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 simota/agent-skills --skill tunergit clone --depth 1 https://github.com/simota/agent-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/simota/agent-skills/tuner)<a href="https://agentmods.dev/skills/simota/agent-skills/tuner"><img src="https://agentmods.dev/badge/skills/simota/agent-skills/tuner/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/simota/agent-skills/tuner"><img src="https://agentmods.dev/badge/skills/simota/agent-skills/tuner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Prompt Injection · line 6 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- medium Excessive Agency · line 106 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00043 | $0.05485 |
| Opus 5.5 | $0.00017 | $0.02194 |
| Sonnet 5.5 | $0.00009 | $0.01097 |
| Haiku 4.5 | $0.00004 | $0.00549 |
Grade A, and why
tuner 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 17d 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 — 272 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tuner
Database-performance specialist for query plans, slow-query analysis, index strategy, ORM hot paths, connection pools, and database observability. Tuner complements Schema and does not guess at bottlenecks.
What ships with it
23 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- _common 10 B
- reference/_common 13 B
- reference/cache-strategy.md 7.3 KB
- reference/cloud-db-optimization-patterns.md 14 KB
- reference/connection-pool-tuning.md 14 KB
- reference/db-monitoring-observability.md 5.3 KB
- reference/db-specific-query-visualization.md 2.7 KB
- reference/explain-analyze-guide.md 1.5 KB
- reference/fix-prompt-generation.md 8.3 KB
- reference/materialized-views-partitioning.md 2.4 KB
- reference/n1-detection-cache-orm.md 1.9 KB
- reference/optimization-patterns.md 2.8 KB
- reference/orm-performance-pitfalls.md 6.9 KB
- reference/performance-report-template.md 888 B
- reference/postgresql-17-performance.md 3.5 KB
- reference/postgresql-18-performance.md 13 KB
- reference/postgresql-19-preview.md 4.3 KB
- reference/query-index-anti-patterns.md 2.4 KB
- reference/slow-query-benchmarks.md 13 KB
- reference/tuner 11 B
- reference/vacuum-autovacuum-tuning.md 8.9 KB
- reference/vector-search-query-optimization.md 9.7 KB
- reference/workflow-detail.md 1.3 KB
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.
- 17d ago Changed 89ab722f1a8e
- 1mo ago Changed · -2 lines 83b4a8da8a72
- 1mo ago Changed 64a7e43f69d7
- 1mo ago Changed · -1 lines 2a5c6934aaf9
- 1mo ago Changed 50c39caa8260
- 1mo ago First seen · 275 lines · 43 tokens per session scan A cf73f56bb859
tuner is a skill published in the GitHub repository simota/agent-skills (95 stars, last pushed yesterday), licensed MIT. It adds 43 tokens to every session and 5,485 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 2026-09-03.
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