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 curiositech/some_claude_skills --skill postgresql-optimizationgit clone --depth 1 https://github.com/curiositech/some_claude_skillsWrote 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/curiositech/some_claude_skills/postgresql-optimization)<a href="https://agentmods.dev/skills/curiositech/some_claude_skills/postgresql-optimization"><img src="https://agentmods.dev/badge/skills/curiositech/some_claude_skills/postgresql-optimization/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/curiositech/some_claude_skills/postgresql-optimization"><img src="https://agentmods.dev/badge/skills/curiositech/some_claude_skills/postgresql-optimization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 202 Skill allows unbounded resource consumption (API calls, storage, compute). Without rate limits or quotas, a compromised or misbehaving agent can cause denial-of-service or cost overruns.Fix: Set explicit rate limits, timeouts, and resource quotas for API calls, file operations, and compute. Implement circuit breakers for runaway loops.
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 | $0.00043 | $0.02272 |
| Opus 5 | $0.00022 | $0.01136 |
| Sonnet 5 | $0.00009 | $0.00454 |
| Haiku 4.5 | $0.00004 | $0.00227 |
Grade A, and why
postgresql-optimization 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 8d 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 — 296 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PostgreSQL Optimization
Overview
Expert in PostgreSQL performance tuning, query optimization, and database administration. Specializes in EXPLAIN analysis, indexing strategies, connection pooling, partitioning, and production-grade PostgreSQL operations.
When to Use
- Diagnosing slow queries with EXPLAIN ANALYZE
- Creating optimal indexes for query patterns
- Designing database schemas for performance
- Configuring PostgreSQL for production workloads
- Implementing connection pooling (PgBouncer, Supavisor)
- Setting up partitioning for large tables
- Analyzing and reducing lock contention
- Migrating or upgrading PostgreSQL versions
Capabilities
Query Optimization
- EXPLAIN / EXPLAIN ANALYZE interpretation
- Query plan analysis and optimization
- Identifying sequential scans vs index scans
- Join optimization and query rewriting
- CTE vs subquery performance trade-offs
- Window function optimization
Indexing Strategies
- B-tree, GIN, GiST, BRIN index selection
- Partial indexes for filtered queries
- Expression indexes for computed values
- Covering indexes (INCLUDE clause)
- Index-only scans optimization
- Concurrent index creation
Schema Design
- Normalization vs denormalization trade-offs
- JSONB column design and indexing
- Array columns and operations
- Enum types vs lookup tables
- Foreign key cascade strategies
- Table inheritance and partitioning
Configuration Tuning
- Memory settings (shared_buffers, work_mem, effective_cache_size)
- Connection limits and pooling
- WAL and checkpoint tuning
- Autovacuum configuration
- Statistics collection settings
Advanced Features
- Partitioning (range, list, hash)
- Materialized views with refresh strategies
- Full-text search with tsvector/tsquery
- PostGIS geospatial queries
- Logical replication setup
- pg_stat_statements analysis
Dependencies
Works well with:
database-modeler- Schema design and ERD creationdata-pipeline-engineer- ETL and data processingsite-reliability-engineer- Database monitoring and alertingnextjs-app-router-expert- Full-stack data fetching
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.
- 8d ago First seen · 296 lines · 43 tokens per session scan A e33a2420d403
postgresql-optimization is a skill published in the GitHub repository curiositech/some_claude_skills (219 stars, last pushed 5d ago), licensed MIT. It adds 43 tokens to every session and 2,272 once invoked, about $0.0002 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 2026-09-03.
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