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 arbazkhan971/godmode --skill ormgit clone --depth 1 https://github.com/arbazkhan971/godmodeWrote 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/arbazkhan971/godmode/orm)<a href="https://agentmods.dev/skills/arbazkhan971/godmode/orm"><img src="https://agentmods.dev/badge/skills/arbazkhan971/godmode/orm/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/arbazkhan971/godmode/orm"><img src="https://agentmods.dev/badge/skills/arbazkhan971/godmode/orm.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 Tool Misuse · line 137 Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
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 | $0.00008 | $0.01132 |
| Opus 5 | $0.00004 | $0.00566 |
| Sonnet 5 | $0.00002 | $0.00226 |
| Haiku 4.5 | $0.00001 | $0.00113 |
Grade A, and why
orm 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.
How it starts
The opening of the file, as written. The whole thing — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Activate When
/godmode:orm, "which ORM", "Prisma vs Drizzle"- "N+1 query", "connection pool", "transaction"
- ORM usage audit for performance issues
Workflow
1. Detect Environment
grep -r "prisma\|drizzle-orm\|typeorm\|sqlalchemy" \
package.json requirements.txt go.mod 2>/dev/null
grep -r "include:\|select_related\|joinedload" \
--include="*.ts" --include="*.py" -l 2>/dev/null
Language: <TS|Python|Go|Ruby|Java>
ORM: <Prisma|Drizzle|TypeORM|SQLAlchemy|Django|GORM>
Database: <PostgreSQL|MySQL|SQLite>
Connection: <direct|pooler|serverless>
2. ORM Selection
TypeScript/JavaScript:
- Prisma: max type safety, great DX, schema-first. Heavy engine (~2MB). Best for most projects.
- Drizzle: SQL-first, ~30KB, edge-ready. Best for performance-critical or serverless.
- TypeORM: decorator-based, NestJS integration.
Python: SQLAlchemy 2.0 (FastAPI), Django ORM. Go: GORM, Ent, sqlc. Ruby: ActiveRecord.
IF edge/serverless: Drizzle (smallest bundle). IF max type safety: Prisma.
3. N+1 Detection & Resolution
Enable query logging, load list page, count queries. If count = 1 + N, you have N+1.
// BAD (N+1): queries in loop
const posts = await prisma.post.findMany();
for (const p of posts) {
await prisma.user.findUnique({
where: { id: p.authorId }
});
}
// GOOD (1 query with JOIN)
const posts = await prisma.post.findMany({
include: { author: true }
});
ORM equivalents: Django select_related/prefetch,
SQLAlchemy joinedload/selectinload,
Rails includes/eager_load, GORM Preload/Joins.
4. Connection Pooling
Formula: pool_size = (core_count * 2) + 1
Typical: 10-20 connections per instance
| Dev | Prod
min | 1 | 5
max | 5 | 20
idle_timeout | 30s | 300s
WARNING: PostgreSQL degrades above ~100 connections.
Use PgBouncer/RDS Proxy for multiplexing.
Coordinate: pool * instances < max_conn * 0.8.
IF pool utilization > 80%: alert and investigate.
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 · 149 lines · 8 tokens per session scan A 6dc4a3eccd92
orm is a skill published in the GitHub repository arbazkhan971/godmode (26 stars, last pushed 14d ago), licensed MIT. It adds 8 tokens to every session and 1,132 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 2026-09-03.
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