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 niels-emmer/myace --skill query-performancegit clone --depth 1 https://github.com/niels-emmer/myaceWrote 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/niels-emmer/myace/query-performance)<a href="https://agentmods.dev/skills/niels-emmer/myace/query-performance"><img src="https://agentmods.dev/badge/skills/niels-emmer/myace/query-performance/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/niels-emmer/myace/query-performance"><img src="https://agentmods.dev/badge/skills/niels-emmer/myace/query-performance.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 | $0.00029 | $0.00471 |
| Opus 5 | $0.00015 | $0.00235 |
| Sonnet 5 | $0.00006 | $0.00094 |
| Haiku 4.5 | $0.00003 | $0.00047 |
Grade A, and why
Query Performance 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 8d 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
Purpose
A query that works on a toy dataset but degrades under real data volume is a defect, not a surprise. This skill is a checklist for verifying that queries are indexed for the access patterns the application actually uses, and that the plan matches intent before the query ships.
When to use it
Every time you write or review a query that touches a table with meaningful data volume — not just for "slow" queries. The discipline should be automatic.
Checklist
- Index for the queries you actually run. Add indexes based on measured access patterns, not speculation. Every index has a write cost; don't index a pattern nothing executes.
- Verify with
EXPLAIN. Confirm the plan uses the index you expect, not a full-table scan. If the plan doesn't match intent, the query isn't done. - Watch for N+1. A loop that issues one query per row is the most common performance defect in application code. Batch the fetch or join instead.
- Test with realistic data. Profile against data volume and distribution that resembles production, not a handful of rows. A plan that's fine on 100 rows can be catastrophic on 10 million.
- Check the write path too. Inserts/updates that touch many rows, or that fight an index, are as important as read performance. Batch writes where the pattern allows.
- Flag full-table scans in review. A scan on a hot table is a review finding, even if it's "fast enough" today — it won't stay that way.
Expected output
Queries that are verified against a realistic plan (via EXPLAIN), indexed for the access patterns the application actually executes, and free of N+1 and full-table-scan surprises — with the performance work treated as part of the change, not a follow-up.
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.
- 8d ago First seen · 28 lines · 29 tokens per session scan A acf9706aea09
Query Performance is a skill published in the GitHub repository niels-emmer/myace (1 stars, last pushed 5d ago), licensed MIT. It adds 29 tokens to every session and 471 once invoked, about $0.0001 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 2026-09-03.
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