and review standards every submission passes through:
- Contribution requirements — including the AI-assistance disclosure expectation.
- Skill submission intake standard — the tiered document matrix new plugins ship with.
- External-PR review standard — how maintainers triage and what gets a submission merged.
Governance
- STANDARDS.md — the public spec posture and the canonical-documents index (one owner per fact class).
- The platform master blueprint — CI gates, release, docs governance, and this README's own landing contract.
- GOVERNANCE.md · SECURITY.md · LICENSE
Provenance
External plugins are hosted mirror-by-default: the contributor's repository stays the source of truth, every mirrored source is pinned in a content lockfile, and upstream credit — author, license, resolved commit — is recorded in the mirror itself. Improvements flow by upstreaming to the author's repository, never by silently editing the mirror. The full decision record is the external-sync model.
License
MIT for the repository scaffolding and first-party tooling; each plugin carries its own license in its manifest, and mirrored plugins keep their upstream license verbatim.
其他
高风险
- 来源需自行核对维护者身份。
- 未检测到明显脚本安装指令。
- 可能需要外部 token、网络权限或第三方服务。
- 存在潜在风险命令，请谨慎安装。
- 扫描发现：2 条。
Codex — Git Clone 安装
- 安装前请先查看来源仓库和风险报告。
- 克隆仓库：git clone https://github.com/jeremylongshore/tons-of-skills-marketplace.git
- 将 "skills/.curated/clickhouse-performance-tuning" 文件夹复制到 Codex 的 skills 目录中。
- 重启 Codex 让新的 skill 生效。
Codex — 手动复制安装
- 安装前请先查看来源仓库和风险报告。
- 从源仓库下载 SKILL.md 及相关文件。
- 在 Codex 的 skills 目录中创建新文件夹。
- 将所有 skill 文件复制到新文件夹中。
- 重启 Codex 让新的 skill 生效。
Claude Code — Git Clone 安装
- 安装前请先查看来源仓库和风险报告。
- 克隆仓库：git clone https://github.com/jeremylongshore/tons-of-skills-marketplace.git
- 将 "skills/.curated/clickhouse-performance-tuning" 文件夹复制到 Claude Code 的 skills 目录中。
- 重启 Claude Code 让新的 skill 生效。
Claude Code — 手动复制安装
- 安装前请先查看来源仓库和风险报告。
- 从源仓库下载 SKILL.md 及相关文件。
- 在 Claude Code 的 skills 目录中创建新文件夹。
- 将所有 skill 文件复制到新文件夹中。
- 重启 Claude Code 让新的 skill 生效。
Cursor — Git Clone 安装
- 安装前请先查看来源仓库和风险报告。
- 克隆仓库：git clone https://github.com/jeremylongshore/tons-of-skills-marketplace.git
- 将 "skills/.curated/clickhouse-performance-tuning" 文件夹复制到 Cursor 的 skills 目录中。
- 重启 Cursor 让新的 skill 生效。
Cursor — 手动复制安装
- 安装前请先查看来源仓库和风险报告。
- 从源仓库下载 SKILL.md 及相关文件。
- 在 Cursor 的 skills 目录中创建新文件夹。
- 将所有 skill 文件复制到新文件夹中。
- 重启 Cursor 让新的 skill 生效。
GitHub Copilot — Git Clone 安装
- 安装前请先查看来源仓库和风险报告。
- 克隆仓库：git clone https://github.com/jeremylongshore/tons-of-skills-marketplace.git
- 将 "skills/.curated/clickhouse-performance-tuning" 文件夹复制到 GitHub Copilot 的 skills 目录中。
- 重启 GitHub Copilot 让新的 skill 生效。
GitHub Copilot — 手动复制安装
- 安装前请先查看来源仓库和风险报告。
- 从源仓库下载 SKILL.md 及相关文件。
- 在 GitHub Copilot 的 skills 目录中创建新文件夹。
- 将所有 skill 文件复制到新文件夹中。
- 重启 GitHub Copilot 让新的 skill 生效。
Windsurf — Git Clone 安装
- 安装前请先查看来源仓库和风险报告。
- 克隆仓库：git clone https://github.com/jeremylongshore/tons-of-skills-marketplace.git
- 将 "skills/.curated/clickhouse-performance-tuning" 文件夹复制到 Windsurf 的 skills 目录中。
- 重启 Windsurf 让新的 skill 生效。
Windsurf — 手动复制安装
- 安装前请先查看来源仓库和风险报告。
- 从源仓库下载 SKILL.md 及相关文件。
- 在 Windsurf 的 skills 目录中创建新文件夹。
- 将所有 skill 文件复制到新文件夹中。
- 重启 Windsurf 让新的 skill 生效。
查看 SKILL.md 原文
name: clickhouse-performance-tuning
description: |
Optimize ClickHouse query performance with indexing, projections, settings
tuning, and query analysis using system tables.
Use when queries are slow, investigating performance bottlenecks, or tuning
ClickHouse server settings.
Trigger with "clickhouse performance", "optimize clickhouse query",
"clickhouse slow query", "clickhouse indexing", "clickhouse tuning",
"clickhouse projections".
allowed-tools: Read, Write, Edit
version: 1.7.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
tags:
- saas
- database
- analytics
- clickhouse
- olap
compatibility: Designed for Claude CodeClickHouse Performance Tuning
Overview
Diagnose and fix ClickHouse performance issues using query analysis, proper indexing,
projections, materialized views, and server settings tuning. Work top-down: measure
first with system.query_log, then apply the single highest-leverage fix (usually the
ORDER BY key), then re-measure to confirm.
Prerequisites
- ClickHouse tables with data (see
clickhouse-core-workflow-a) - Access to
system.query_logandsystem.parts
Instructions
The tuning workflow is seven independent steps. Diagnose first, then reach for the fix that matches the bottleneck. Each step's full SQL lives in references/implementation.md — start there for the complete, copy-paste commands.
- Diagnose slow queries — rank the last 24h of
system.query_logbyquery_duration_ms, then inspect a suspect query withEXPLAIN PLAN/EXPLAIN PIPELINE. - ORDER BY key optimization — the primary lever. Filtering on the ORDER BY prefix skips whole granules; a mismatched key forces a full scan.
- Data skipping indexes —
bloom_filterfor high-cardinality lookups,setfor low-cardinality columns,minmaxfor range filters on non-key columns. - Projections — automatic pre-aggregation ClickHouse picks transparently when a query matches the projection's shape.
- Server settings —
max_threads, external sort/group-by spill,async_insert, and friends, set per-query or per-session. - Materialized views — pre-aggregate on INSERT into an
AggregatingMergeTreeso dashboard reads hit milliseconds, not seconds. - Query patterns —
PREWHERE,LIMIT BY, and avoidingFINAL.
The essential first move — find the slowest queries:
SELECT event_time, query_duration_ms, read_rows, read_bytes,
substring(query, 1, 300) AS query_preview
FROM system.query_log
WHERE type = 'QueryFinish'
AND event_time >= now() - INTERVAL 24 HOUR
AND query_duration_ms > 1000 -- > 1 second
ORDER BY query_duration_ms DESC
LIMIT 20;
Output
Applying this workflow produces:
- A ranked list of the slowest queries with their
read_rows/read_bytescost. - One or more concrete schema/query changes: a corrected
ORDER BYkey, added data skipping indexes, a projection, a materialized view, or tuned session settings. - A before/after measurement from
system.query_logproving the change reducedread_rows,read_bytes,query_duration_ms, ormemory_usage.
Error Handling
| Issue | Indicator | Solution |
|---|---|---|
| Full table scan | read_rows = total rows | Fix ORDER BY to match filters |
| Memory exceeded | Error 241 | Add LIMIT, use streaming, increase limit |
| Slow GROUP BY | High read_bytes | Add materialized view or projection |
| Merge backlog | Parts > 300 | Reduce insert frequency, increase merge threads |
Examples
Worked before/after scenarios — full-scan → ORDER BY fix, slow GROUP BY → projection, confirming a skipping index fires, and the query-cost measurement query — are in references/examples.md. The core measurement, run right after any query you are tuning:
SELECT query_duration_ms, read_rows,
formatReadableSize(read_bytes) AS read_size,
formatReadableSize(memory_usage) AS memory
FROM system.query_log
WHERE query_id = currentQueryId() AND type = 'QueryFinish';
Resources
- references/implementation.md — full 7-step SQL walkthrough
- references/examples.md — worked before/after tuning examples
- Projections
- Data Skipping Indexes
- MergeTree Settings
Next Steps
For cost optimization, see clickhouse-cost-tuning.
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