Postgresql Best Practices Cloudbase
TencentCloudBase/CloudBase-AI-Toolkit
CloudBase PostgreSQL access-pattern and slow-query quality guidance.
SQL and NoSQL query optimization techniques, indexing strategies, execution plan analysis, JOIN algorithms, cardinality estimation, and database-specific query patterns
Install Nw Query Optimization
$ npx skills add nWave-ai/nWave --skill nw-query-optimization -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install nWave-ai/nWave nw-query-optimization --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/nWave-ai/nWave.git skills-src && mkdir -p .claude/skills && cp -r skills-src/nWave/skills/nw-query-optimization .claude/skills/nw-query-optimization && 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 "nw-query-optimization" agent skill from https://github.com/nWave-ai/nWave/tree/main/nWave/skills/nw-query-optimization into .claude/skills/nw-query-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nw-query-optimization", 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/nWave-ai/nWave/tree/main/nWave/skills/nw-query-optimizationType 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 nWave-ai/nWave --skill nw-query-optimization -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install nWave-ai/nWave nw-query-optimization --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nWave-ai/nWave.git skills-src && mkdir -p .agents/skills && cp -r skills-src/nWave/skills/nw-query-optimization .agents/skills/nw-query-optimization && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "nw-query-optimization" agent skill from https://github.com/nWave-ai/nWave/tree/main/nWave/skills/nw-query-optimization into .agents/skills/nw-query-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nw-query-optimization", 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 nWave-ai/nWave --skill nw-query-optimization -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install nWave-ai/nWave nw-query-optimization --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nWave-ai/nWave.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/nWave/skills/nw-query-optimization .cursor/skills/nw-query-optimization && 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 "nw-query-optimization" agent skill from https://github.com/nWave-ai/nWave/tree/main/nWave/skills/nw-query-optimization into .cursor/skills/nw-query-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nw-query-optimization", 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/nWave-ai/nWave.git --path nWave/skills/nw-query-optimization--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 nWave-ai/nWave --skill nw-query-optimization -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install nWave-ai/nWave nw-query-optimization --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nWave-ai/nWave.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/nWave/skills/nw-query-optimization .gemini/skills/nw-query-optimization && 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 "nw-query-optimization" agent skill from https://github.com/nWave-ai/nWave/tree/main/nWave/skills/nw-query-optimization into .gemini/skills/nw-query-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nw-query-optimization", 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 nWave-ai/nWave nw-query-optimizationInstalls 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 nWave-ai/nWave --skill nw-query-optimization -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/nWave-ai/nWave.git skills-src && mkdir -p .github/skills && cp -r skills-src/nWave/skills/nw-query-optimization .github/skills/nw-query-optimization && 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 "nw-query-optimization" agent skill from https://github.com/nWave-ai/nWave/tree/main/nWave/skills/nw-query-optimization into .github/skills/nw-query-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nw-query-optimization", 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 nWave-ai/nWave --skill nw-query-optimization -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install nWave-ai/nWave nw-query-optimization --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/nWave-ai/nWave.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/nWave/skills/nw-query-optimization .opencode/skills/nw-query-optimization && 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 "nw-query-optimization" agent skill from https://github.com/nWave-ai/nWave/tree/main/nWave/skills/nw-query-optimization into .opencode/skills/nw-query-optimization/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "nw-query-optimization", 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
nw-query-optimization- GitHub stars
- 617
- Token cost
- ~1.3k tokens
- SKILL.md length
- 499 words
- Files
- 1
- Skills in repo
- 106
- Repo updated
- First seen
- Licence
- MIT
At a glance
SQL and NoSQL query optimization techniques, indexing strategies, execution plan analysis, JOIN algorithms, cardinality estimation, and database-specific query patterns
- Tasks that involve Query optimization
- SKILL.md covers Cost-Based Optimization, Indexing Strategies, SQL Optimization Patterns and JOIN Algorithm Selection, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Tasks that involve NoSQL databases
What it does
Nw Query Optimization is an agent skill from nWave-ai/nWave. SQL and NoSQL query optimization techniques, indexing strategies, execution plan analysis, JOIN algorithms, cardinality estimation, and database-specific query patterns
Its SKILL.md is about 1.3k 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, NoSQL databases and SQL. It works with SQL. The repository describes itself as: AI agents that guide you from idea to working code, with you in control at every step. The licence is MIT.
When your agent uses it
- Tasks that involve Query optimization
- Tasks that involve NoSQL databases
- Tasks that involve SQL
Example prompts
- “/nw-query-optimization”
What it can do on your machine
Read from SKILL.md and the folder at commit da401a8. 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 (its code samples are sql and javascript).
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
Nw Query Optimization loads about 1.3k tokens when it runs. Until then it costs about 48 tokens; SKILL.md has 499 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 nWave-ai/nWave at commit da401a8, republished under its MIT licence (© nWave-ai). 499 words, ~1,333 tokens.
Download SKILL.mdSave it as
.claude/skills/nw-query-optimization/SKILL.md (or your agent's skills folder).- name
- nw-query-optimization
- description
- SQL and NoSQL query optimization techniques, indexing strategies, execution plan analysis, JOIN algorithms, cardinality estimation, and database-specific query patterns
- user-invocable
- false
- disable-model-invocation
- true
Query Optimization
Cost-Based Optimization
Modern relational DBs use cost-based optimizers (CBO): generate plan candidates -> estimate cost via statistics (row counts, distributions, selectivity) -> select lowest I/O/CPU/memory plan. Stale statistics lead to suboptimal plans.
Execution Plan Analysis
Validate optimization with EXPLAIN before and after changes.
-- PostgreSQL (add ANALYZE for actual runtime stats)
EXPLAIN ANALYZE SELECT order_id, total FROM orders WHERE customer_id = 12345;
-- MySQL: EXPLAIN FORMAT=JSON ... | SQL Server: SET STATISTICS IO ONKey indicators: Seq Scan/Table Scan = missing index | Index Scan/Seek = efficient | Hash Join = large equality joins | Nested Loop = small/indexed inner | Merge Join = pre-sorted inputs | Sort = watch disk spills
Indexing Strategies
B-Tree (Default)
Supports: equality, range, sorting, prefix matching | O(log n) lookup | General-purpose, all major DBs default
Hash
Equality only | O(1) lookup | High-cardinality exact-match | No range/sorting/pattern support
Covering Indexes
Include all query columns in index -> eliminates table access (index-only scan) | Trade-off: larger index, slower writes
-- Covering index for: SELECT name, email FROM users WHERE status = 'active'
CREATE INDEX idx_users_status_covering ON users(status) INCLUDE (name, email);PostgreSQL Specialized
- GiST: Geometric data, full-text search, nearest-neighbor
- GIN: Arrays, full-text search, JSONB queries
- BRIN: Large tables with physically correlated data (timestamps), minimal storage
- SP-GiST: Non-balanced structures, point-based geometric queries
Compound Index Design
Order by: 1. Equality conditions first (highest selectivity) | 2. Sort columns second | 3. Range conditions last
MongoDB ESR Rule
Equality-Sort-Range ordering for compound indexes:
// Query: status = "A", qty > 20, sorted by item
// Optimal index:
db.collection.createIndex({ status: 1, item: 1, qty: 1 })
// E(quality) S(ort) R(ange)SQL Optimization Patterns
Select Only Needed Columns
-- Bad: SELECT * retrieves unnecessary data, prevents covering indexes
SELECT * FROM orders WHERE customer_id = 12345;
-- Good: Specify columns, enables covering index
SELECT order_id, order_date, total FROM orders WHERE customer_id = 12345;Other Key Patterns
- CTEs: Improve readability but not always performance -- PostgreSQL may materialize CTEs (pre-v12), MySQL inlines them
- Window functions: Use
SUM() OVER,RANK() OVER (PARTITION BY ...)for analytics without self-joins - Pagination: Prefer keyset (
WHERE id > last_seen ORDER BY id LIMIT N) over OFFSET for deep pages - Parameterized queries: Prevent SQL injection AND enable plan caching (
cursor.execute("... WHERE id = %s", (id,)))
JOIN Algorithm Selection
| Algorithm | Best When | Cost |
|---|---|---|
| Nested Loop | Small outer table, indexed inner table | O(n * m) worst, O(n * log m) with index |
| Hash Join | Large tables, equality joins, no useful indexes | O(n + m) build + probe |
| Merge Join | Both inputs already sorted (index order) | O(n + m) after sort |
Show full SKILL.md (210 more words)Show less
Cardinality Estimation
Optimizer predicts row counts using: Histograms (value distribution) | Density vectors (non-histogram columns) | Statistics objects via ANALYZE (PostgreSQL) / UPDATE STATISTICS (SQL Server)
When estimation is wrong (correlated columns, skewed data, multi-table joins): 1. Run ANALYZE/UPDATE STATISTICS | 2. Create multi-column statistics | 3. Query hints as last resort
NoSQL Query Optimization
MongoDB
Place $match/$project early in pipelines | Use $lookup sparingly (left outer joins) | Compound indexes following ESR | Validate with explain("executionStats")
Cassandra
Always include partition key | Design tables around query patterns (query-first) | Use SAI over SASI (43% throughput gain) | Avoid ALLOW FILTERING (full cluster scan) | Materialized views add write overhead
DynamoDB
Use Query not Scan | Design partition keys for even distribution | GSIs for alternative access patterns | Single-table design with composite sort keys
Redis
FT.SEARCH for complex queries (RediSearch module) | Design key naming for efficient SCAN | Use pipelining for batch ops
Anti-Patterns to Detect
- **SELECT ***: Wastes I/O, prevents covering indexes
- Missing indexes on WHERE/JOIN/ORDER BY columns: full table scans
- N+1 queries: Fetch in loops instead of JOINs/batch
- Implicit type conversions: Prevents index use (WHERE varchar_col = 123)
- Functions on indexed columns:
WHERE UPPER(name) = 'JOHN'blocks index; use function-based indexes - Missing pagination: Unbounded result sets
- Hot partitions (NoSQL): Low-cardinality partition keys concentrate load
- ALLOW FILTERING (Cassandra): Expensive full-cluster scans
- Large partitions (Cassandra): >100MB degrades performance
© nWave-ai, 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 nWave/skills/nw-query-optimization of nWave-ai/nWave.
Open the folder on GitHubat commit da401a8
Compare with similar skills
Nw Query Optimization 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 |
|---|---|---|---|---|---|---|
| Nw Query Optimization this skillnWave-ai/nWave | 617 | — | ~1.3k | Automated safety check: Pass | MIT | |
| Postgresql Best Practices CloudbaseTencentCloudBase/CloudBase-AI-Toolkit | 1.1k | 1 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Query Expertjamesrochabrun/skills | 216 | — | ~4.3k | Automated safety check: Pass | MIT | |
| DatabasesMicrock/ordinary-claude-skills | 403 | — | ~1.9k | Automated safety check: Notes | MIT | |
| SQL Optimization Patternsynulihao/AgentSkillOS | 617 | 11 repos | ~3.3k | Automated safety check: Pass | None | |
| Query Engine Designrevfactory/claude-code-harness | 120 | — | ~474 | Automated safety check: Pass | None |
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Related
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Categories
Questions about Nw Query Optimization
What does Nw Query Optimization do?
SQL and NoSQL query optimization techniques, indexing strategies, execution plan analysis, JOIN algorithms, cardinality estimation, and database-specific query patterns. Nw Query Optimization is an agent skill from nWave-ai/nWave.
When should I use Nw Query Optimization?
Nw Query Optimization fits situations like: tasks that involve Query optimization; tasks that involve NoSQL databases; tasks that involve SQL.
How do I install Nw Query Optimization in Claude Code?
Run `npx skills add nWave-ai/nWave --skill nw-query-optimization -a claude-code`. Or copy the skill folder (nWave/skills/nw-query-optimization in nWave-ai/nWave) into .claude/skills/nw-query-optimization in your project. Claude Code loads it when a task matches its description.
How do I install Nw Query Optimization in Codex?
Run `npx skills add nWave-ai/nWave --skill nw-query-optimization -a codex`. Or copy the skill folder (nWave/skills/nw-query-optimization in nWave-ai/nWave) into .agents/skills/nw-query-optimization in your project. Codex loads it when a task matches its description.
Can I use Nw Query Optimization 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 nWave-ai/nWave --skill nw-query-optimization -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/nw-query-optimization, .gemini/skills/nw-query-optimization, .github/skills/nw-query-optimization and .opencode/skills/nw-query-optimization in your project.
What does Nw Query Optimization need to run?
SKILL.md names no scripts, command-line tools or credentials: Nw Query Optimization is instructions for the agent only.
Does Nw Query Optimization 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 Nw Query Optimization 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 Nw Query Optimization use?
Nw Query Optimization 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 Nw Query Optimization use?
About 1.3k tokens (SKILL.md is roughly 5.3k 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 Nw Query Optimization?
Skills that share tags, products or a category with Nw Query Optimization: Postgresql Best Practices Cloudbase (TencentCloudBase/CloudBase-AI-Toolkit, 1.1k stars), Query Expert (jamesrochabrun/skills, 216 stars), Databases (Microck/ordinary-claude-skills, 403 stars) and SQL Optimization Patterns (ynulihao/AgentSkillOS, 617 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Nw Query Optimization?
nWave-ai (a GitHub organization) maintains it in nWave-ai/nWave, which has 617 GitHub stars. The repository holds 106 skills in this directory. The repository was last updated on September 16, 2026.
Source: nWave-ai/nWave on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.