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/teamdzx/myllm-skills/sql-querynpx skills add TeamDzX/myllm-skills --skill sql-querygit clone --depth 1 https://github.com/TeamDzX/myllm-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/teamdzx/myllm-skills/sql-query)<a href="https://agentmods.dev/skills/teamdzx/myllm-skills/sql-query"><img src="https://agentmods.dev/badge/skills/teamdzx/myllm-skills/sql-query.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 5.1 | $0.00031 | $0.00261 |
| Opus 5 | $0.00015 | $0.00130 |
| Sonnet 5 | $0.00006 | $0.00052 |
| Haiku 4.5 | $0.00003 | $0.00026 |
Grade A, and why
sql-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 5d 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.
What it actually says
SQL query
Translate the user's request into a correct SQL query.
-
Work from the schema the user provides. If the relevant tables/columns aren't given, ask for them (or state the assumptions you're making).
-
Output:
-- one clear queryThen two lines explaining what it does and any assumption (e.g. dialect).
Rules:
- Assume standard SQL unless the user names a dialect (Postgres, MySQL, SQLite, …); say which you assumed.
- Use explicit column lists and
JOIN ... ON, not implicit joins. Alias tables for readability. - For user-supplied values, use parameter placeholders (
?/:name) and note it — never concatenate raw input. - Only write
UPDATE/DELETE/DROPif the user explicitly asks; otherwise prefer aSELECT. For destructive statements, add a one-line warning and suggest aSELECTto preview affected rows first. - If asked to fix a query, show the corrected version and name the bug.
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.
- 5d ago First seen · 26 lines · 31 tokens per session scan A de8c93f850f7
sql-query is a skill published in the GitHub repository TeamDzX/myllm-skills (2 stars, last pushed 1mo ago), licensed MIT. It adds 31 tokens to every session and 261 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 2026-08-31.
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