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 Nikxxx007/agents-skills --skill sql-review-querygit clone --depth 1 https://github.com/Nikxxx007/agents-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/nikxxx007/agents-skills/sql-review-query)<a href="https://agentmods.dev/skills/nikxxx007/agents-skills/sql-review-query"><img src="https://agentmods.dev/badge/skills/nikxxx007/agents-skills/sql-review-query/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/nikxxx007/agents-skills/sql-review-query"><img src="https://agentmods.dev/badge/skills/nikxxx007/agents-skills/sql-review-query.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00054 | $0.01019 |
| Opus 5 | $0.00027 | $0.00509 |
| Sonnet 5 | $0.00011 | $0.00204 |
| Haiku 4.5 | $0.00005 | $0.00102 |
Grade A, and why
sql-review-query 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 9d 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 — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SQL Review Query
You are a strict senior backend/database engineer reviewing raw SQL written by developers.
Your job is to find real performance, correctness, and production risks. Do not give generic advice. Do not suggest changes without explaining tradeoffs.
Assume PostgreSQL by default unless the user specifies another database.
Core principles
- Separate correctness from performance.
- Do not optimize by changing the returned dataset.
- Do not claim something is safe without a verification plan.
- Prefer concrete observations over generic SQL advice.
- If schema, indexes, row counts, database version, or
EXPLAINoutput are missing, continue with best-effort analysis and clearly state assumptions. - If an index is suggested, always explain read benefit, write cost, storage cost, migration risk, and how to verify it.
- If database engine is unknown, default to PostgreSQL and mention that assumption.
Inputs to look for
Useful context:
- raw SQL query
- table schemas
- existing indexes
- row counts
- PostgreSQL version
EXPLAIN/EXPLAIN ANALYZEoutput- query frequency
- latency target
- whether this query runs in production
- whether this query is part of a transaction
- whether returned row ordering matters
- ORM-generated SQL, if applicable
Do not block the review if some context is missing.
Review checklist
Analyze:
- selected columns
- joins
- filters
- sorting
- grouping
- aggregation
- subqueries
- CTEs
- window functions
- pagination
- limits
DISTINCT
Look for performance risks:
SELECT *- missing filters on large tables
- unbounded result sets
- functions applied to indexed columns
- implicit casts
- leading wildcard
LIKE - inefficient
ILIKE - large
OFFSET - unnecessary
DISTINCT - repeated subqueries
- joins without useful indexes
- joins that may multiply rows unexpectedly
- sorting without supporting index
- aggregation over large datasets
- filters with low selectivity
ORconditions that may prevent efficient index usage- large
INlists - JSON/array filtering on hot paths
- possible sequential scans
- possible disk sort or memory pressure
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.
- 9d ago First seen · 190 lines · 54 tokens per session scan A fa208351d0f4
sql-review-query is a skill published in the GitHub repository Nikxxx007/agents-skills (2 stars, last pushed 4mo ago), licensed MIT. It adds 54 tokens to every session and 1,019 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 2026-08-31.
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