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 agentmods add skills/methasit-pun/data_engineer_claude_skills/sql-patternsnpx skills add Methasit-Pun/data_engineer_claude_skills --skill sql-patternsgit clone --depth 1 https://github.com/Methasit-Pun/data_engineer_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/methasit-pun/data_engineer_claude_skills/sql-patterns)<a href="https://agentmods.dev/skills/methasit-pun/data_engineer_claude_skills/sql-patterns"><img src="https://agentmods.dev/badge/skills/methasit-pun/data_engineer_claude_skills/sql-patterns.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 | $0.00137 | $0.01565 |
| Opus 5 | $0.00068 | $0.00783 |
| Sonnet 5 | $0.00027 | $0.00313 |
| Haiku 4.5 | $0.00014 | $0.00156 |
Grade A, and why
sql-patterns 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 3d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 3d ago First seen · 187 lines · 137 tokens per session scan A 1d608040e872
sql-patterns is a skill published in the GitHub repository Methasit-Pun/data_engineer_claude_skills (1 stars, last pushed 1mo ago), with no licence file. It adds 137 tokens to every session and 1,565 once invoked, about $0.0007 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 2026-08-31.
Other skills, from other repositories
dbt-troubleshoot
Debug dbt errors — compilation failures, runtime database errors, test failures, wrong data, and performance issues. Use when something is broken, producing wrong results, or failing to build. Powered by altimate-dbt.
dbt-unit-tests
Generate dbt unit tests automatically for any model. Analyzes SQL logic (CASE/WHEN, JOINs, window functions, NULLs), creates type-correct mock inputs from manifest schema, and assembles complete YAML. Use when a user says "generate tests", "add unit tests", "test this model", or "test coverage" for dbt models.
dbt-pr-review
Cloudflare-style AI code review for dbt/SQL pull requests. Produces a signed APPROVE/COMMENT/REQUESTCHANGES verdict where every blocking finding is backed by a deterministic engine call — column-lineage blast radius, query equivalence, PII classification, and A–F grade. Use to review a dbt PR or the working-tree…
query-optimize
Analyze and optimize SQL queries for better performance.
lineage-diff
Compare column-level lineage between two versions of a SQL query to show added, removed, and changed data flow edges.
ktx-analytics
Use when answering a question that needs data from a ktx-connected database - investigating, analyzing, "how many", "show me", "what's the breakdown of", finding records by value, exploring tables, comparing periods, explaining metrics, or any data-analysis request. Triggers even when the user does not say…