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/query-optimize/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/query-optimize)<a href="https://agentmods.dev/skills/altimateai/altimate-code/query-optimize"><img src="https://agentmods.dev/badge/skills/altimateai/altimate-code/query-optimize/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/query-optimize"><img src="https://agentmods.dev/badge/skills/altimateai/altimate-code/query-optimize.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 | $0.00012 | $0.00924 |
| Opus 5.5 | $0.00005 | $0.00370 |
| Sonnet 5.5 | $0.00002 | $0.00185 |
| Haiku 4.5 | $0.00001 | $0.00092 |
Grade A, and why
query-optimize 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 — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Query Optimize
Requirements
Agent: any (read-only analysis)
Tools used: altimate_core_rewrite (with verify_equivalence: true), sql_analyze, sql_explain, read, glob, schema_inspect, warehouse_list
Analyze SQL queries for performance issues and suggest concrete optimizations including rewritten SQL.
Workflow
-
Get the SQL query -- Either:
- Read SQL from a file path provided by the user
- Accept SQL directly from the conversation
- Read from clipboard or stdin if mentioned
-
Determine the dialect -- Default to
snowflake. If the user specifies a dialect (postgres, bigquery, duckdb, etc.), use that instead. Check the project for warehouse connections usingwarehouse_listif unsure. -
Run the verified optimizer:
- If the user has a warehouse connection, first call
schema_inspecton the relevant tables to build schema context (needed both for better rewrites — e.g. SELECT * expansion — and to verify equivalence) - Call
altimate_core_rewritewith the SQL, schema context, andverify_equivalence: true. This proposes rewrites AND proves each one returns the same results as the original in a single step. The result is partitioned into verified-equivalent rewrites (safe to apply) and unverified rewrites (review before applying), so you never recommend a rewrite that silently changes semantics.
- If the user has a warehouse connection, first call
-
Run detailed analysis:
- Call
sql_analyzewith the same SQL and dialect to get the full anti-pattern breakdown with recommendations
- Call
-
Get execution plan (if warehouse connected):
- Call
sql_explainto run EXPLAIN on the query and get the execution plan - Look for: full table scans, sort operations on large datasets, inefficient join strategies, missing partition pruning
- Include key findings in the report under "Execution Plan Insights"
- Call
-
Equivalence verification is built into step 3 (
verify_equivalence: true):- Present the verified-equivalent rewrites as safe to apply.
- Present unverified rewrites separately with their reason ("review before applying") — do not recommend applying these without manual review.
- If no schema was available, all rewrites come back unverified; say so and recommend supplying a schema (or a warehouse connection) to enable verification.
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 · 87 lines · 12 tokens per session scan A 643cd0ec1391
query-optimize is a skill published in the GitHub repository AltimateAI/altimate-code (813 stars, last pushed today), licensed MIT. It adds 12 tokens to every session and 924 once invoked, about $0.0000 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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