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/xspoonai/spoon-awesome-skill/db-sql-runnernpx skills add XSpoonAi/spoon-awesome-skill --skill db-sql-runnergit clone --depth 1 https://github.com/XSpoonAi/spoon-awesome-skillWrote 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/xspoonai/spoon-awesome-skill/db-sql-runner)<a href="https://agentmods.dev/skills/xspoonai/spoon-awesome-skill/db-sql-runner"><img src="https://agentmods.dev/badge/skills/xspoonai/spoon-awesome-skill/db-sql-runner.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 | $0.00005 | $0.00325 |
| Opus 5 | $0.00003 | $0.00162 |
| Sonnet 5 | $0.00001 | $0.00065 |
| Haiku 4.5 | $0.00001 | $0.00032 |
Grade A, and why
db-sql-runner 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
What ships with it
2 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.
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 · 73 lines · 5 tokens per session scan A d646b91886fe
db-sql-runner is a skill published in the GitHub repository XSpoonAi/spoon-awesome-skill (17 stars, last pushed 5mo ago), with no licence file. It adds 5 tokens to every session and 325 once invoked, about $0.0000 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 2026-08-30.
Other skills, from other repositories
kotlin-exposed-patterns
JetBrains Exposed ORM patterns including DSL queries, DAO pattern, transactions, HikariCP connection pooling, Flyway migrations, and repository pattern.
db-migrator
数据库迁移助手 - Schema 对比、迁移脚本生成.
database-seeding
Populate databases with realistic, reproducible test data for development, testing, and staging environments. Use when the user requests database seeding or provides relevant inputs for this workflow.
database-migration
Create, execute, and roll back versioned database schema migrations using tools like Alembic, Prisma Migrate, Flyway, and Knex. Use when the user requests database migration or provides relevant inputs for this workflow.
database-schema-design
Design normalized database schemas with tables, relationships, indexes, and constraints for any application domain. Use when the user requests database schema design or provides relevant inputs for this workflow.
AgentDB Performance Optimization
Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.