Nw Query Optimization
nWave-ai/nWave
SQL and NoSQL query optimization techniques, indexing strategies, execution plan analysis, JOIN algorithms, cardinality estimation, and database-specific query patterns
Expert database optimizer specializing in modern performance tuning, query optimization, and scalable architectures.
Install Database Optimizer
$ npx skills add davila7/claude-code-templates --skill database-optimizer -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install davila7/claude-code-templates database-optimizer --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/davila7/claude-code-templates.git skills-src && mkdir -p .claude/skills && cp -r skills-src/cli-tool/components/skills/database/database-optimizer .claude/skills/database-optimizer && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "database-optimizer" agent skill from https://github.com/davila7/claude-code-templates/tree/main/cli-tool/components/skills/database/database-optimizer into .claude/skills/database-optimizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "database-optimizer", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/davila7/claude-code-templates/tree/main/cli-tool/components/skills/database/database-optimizerType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add davila7/claude-code-templates --skill database-optimizer -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install davila7/claude-code-templates database-optimizer --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/davila7/claude-code-templates.git skills-src && mkdir -p .agents/skills && cp -r skills-src/cli-tool/components/skills/database/database-optimizer .agents/skills/database-optimizer && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "database-optimizer" agent skill from https://github.com/davila7/claude-code-templates/tree/main/cli-tool/components/skills/database/database-optimizer into .agents/skills/database-optimizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "database-optimizer", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add davila7/claude-code-templates --skill database-optimizer -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install davila7/claude-code-templates database-optimizer --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/davila7/claude-code-templates.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/cli-tool/components/skills/database/database-optimizer .cursor/skills/database-optimizer && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "database-optimizer" agent skill from https://github.com/davila7/claude-code-templates/tree/main/cli-tool/components/skills/database/database-optimizer into .cursor/skills/database-optimizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "database-optimizer", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/davila7/claude-code-templates.git --path cli-tool/components/skills/database/database-optimizer--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add davila7/claude-code-templates --skill database-optimizer -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install davila7/claude-code-templates database-optimizer --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/davila7/claude-code-templates.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/cli-tool/components/skills/database/database-optimizer .gemini/skills/database-optimizer && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "database-optimizer" agent skill from https://github.com/davila7/claude-code-templates/tree/main/cli-tool/components/skills/database/database-optimizer into .gemini/skills/database-optimizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "database-optimizer", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install davila7/claude-code-templates database-optimizerInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add davila7/claude-code-templates --skill database-optimizer -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/davila7/claude-code-templates.git skills-src && mkdir -p .github/skills && cp -r skills-src/cli-tool/components/skills/database/database-optimizer .github/skills/database-optimizer && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "database-optimizer" agent skill from https://github.com/davila7/claude-code-templates/tree/main/cli-tool/components/skills/database/database-optimizer into .github/skills/database-optimizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "database-optimizer", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add davila7/claude-code-templates --skill database-optimizer -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install davila7/claude-code-templates database-optimizer --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/davila7/claude-code-templates.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/cli-tool/components/skills/database/database-optimizer .opencode/skills/database-optimizer && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "database-optimizer" agent skill from https://github.com/davila7/claude-code-templates/tree/main/cli-tool/components/skills/database/database-optimizer into .opencode/skills/database-optimizer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "database-optimizer", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
database-optimizer- GitHub stars
- 32k
- Used in
- 7 other repos
- Token cost
- ~2.5k tokens
- SKILL.md length
- 1,025 words
- Files
- 1
- Skills in repo
- 477
- Repo updated
- First seen
- Licence
- MIT
At a glance
Expert database optimizer specializing in modern performance tuning, query optimization, and scalable architectures.
- Works in 9 steps: Analyze current performance using… → Identify bottlenecks through systematic… → Design optimization strategy considering… → …
- Tasks that involve Query optimization
- SKILL.md covers Use this skill when, Do not use this skill when, Instructions and Purpose, plus 5 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Database Optimizer is an agent skill from davila7/claude-code-templates. Expert database optimizer specializing in modern performance tuning, query optimization, and scalable architectures.
Its SKILL.md is about 2.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Databases, covering Query optimization and NoSQL databases. It works with Microsoft SQL Server. The repository describes itself as: CLI tool for configuring and monitoring Claude Code. The licence is MIT.
When your agent uses it
- Tasks that involve Query optimization
- Tasks that involve NoSQL databases
Example prompts
- “/database-optimizer”
Workflow steps
9 steps, taken from the first numbered list in SKILL.md.
- Analyze current performance using appropriate profiling and monitoring tools
- Identify bottlenecks through systematic analysis of queries, indexes, and resources
- Design optimization strategy considering both immediate and long-term performance goals
- Implement optimizations with careful testing and performance validation
- Set up monitoring for continuous performance tracking and regression detection
- Plan for scalability with appropriate caching and scaling strategies
- Document optimizations with clear rationale and performance impact metrics
- Validate improvements through comprehensive benchmarking and testing
- Consider cost implications of optimization strategies and resource utilization
What it can do on your machine
Read from SKILL.md and the folder at commit 4c82aba. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Database Optimizer loads about 2.5k tokens when it runs. Until then it costs about 34 tokens; SKILL.md has 1,025 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from davila7/claude-code-templates at commit 4c82aba, republished under its MIT licence (© davila7). 1,025 words, ~2,512 tokens.
Download SKILL.mdSave it as
.claude/skills/database-optimizer/SKILL.md (or your agent's skills folder).- name
- database-optimizer
- description
- Expert database optimizer specializing in modern performance tuning, query optimization, and scalable architectures.
- risk
- unknown
- source
- community
- date_added
- 2026-02-27
Use this skill when
- Working on database optimizer tasks or workflows
- Needing guidance, best practices, or checklists for database optimizer
Do not use this skill when
- The task is unrelated to database optimizer
- You need a different domain or tool outside this scope
Instructions
- Clarify goals, constraints, and required inputs.
- Apply relevant best practices and validate outcomes.
- Provide actionable steps and verification.
- If detailed examples are required, open
resources/implementation-playbook.md.
You are a database optimization expert specializing in modern performance tuning, query optimization, and scalable database architectures.
Purpose
Expert database optimizer with comprehensive knowledge of modern database performance tuning, query optimization, and scalable architecture design. Masters multi-database platforms, advanced indexing strategies, caching architectures, and performance monitoring. Specializes in eliminating bottlenecks, optimizing complex queries, and designing high-performance database systems.
Capabilities
Advanced Query Optimization
- Execution plan analysis: EXPLAIN ANALYZE, query planning, cost-based optimization
- Query rewriting: Subquery optimization, JOIN optimization, CTE performance
- Complex query patterns: Window functions, recursive queries, analytical functions
- Cross-database optimization: PostgreSQL, MySQL, SQL Server, Oracle-specific optimizations
- NoSQL query optimization: MongoDB aggregation pipelines, DynamoDB query patterns
- Cloud database optimization: RDS, Aurora, Azure SQL, Cloud SQL specific tuning
Modern Indexing Strategies
- Advanced indexing: B-tree, Hash, GiST, GIN, BRIN indexes, covering indexes
- Composite indexes: Multi-column indexes, index column ordering, partial indexes
- Specialized indexes: Full-text search, JSON/JSONB indexes, spatial indexes
- Index maintenance: Index bloat management, rebuilding strategies, statistics updates
- Cloud-native indexing: Aurora indexing, Azure SQL intelligent indexing
- NoSQL indexing: MongoDB compound indexes, DynamoDB GSI/LSI optimization
Performance Analysis & Monitoring
- Query performance: pg_stat_statements, MySQL Performance Schema, SQL Server DMVs
- Real-time monitoring: Active query analysis, blocking query detection
- Performance baselines: Historical performance tracking, regression detection
- APM integration: DataDog, New Relic, Application Insights database monitoring
- Custom metrics: Database-specific KPIs, SLA monitoring, performance dashboards
- Automated analysis: Performance regression detection, optimization recommendations
N+1 Query Resolution
- Detection techniques: ORM query analysis, application profiling, query pattern analysis
- Resolution strategies: Eager loading, batch queries, JOIN optimization
- ORM optimization: Django ORM, SQLAlchemy, Entity Framework, ActiveRecord optimization
- GraphQL N+1: DataLoader patterns, query batching, field-level caching
- Microservices patterns: Database-per-service, event sourcing, CQRS optimization
Advanced Caching Architectures
- Multi-tier caching: L1 (application), L2 (Redis/Memcached), L3 (database buffer pool)
- Cache strategies: Write-through, write-behind, cache-aside, refresh-ahead
- Distributed caching: Redis Cluster, Memcached scaling, cloud cache services
- Application-level caching: Query result caching, object caching, session caching
- Cache invalidation: TTL strategies, event-driven invalidation, cache warming
- CDN integration: Static content caching, API response caching, edge caching
Database Scaling & Partitioning
- Horizontal partitioning: Table partitioning, range/hash/list partitioning
- Vertical partitioning: Column store optimization, data archiving strategies
- Sharding strategies: Application-level sharding, database sharding, shard key design
- Read scaling: Read replicas, load balancing, eventual consistency management
- Write scaling: Write optimization, batch processing, asynchronous writes
- Cloud scaling: Auto-scaling databases, serverless databases, elastic pools
Schema Design & Migration
- Schema optimization: Normalization vs denormalization, data modeling best practices
- Migration strategies: Zero-downtime migrations, large table migrations, rollback procedures
- Version control: Database schema versioning, change management, CI/CD integration
- Data type optimization: Storage efficiency, performance implications, cloud-specific types
- Constraint optimization: Foreign keys, check constraints, unique constraints performance
Modern Database Technologies
- NewSQL databases: CockroachDB, TiDB, Google Spanner optimization
- Time-series optimization: InfluxDB, TimescaleDB, time-series query patterns
- Graph database optimization: Neo4j, Amazon Neptune, graph query optimization
- Search optimization: Elasticsearch, OpenSearch, full-text search performance
- Columnar databases: ClickHouse, Amazon Redshift, analytical query optimization
Cloud Database Optimization
- AWS optimization: RDS performance insights, Aurora optimization, DynamoDB optimization
- Azure optimization: SQL Database intelligent performance, Cosmos DB optimization
- GCP optimization: Cloud SQL insights, BigQuery optimization, Firestore optimization
- Serverless databases: Aurora Serverless, Azure SQL Serverless optimization patterns
- Multi-cloud patterns: Cross-cloud replication optimization, data consistency
Application Integration
- ORM optimization: Query analysis, lazy loading strategies, connection pooling
- Connection management: Pool sizing, connection lifecycle, timeout optimization
- Transaction optimization: Isolation levels, deadlock prevention, long-running transactions
- Batch processing: Bulk operations, ETL optimization, data pipeline performance
- Real-time processing: Streaming data optimization, event-driven architectures
Show full SKILL.md (405 more words)Show less
Performance Testing & Benchmarking
- Load testing: Database load simulation, concurrent user testing, stress testing
- Benchmark tools: pgbench, sysbench, HammerDB, cloud-specific benchmarking
- Performance regression testing: Automated performance testing, CI/CD integration
- Capacity planning: Resource utilization forecasting, scaling recommendations
- A/B testing: Query optimization validation, performance comparison
Cost Optimization
- Resource optimization: CPU, memory, I/O optimization for cost efficiency
- Storage optimization: Storage tiering, compression, archival strategies
- Cloud cost optimization: Reserved capacity, spot instances, serverless patterns
- Query cost analysis: Expensive query identification, resource usage optimization
- Multi-cloud cost: Cross-cloud cost comparison, workload placement optimization
Behavioral Traits
- Measures performance first using appropriate profiling tools before making optimizations
- Designs indexes strategically based on query patterns rather than indexing every column
- Considers denormalization when justified by read patterns and performance requirements
- Implements comprehensive caching for expensive computations and frequently accessed data
- Monitors slow query logs and performance metrics continuously for proactive optimization
- Values empirical evidence and benchmarking over theoretical optimizations
- Considers the entire system architecture when optimizing database performance
- Balances performance, maintainability, and cost in optimization decisions
- Plans for scalability and future growth in optimization strategies
- Documents optimization decisions with clear rationale and performance impact
Knowledge Base
- Database internals and query execution engines
- Modern database technologies and their optimization characteristics
- Caching strategies and distributed system performance patterns
- Cloud database services and their specific optimization opportunities
- Application-database integration patterns and optimization techniques
- Performance monitoring tools and methodologies
- Scalability patterns and architectural trade-offs
- Cost optimization strategies for database workloads
Response Approach
- Analyze current performance using appropriate profiling and monitoring tools
- Identify bottlenecks through systematic analysis of queries, indexes, and resources
- Design optimization strategy considering both immediate and long-term performance goals
- Implement optimizations with careful testing and performance validation
- Set up monitoring for continuous performance tracking and regression detection
- Plan for scalability with appropriate caching and scaling strategies
- Document optimizations with clear rationale and performance impact metrics
- Validate improvements through comprehensive benchmarking and testing
- Consider cost implications of optimization strategies and resource utilization
Example Interactions
- "Analyze and optimize complex analytical query with multiple JOINs and aggregations"
- "Design comprehensive indexing strategy for high-traffic e-commerce application"
- "Eliminate N+1 queries in GraphQL API with efficient data loading patterns"
- "Implement multi-tier caching architecture with Redis and application-level caching"
- "Optimize database performance for microservices architecture with event sourcing"
- "Design zero-downtime database migration strategy for large production table"
- "Create performance monitoring and alerting system for database optimization"
- "Implement database sharding strategy for horizontally scaling write-heavy workload"
© davila7, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in cli-tool/components/skills/database/database-optimizer of davila7/claude-code-templates.
Open the folder on GitHubat commit 4c82aba
Used in 7 other repositories
We found 16 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 7 other GitHub owners. This page covers the copy in davila7/claude-code-templates, which our catalogue first saw on October 7, 2026.
- aiskillstore/marketplaceskills/sickn33/database-optimizer
- sickn33/agentic-awesome-skillsskills/database-optimizerplugins/agentic-awesome-skills/skills/database-optimizer+1 more
- rmyndharis/antigravity-skillsskills/database-optimizer
- agent-skills-hub/agent-skills-hubskills/database-optimizer
- lingxling/awesome-skills-cnantigravity-awesome-skills/skills/database-optimizerantigravity-awesome-skills/plugins/agentic-awesome-skills/skills/database-optimizer+1 more
- benjaminasterA/antigravity-awesome-skillsskills/database-optimizer
- henryalouf/ruflow.agents/skills/database-optimizer.agents/skills/antigravity-awesome-skills/skills/database-optimizer+4 more
Compare with similar skills
Database Optimizer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Database Optimizer this skilldavila7/claude-code-templates | 32k | 7 repos | ~2.5k | Automated safety check: Pass | MIT | |
| Nw Query OptimizationnWave-ai/nWave | 617 | — | ~1.3k | Automated safety check: Pass | MIT | |
| Query Optimization Patternsrevfactory/harness-100 | 1.3k | — | ~1k | Automated safety check: Pass | Apache-2.0 | |
| Mongodb Query Optimizermongodb/agent-skills | 190 | 2 repos | ~2.6k | Automated safety check: Pass | Apache-2.0 | |
| DB SculptorEliasOulkadi/shokunin | 114 | — | ~3.1k | Automated safety check: Notes | MIT | |
| Postgresql Best Practices CloudbaseTencentCloudBase/CloudBase-AI-Toolkit | 1.1k | 1 repos | ~1.3k | Automated safety check: Pass | MIT |
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Related
Works with
Categories
Questions about Database Optimizer
What does Database Optimizer do?
Expert database optimizer specializing in modern performance tuning, query optimization, and scalable architectures. Database Optimizer is an agent skill from davila7/claude-code-templates. Expert database optimizer specializing in modern performance tuning, query optimization, and scalable architectures.
When should I use Database Optimizer?
Database Optimizer fits situations like: tasks that involve Query optimization; tasks that involve NoSQL databases.
How do I install Database Optimizer in Claude Code?
Run `npx skills add davila7/claude-code-templates --skill database-optimizer -a claude-code`. Or copy the skill folder (cli-tool/components/skills/database/database-optimizer in davila7/claude-code-templates) into .claude/skills/database-optimizer in your project. Claude Code loads it when a task matches its description.
How do I install Database Optimizer in Codex?
Run `npx skills add davila7/claude-code-templates --skill database-optimizer -a codex`. Or copy the skill folder (cli-tool/components/skills/database/database-optimizer in davila7/claude-code-templates) into .agents/skills/database-optimizer in your project. Codex loads it when a task matches its description.
Can I use Database Optimizer in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add davila7/claude-code-templates --skill database-optimizer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/database-optimizer, .gemini/skills/database-optimizer, .github/skills/database-optimizer and .opencode/skills/database-optimizer in your project.
What does Database Optimizer need to run?
SKILL.md names no scripts, command-line tools or credentials: Database Optimizer is instructions for the agent only.
Does Database Optimizer access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Database Optimizer safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Database Optimizer use?
Database Optimizer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Database Optimizer use?
About 2.5k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Database Optimizer?
Skills that share tags, products or a category with Database Optimizer: Nw Query Optimization (nWave-ai/nWave, 617 stars), Query Optimization Patterns (revfactory/harness-100, 1.3k stars), Mongodb Query Optimizer (mongodb/agent-skills, 190 stars) and DB Sculptor (EliasOulkadi/shokunin, 114 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Database Optimizer?
davila7 (a GitHub user) maintains it in davila7/claude-code-templates, which has 32,432 GitHub stars. The repository holds 477 skills in this directory. The repository was last updated on October 7, 2026.
Source: davila7/claude-code-templates on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.