Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add isdaniel/pgtuner_mcp --skill pg-query-rewritegit clone --depth 1 https://github.com/isdaniel/pgtuner_mcpWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/isdaniel/pgtuner_mcp/pg-query-rewrite)<a href="https://agentmods.dev/skills/isdaniel/pgtuner_mcp/pg-query-rewrite"><img src="https://agentmods.dev/badge/skills/isdaniel/pgtuner_mcp/pg-query-rewrite.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00067 | $0.03097 |
| Opus 5 | $0.00034 | $0.01548 |
| Sonnet 5 | $0.00013 | $0.00619 |
| Haiku 4.5 | $0.00007 | $0.00310 |
Grade A, and why
pg-query-rewrite scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 371 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PostgreSQL Query Rewrite Patterns
This skill guides the agent through analyzing SQL queries and applying common restructuring patterns to improve performance, using pgtuner-mcp execution plan analysis tools.
When to Use This Skill
Use this skill when the user:
- Has a specific slow query and wants it rewritten for better performance
- Asks "how can I make this query faster?"
- Reports that adding indexes didn't help (query structure is the issue)
- Has queries with subqueries, CTEs, OR conditions, or NOT IN that could be improved
- Asks about query optimization patterns or best practices
- Has queries with
SELECT *or inefficient pagination
MCP Resources Available
pgtuner://docs/tools-- Reference foranalyze_queryparameters and optionspgtuner://query/{query_hash}/stats-- Get statistics for a specific query by itsqueryidpgtuner://table/{schema}/{table_name}/indexes-- Check available indexes on involved tables
Related MCP Prompt
This skill is closely related to the query_tuning MCP Prompt, which provides a structured query optimization workflow.
Prerequisites
- The pgtuner-mcp server must be connected with a valid
DATABASE_URI - Required:
pg_stat_statementsextension (for identifying slow queries to rewrite) - The user should provide the specific SQL query to optimize
Agent Decision Tree
Start: User provides a slow query
|
+--> Step 1: Analyze the execution plan
|
+--> Look at the plan for these patterns:
|
+--> SubPlan / Correlated Subquery?
| --> Apply Pattern 1: Subquery to JOIN
|
+--> CTE Scan with many rows materialized?
| --> Apply Pattern 2: CTE Materialization Control
|
+--> BitmapOr / multiple OR conditions?
| --> Apply Pattern 3: OR to UNION ALL
|
+--> NOT IN with possible NULLs?
| --> Apply Pattern 4: NOT IN to NOT EXISTS
|
+--> Seq Scan on query with OFFSET + LIMIT?
| --> Apply Pattern 5: Keyset Pagination
|
+--> Many columns fetched but few used?
| --> Apply Pattern 6: Eliminate SELECT *
|
+--> Sort on non-indexed column?
| --> Recommend index (redirect to pg-index-optimization)
|
+--> No obvious rewrite opportunity?
--> Check statistics freshness (ANALYZE table)
--> Check index recommendations
--> Consider configuration tuning (work_mem, etc.)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 371 lines · 67 tokens per session scan A 7955c48bf087
pg-query-rewrite is a skill published in the GitHub repository isdaniel/pgtuner_mcp (29 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 67 tokens to every session and 3,097 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
amazon aurora dsql
Deprecated compatibility redirect for Aurora DSQL guidance. Use when a request concerns DSQL, Aurora DSQL, distributed SQL, DSQL schemas, migrations, queries, authentication, performance, or application development.
exasol-table-design
Exasol table design for performance: DISTRIBUTE BY, PARTITION BY, zone maps, data types, replication, surrogate keys, and CREATE TABLE syntax.
exasol-import-export
Exasol IMPORT and EXPORT SQL statements: syntax, file formats (CSV, FBV, Parquet), cloud storage (S3, Azure, GCS), connection objects, error handling, and ETL staging patterns.
exasol-system-tables
Exasol system and statistics tables: what they contain, visibility prefixes (EXAALL, EXADBA, EXAUSER), and when to query them directly vs using MCP tools.
exasol-udfs
Exasol User-Defined Functions (UDFs) and Scripts: CREATE SCRIPT syntax, language options, SQL-to-language data type mappings, ExaIterator API, BucketFS access, and Script Language Containers.
exasol-sql-dialect
Exasol SQL dialect specifics: syntax, data types, functions, and common pitfalls for generating correct Exasol SQL.