Borrowing it
Nothing to install: this file belongs to AltimateAI/altimate-code. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/AltimateAI/altimate-code/main/.opencode/skills/sql-review/SKILL.mdgit clone --depth 1 https://github.com/AltimateAI/altimate-codeWrote 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/altimateai/altimate-code/sql-review)<a href="https://agentmods.dev/skills/altimateai/altimate-code/sql-review"><img src="https://agentmods.dev/badge/skills/altimateai/altimate-code/sql-review/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/altimateai/altimate-code/sql-review"><img src="https://agentmods.dev/badge/skills/altimateai/altimate-code/sql-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00041 | $0.00944 |
| Opus 5.5 | $0.00016 | $0.00378 |
| Sonnet 5.5 | $0.00008 | $0.00189 |
| Haiku 4.5 | $0.00004 | $0.00094 |
Grade A, and why
sql-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SQL Review
Requirements
Agent: any (read-only analysis) Tools used: altimate_core_check, altimate_core_grade, sql_analyze, read, glob, bash (for git operations)
When to Use This Skill
Use when the user wants to:
- Review SQL quality before merging a PR
- Get a quality grade (A-F) on a query or model
- Run a comprehensive lint + safety + syntax check in one pass
- Audit SQL files in a directory for anti-patterns
Do NOT use for:
- Optimizing query performance -> use
query-optimize - Fixing broken SQL -> use
dbt-troubleshoot - Translating between dialects -> use
sql-translate
Workflow
1. Collect SQL to Review
Either:
- Read SQL from a file path provided by the user
- Accept SQL directly from the conversation
- Auto-detect changed SQL files from git:
git diff --name-only HEAD~1 | grep '\.sql$'
For dbt models, compile first to get the full SQL:
altimate-dbt compile --model <name>
2. Run Comprehensive Check
Call altimate_core_check — this is the single-call code review that composes:
- Syntax validation: Parse errors with line/column positions
- Lint (26 anti-patterns): SELECT *, unused CTEs, implicit casts, NULL comparisons, missing WHERE on DELETE/UPDATE, cartesian joins, non-sargable predicates, missing partition filters, and more
- Injection scan: Tautology attacks, UNION injection, stacked queries, comment injection, Jinja template injection
- PII exposure: Flags queries accessing columns classified as PII
altimate_core_check(sql: <sql>, schema_context: <schema_object>)
3. Grade the SQL
Call altimate_core_grade to get an A-F quality score with per-category breakdown:
altimate_core_grade(sql: <sql>, schema_context: <schema_object>)
Categories scored:
- Readability: Naming, formatting, CTE structure
- Performance: Anti-patterns, index usage, scan efficiency
- Correctness: NULL handling, join logic, type safety
- Best Practices: Explicit columns, proper materialization hints
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.
- 1mo ago First seen · 119 lines · 41 tokens per session scan A 9de026d5636e
sql-review is a skill published in the GitHub repository AltimateAI/altimate-code (813 stars, last pushed today), licensed MIT. It adds 41 tokens to every session and 944 once invoked, about $0.0002 per session on Opus 5.5. 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.
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